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338
10
LlDAR Remote Sensi"'l
LI[
u. Table 10- 1.
-
("haradcrisllcs of L1DAR.Ja1a collected on the Sa vannah River Site on Octobe r 10. 200t
Vend or
Date
pe r sec
Sanborn. Inc.
Optcch Al TM
10-10-04
50,000 tSOk Hl)
20~
Nominal
Pul ses
UDAR sensor
Wave length 1046
om
Scan angle
post spacing
;t1O
C:Vl."ry J() em in r and}
"i n
a: ((
th C te
r,
craft (h) AGL. th e instantaneous angular scanning speed (a...., ) in radians per second. and the instanran..-ous scan angle 10_> [ Baltsavias. 191)()b ):
the scan angle orthe U DAR atj he lime of' the l ascr ~
a o
the effect o f atmos pheric refraction on the speed of light:
I I
(1O-5)
Actual sampling dcns itic-s for an I1rt'
the laser pulse travel t ime from the UDAR instruI:le!l the larget (ground) and lu ck. It is useful til delv e more deeply into several ofthese patm" eters. For the purposes o f discuss ion, we w ill use UD..IJ data of the Savannah Rive r Sue nea r A iken, SC collected October 10. 2004. The data " ere acq uired using a U DAl that transmitted ;O.()(M"} rll l ~s of near- infra red (\().16 iii 11I"",r light pe r second, The UDAR data acqu isition ~ii cations arc surmu arizcd in Table 10-\ (Sa nborn. 2005)
LlDAR Laser Location T he ma ximum u lT-l1
lt i ~ import ant to know the exact loc at ion o r the U DAR jse at all rime s during data co llect ion. This is accomplisbcrl using Differcnuat Global Posit ioni ng Sys tem (D GI'Sj led\llo logy. lXi l'S is based on the use of tv.0 G PS rcc civ crs ue simulruucously record pos itiona l information. A tcrrcstria, (i I'S ba se station is located ;1\ a n accurat ely surveyed lea. tiou with well -docum ente d .r, y. and a-cocrdiuatcs. Thee rrcstr iu! ba se s t.uion record s its G I'S position for the duration of t he UDAR da ta co llectio n mis sion . The second GPS receiv er is located . HI the airc raft and record s the LlDAR antenna position at all times du ring data col lection.
A tier the U DAR d ata an: co llected. the data from both GPi units (one on the grou nd an d one in the ai rcra ft) arc post-processed alo ng with the !.: nm\ n loca tion o f the base 5taliOG. ante nna. T his process de termines the exact location ofthc airc raft 's ante nna for the ent ire fligh t. The accuracy oftbt aircraft position is typica lly < 5- 10 cm, and is OU[PUI in units of latit ude, longitude. and ellips" idal height in a WGS S.l coordinate system.
339
RPrinc iples
9
R Antenna A ttitud e (Orientation)
lII."(:c:>~af)'
be :
1.1 1M, I~ Returns
-
to have accu rate L1 DAR ante nna orientation
(?-·ii ,~
auu n (roll . pitc h. a nd hc"Jing ) ar all times duri ng data ion. This is mea sured h)' an inertia l measuremen t un it I). The I\'I V uses ro ll. pitch, and yaw g )fOSCOp.:S and . accele romet ers 10 measu re the orientation o f the :\ R antenna at tho: exact moment ev ery pulse is transmitJlId received. Aftcr the L1DAR da ta are collected. data the I\1 U is pos t-processed along wuh the GPS-dcri\ed na position data to (llIlrUI a file ind icating the trajectory
-""F
' .'1
pulse A
pu lse B
ic aircraft and the laser antenna at all limes during the
It; 11
to
am-
AR mission . The outpul ti le docume nts the pos ition of nrcraft {latitude. 1\1f1gitude. and e llipsoidal hei ght) and orio:nfalion (rol l. pu ch . and heading]. indexed by G PS
R Post·Process;ng of Multip le Returns
IA R
Jon ':\ R
-tm) ~i1i·
-
.ser l ed chhut ·ia l
far we have col lec ted GI'S data. I\tl U data. and se nt received laser pulse s. 1I0w arc these data turne d into I elevation values at specific .r ,I" a nd locations on the :c of the ta n h'! Th is is accomplished thro ugh lI DA R -proccssmg wh ich tak es place after the aircraft has Post·pru~·cssing software is used to associ ate I ) AR antenna X ,I'.:" pos ition. 2) antenn a roll. pitch. and "orientatio n, a nd 3) LID AR range (d istance ) in form at io n a set o f latitude . lo ng itud e. and altitude (x,v.=) coordtfor each L1 DAR retu rn . The outpu t is typica lly in a pact binary format o f W CiS S4 coordinates. with options convening the out pu t to ASCII fonn at s and/or UTM rdinatcs. Nul,', let us co nside r the chaructcris ucs of the iDAR dat a.
=
e r-
""
llD.\ R Returns
P5
," '5 0-
m ic
rc ts i4
mentioned, a pulse o f laser energy c:;; iting the trans m itter directed toward the terrain at a ce rtain ang le by the rutat ~ mirror. Depend ing upo n the altitud e of the UD AR rumem AGL and the a ng le :11 which the pul se is sent, ·n pulse' illuminates a ncar-circula r area on thc grou nd led the inxtantunrons laserJontprin t. e.g.• 30 em in diarn[Fig ure 10·1 a ). Th is single pulse ca n gener ate one return multip le returns. Figure 10-2 depicts ho w multiple returns ght be produced from a single pu lse . A ll of the energy -itni n laser pulse A interact s w ith the gro und . One wou ld ssumc tha t th is wou ld ge ne rate' on ly a single return. How:'off. if there are any materials wha tsoever with loca l re lief -shin the instantaneo us laser footprin t te. g.. gr ass, small
msrauranccu, laser
footprint Figure 10-2
I low muhiplc relums are generated from a single ofla ser light.
pul~e
roc ks. t>,>,'igsJ, then there will he mult iple returns. The hI will come from these mate rials that have local relief (even on the o rde r 01'3 to 5 em) and the 2n d and perhap s lus t retllrll wi ll co me fW111 the bare- Earth. A ltho ugh not idenrical, the ran ge [dis tanc e ] associated with the first and last return s will he very similar. n.'/1I1"/1
Laser pu lse !J encounters two part s o f a tree ut different clc \"at icms and then the hare Earth. In the ex amp le. pan o f pu lse 8 encounters a branc h at 3 m A(i L causing so me ofthe mcident laser p ulse to be bac kscauc rcd toward the UDA R receiv er. T his is recorded :Is till' tsr ft' lllrll ( Figure 10--2 ). The rem ainde r o f the pulse continues until at2 m AG L it e nco unten; another branch that scatters l'nergy hack toward the UD AR rece iver. T his is recorded as the l nd tt'rtlm. In this ex ample. appro ximate ly one -hal f o f the pu lse finall y rea ches the ground. and some o f it is backscancrcd tow ard the
34 0
L1 DAR rece iver. Th is is the I..w ref il m. If we wanted infe rrnation about the heig ht o f t he tree and its struct ural characteristics then we oul d 1'10: interes ted in the 151 and 2nd returns assoc iated nh pulse B. lf we arc only interested in creati ng a ba re-Earth d jgunltcrrain mode l then we woul d be especi ally interested in the las l return assoc iated w ith pulses .-I and B. Th us. each laser pulse tra nsmuted from the airc raft ca n y ield mu ltipk return s. Th is is re ferred 10 as multiple-return HOAR data . Pos t-p roce ssing the original da ta res ults in sev-
era l LJDAR tiles co mmonly referred to as: 1st return; possible intermed iate returns; last retu rn: and
inte ns ity.
TIle masspoims assoc iated with each return file (e.g.. lsi return) arc d istribu ted throu ghout the land scape ar various densities depending upon the scan angle. the number of pulses per second transmiucd (e.g., 50.000 pps). aircraft speed. an d the materials that the lase r pu lses encountered. Areas on the ground that do not yield any Ll DAR-relUm data arc referred to as data vo ids. Data co llect ion ve ndo rs del iver U DAR data acco rding to user specifl cuuons. For example, the Savan nah Rive r Sue UD AR retu rn dOl la we re delivered in ASC II form at as :
CII.\I'n:H;
10
L1DAR Remote Sensing
Extraction of Firs/' Intermediate, and/or Last Retum Digital Surfac e Models (DSMs)
Massmnms assoc iated .....ith the las l returns from the UDAl m ission Ilown ov er the Savanna h Rive r Sue on October ~004 arc shown in Figure 1O-3a. Note the distribcnce density o f these po ints. Each masspoint has a uniqut' 1\'1(,:
time o f day. .r-cunrdinntc, j-coo rdin atc. a-coordin ate. and intens ity. The si mple ASC lI format makes it stra ightfun.... urd to input the UDA R data into a G IS for ex aminat ion and ana lysis. The UJ)..\ R ret urns were processed by the vendor into scparate files u f:
1st returns; last returns ; and bare-Ea rth re turns .
Bare- Earth return s .... ere derived from tile li rst and last returns using a pos t-processing proc ed ure (to be: disc ussed ),
interp ret by appl ying J shaded-relief algor ithm that high· Ii ght ~ the terrain as if it were illuminated by the Sun froma specrflc direction ( c.g .. from the northw est ). An examples presented in Figure IO·.k . The or ig ina l masspoinrs hare bee n overlai d o n the shaded-relief display fo r illustratia purposes. [)ra p ing masspuims onto onhophotog raphy is al' l\ very usc ful t Figu re 10-3..1). Most LI[)A R p rojects generate som uc h data that it is necesary to subd ivide the d.ua sct intu t iles. w e ha ve been u amining a sma ll portion o f one t ile. T he first- and lasr-renss d igita l surface mod e ls fo r a n entire tile arc sho wn ill Figure 10-4ab. Th is graphic dep icts both the first- and fust-re en dat a as Inverse d istance weighted l ID \\' ) d igital su~ mod els I DS M). First- and last-retu rn ID\\" DS~h are thcI portraye d in shaded- relie f fo rmat. T he multiple ret urn DS\1 Illes arc of sign ifican t value fa mall>' upp hcanons such as the: cxuucuon of wgcta:Ka
341
RPrinciples
9
"
Varillll~ () i'ip la~ ' s
-
of Las t-Rerum UI>.-\H. l\Iasspoi nts
DAR 10,
T
t
and
e
f~1
xum
ping -orn-
Its 10
does reo 11 ecb-
'Oint
rrolion
US
cus-
\ur-
lion
,,<.
;:11,'·
""
Ilgs
ave
"0 ate
lIC-
" «I ~h.
:gJre 10-3
-r a is
'"
" '"
om
a) r-. l a '~f'I.,; nls can he viewed individually This proced ure is useful for identifying any data voids . On e can also set' that the data in th is 1,1SI return J"tas<;l carne from mu ltiple Ilightlinc s. Digital surface mu
kight and biomass and building heig ht informarion (e.g.. ef-ky ct II I.• 2005 ; 1\ ta. 2( 05 ). 111)1.\ ever hal i f .... I' desire a are-Earth d igitalte rrain model I DTM ) itho ut thc presence trees and or ma n- made structures? How is it created'!
re m
Extraction of Bare-Earth Digital Terrain Models (DTMs)
'"
m
the purpose o f a LIDA R overfl igtu is to collect J OlIOl to ereIe
•o
a digital terra in mod el. the presen ce of vegetatio n (and
Ilbcr surface obstmcnons j ca n be a nuisance . In areas 1;0 \ mJ by dense \ egcunion. the major ity o f the LlDAR returns
will he from the ca nopy. with only a few pul ses reach ing the ground . Hendrix l ll)l)9 ) found thai up III 9 ) '};' o f Ll DAR pu lse s neve r reached the ground in mixed bonomlund hardwo ods ncar Aike n. Sc. Separating gro und returns from vegetatio n ca nop y return s call be problematic. Nev crth etc ss. it ca n be don e. A ba re- Earth d igual terrain model I DT~I ) may be created by systemati ca lly rem ov ing masspoint s in the first , mtcrmcdiate. and/or last return UDA l{ data that co me fro m trees. shrubs. and ('\ en g rass that extend abo ve the bare grou nd. Th is procedure is typ ica lly performed in ' w 0 steps: I ) semi-
C11 \ I'TFR
342
10
L1DAR Remote sensing
1I
I.ID,\ I{ Dat a of th e Sa va n na h River Sill' O brat ncd o n Odn hl' r Ill, 21104
S<
"
" a d I'
t
J
Fig ure 104
\
:H Inverse distance \\ clghung (1I)W)
343
A Princ iples
marie m a~sro inl filte ring. and b lru auualmasspoint edit_(Raber CI ul., :!002; Leonard, 200 5),
tautuma uc \ 'eJ,:\'Ia liUII a lld/or \I a n-m ad e Structure point Fillt'rillJ,: ~
landscapes contain dense vegetation. It is imperati ve a techn ique that remov Cl> ()() - <)8% of the abovevegetation masspoints . This is don e us ing a filtering thm that systematically P;hSI.~ through the lI D:\ R exam ining each masspoiru and the elevation characics associated w ith its II nearest-neighbors. The filter identifies those points thai arc a l bare ground. b) scrub. cttrccs. andor d) man-made structures. For example, ct a l. (2002 ) deve loped an adapt ive vegeta tio n val filter thai took into account the lIDAR- predic ted vcr type. Suholc and Vos.sclman (2004) rev iew eight erenr filters applied 10 twelve UDAR datasets. Progres s been made in the development of se mia unnnatic \ cgetaand/or man-made'ohjl't: l remo val algorit hms . New algo1111m will ho pdu lly he more efficient and accurate. !la\C
Ilanoal \ 'li~cl a l i llll a nd /or \lall-mad l' ~r u (' l u r(' \ la ss~nl t~d it i n l:.
lefonunatcly, scmlautoruu uc Ilhe ring rarely ide ntifies all u-"spoints acsoc tat ed w ith shrubs. trees, aud'or man- made ~s (Leonard. 2005 ). n is usua lly nec essary for a wellnincd analyst to visua lly e xam ine the re su lts of app lying Qcst'miau toma tic filte r and then selectivel y ide ntify and Sl:'t side an)' abov e-grou nd masspnints that wer e not detected emimuomancally. Th is approach may involve vie wing the »im clouds in 3-d ime nsio ns o r o verlaying the ma sspnims 00 rectified ae rial photog rap hy, The manually edi ted mas sloint' can 1I1I.'n be used to create' a hare-Earth digital terrain wodrl (DT M J. Figures 10-40: an d l u-a fdc pic t a bare-Earth DD,1in which allofrhc vcgctarion und huilJ ings ha ve bee n eeovcd. Figu re 10-5" presents an e n l ;\r~ l:d view o f a sllla ll pan of thl"lire;! show n in fi gu T<.' ] O-·h; a nd I 0--4 f v, itll the lilkred bare- b rth m a s~ po i n ts uverla id on thc last rct urn ID\V OS\t NOle the {lata vo ids on the bui l,ling rtHl rto ps I I here Ihe rlmr oints v.'Crl"del eted hy aUlomated and/ llr man ua l Ii her{I~ The hare-Earth masspo illts can then be pn K:esscd to )ield a DTM that contains no huild ings
be' used h. mod e l the now o f wa ter on the ground. then we wou ld not want 10 usc the n TM show n in Fi gure IO-4 f(and Figure 1O..5d) bec ause the buil dings have bee-n removed. Instead . we wo uld want tu re move all above-grou nd veget atio n and the n create the D'Tj..l . The DT ~I wo uld con ta in bare-Ea rth and build ing elevation information. A hyd rologic mudd using th is DT \-t wouhl I1 m\ water co rrectly around bu ildings. not thro ugh them.
xtost U D.-\ R ~)".tC'ms provrdc an mll.'flsity ti le in add ition 10 the multiple reru m da ta For example.the intensity data produccd by the Lc ica A LS4 l1 50 L1 1)A R sy..tern rep resents the peak voltage o r the return ~ignal as recorded b) the system co ntroller (LI.·•.mard, ::!OO5). The recorded imcnsity is in mos t cases not the integration of the' returned echo from all the pulse returns, but just ih maximum I Ba ltsa\ ia... 1 ~ ) . Th e-re a rc several factors which influence the inten s ity valu e. Fn-a. it is rmponaru III remember tha t laser light is mono-
chromatic and has a n esucmcly smal l bandwid th (c .g .. ~ - 5 nnu usua lly centered on a ncar-infrared wave lengt h (e .g.. I n4t. nm). Conversely, mu ltispectra l remote sensing bandwidths an... o ften 50 100 11m w ide al tho ugh hypcrspcctral senso rs might have bandwid ths as sma ll a s 10 nm ( Ba ltsavias. 144<) ,. Other signilica nt factors include the- ra nge to the target, an gle of incidence a nd atmosph eric dis persion. In add ition. the system controller also reco rds the state of the AGe (automa tic gai n co ntrol). Till: AGe ci rcui t (IdJush the retu rn signal gain in response 10 cha nges in ta~e't reneeranee. T he gain and irucnxity vafucs may vary ove r a sce ne ami from day 10 da y. This vnriahility in ga in conr rol can cause' problems v.hell inlt'lll rct ing intens ify da ta ( Leon ard,
2no:,). I'heor elil'a lly, one would th ink tha t because the la ser uses nl'a r- infr;tn: d lighl that lhe intensi ty val lie lit eac h (lf the masspoi nt l(leations would 111 et l e'et ht' si milllr to the- relle-etane c fuun a w hen cu nduet ing Ilptiea l relllole se nsi ng in the n('arinfrar cd port ion o l" t he spc(·l rum. Unlo l1unatcly. this is not the- case. !'or e xam p le. Figu re j(J·(,a prese nls a D S ~ 1 pro duced usin g [DW a pplied to lasHet uru U DA R data . Figure 1O-6 h i" an irncnsity DS\ 1 prod llCed using lO W. Th e iotensit~ image- contains 11 we alth 111" dcl ailltlld in many re-,;P'Xh 1110 ks like 1I panchro matic aerial phutograph o f the' study area. 11 0w<·\ er. Ihere ;Ire snm.: intt'resting annmlllies when we ellmpare the i n h:n s i t~ image tn v. hat WI.' wou ld ex pl.'t:t to lind in a t~ piea l b laek-and·wh ite nl'a r-infrared ima ge.
lis importantlo no te thal the linal har e-Earth DT fll mayor
f
m;.. nOI include- man-made struClures such as bu ildlllgs. For fumple. if we' arc cu neertled w ith creating a DT\-1lhat will
d
First. consitlcr the lal)!e forested area show n atlJ in Figure 10-6b . Thi s is a malOre 1~) r~'St that has suh-Iant ial loca l re lie f
nI Af'TEIt
344
10
lI DAR Remot e Sensing
---
Distribution of ;\I asspoint s After Digita l and vl anual Ed iti ng
'.
~ ,.
--.. );
:./'''-
.' " ' , ;-
c. Edit...! I,u"'l",inh uvcrlafd on 1 x 1 III ll rlh opholo ,
Rgure 10-5
3) Edited rnlls~r "illl ~ ovcrkud nn the onginnllast-rctum Inw digital sur ra(~' mudd. h) Sbudcd-rclicf version "f (a). c) Edi[~ tl\llss po irlls overlaid I'll an on hophotc. d j Har e-Earth digitalterrain mudd in a trian g ular irreg ular netw or k (T l f'; ) data slruC1Ur:
as ev ide nced by the bngju ret urn i ll till' adjac ent last retu rn data set (Figu re 10-(,;1 ). We would normally e xpect this area ICl appear bright in a black-and- white nca r-infrared image. Conve rse ly, it ap pea rs qui tc dar k in the inte ns ity image. Simil arly. consul...r several ind i\ idua l decid uous trees at location h in Figure 10-6 11 and show n in Figu re 10-7. These IfC<:S a lso ex hib u less mrcn suy than ex pec ted . The natural grass surround ing these tree s has a higher intensity range than the trees I Fig ure H)-7..: l_ Fina lly. convidcr the hrighl areas at location c in the mrencrty image I Figu re IO·(,bl . The nort hern half o f three of the rest-
pad mound s were cleared lind sodded with centipede grJli do not have as much biomass as rhe trees III a Of b. Nevertheless. they ex hibit II w ry hrigh l return in the mIl.'[)suy imag e ( Figure lO-6hl.
T hC'~'
In these ex amp les , it appears that when the Ll lJAR pulse encounter trees. vo lume sc.utcring wi thi n th..: tree canOl'!' red uces the amount o f ene rgy bnckscau crcd toward dt L1D..\ !t recei ver. Th is causes the lrees to appear dark in dt imcnsuy image ry, Conversely. L.IIH .R pulses that hit l!'t natura l gra ss at locauon h and new ly sodded cen npcde grail at locauon (' are not absorbed or scattered away, Ratho:r. l
LIOA F
34 5
IJA R Princ iples
LlIHR Last Return and lutcnsfty. nata
a, UOAR lIl'''~~ distance wtl ghled last-return elevation.
Figure 10 -6
on
b. L1D.\R intensity,
Inverse distance \\ clghtmg applktl III L1 0AR last-return data. til IDW al'ph~.,j \0 L1IHR illlcnslt) data . Three ..rcas are highlighted for d iscus sion .
;1 )
won g ret urn exit s these mixed grass a nd bare-Earth surfaces C3 using them to appear bright.
Many of the buildings are " righ t in th... intensity image suggesting (hM most of the inc ide nt laser pulse is buckscauc red resulting in ~tf(lllg voltage read ings . The intens ity or thc return is a function of the rooft op material. leonard (2005) states thai ra nge and angle o f incidcnc.., al so hal e an effect on intensity readi ngs ov c·r the cou rse o fa si ngle l1ightli nc . As the UD AR scanni ng mi rror moves fr om nadir III t he lodge or the fiel d of view mo re c nt:~y is rerlccrcd away from the receiver optics . A s a resu lt. ime nsity
readi ngs arc higher closer III n,ld ir than at the edge. Range to larget is anot he r signif ica nt factor in intens ity normaliza tio n, Sho rter ra nges ha ve high er intensity readings due ttl less atmospheric signa l lo st. Cu rren tly, there are no rigorou s guideli nes about ho w ( 0 inte rpret LIDA R intens ity images . Neve rtheless. it is clear th;II they contain a wealth o f inforrnano n. For exam p le. co nsider Color Plate 10..1 whic h de picts the intensity data dra ped o ver the last return elevation data for the dec iduo us trces shown at loc at ion h in Figure 10-6 b. When these data arc co lor-ended i Co lor Plate 10-1 ti} and e valua ted ubliq uc ly (Colnr Plate [Il-Le], it is cle ar t hat the intensity o f the return s
346
ClIAI'I HI
UDAl{ L l..c(-t{eturn Eleva tio n C Ollipa red n it h
a. In\l' J"',C distance "cighlcd last-return e1c\at ion.
10 1.11),\1{
L1DAR Remote Sensin g
Intt'Il'iily
b. Shaded-rehef versjon of(a l.
Figu re 10-7
aj Inverse drstence ~cig h llnl:! applied to tasr.rerum data. h) Shaded-reliefver~ion of ta). c ) UDAl( inlcnsily data.
• c. LlDAI{ intensi ty.
in The trees is a func tion Ilfhll\\ far the pu lses penet rated into the tree canopy, Such iufornuuion could 1\0: related to tree b iophysical cha ract eristic s (c.g .. LAI. perc ent canopy closure, biomass. basal area l.
Contours
or
Sometimes it i., valuable [0 extract contours {lines equa l CIC \3I il' n ) from DS\1s or DT\1s to hig hlight subtle drtfcrc nces in the te rrain and 10 ide ntify lk rrcss inns. Fo r exa mple. co nsider tho: test pad mounds located at c- in Figu re 10-6h. These rcstp..J s were engineered "'lCt.: ifica lly to tcst the effcc nvcncsv of venous clay-cap materials used 10 protect subsurface hazar dous materials . var ious Iy ~ s of impe rmea hlc po lyure thane barriers .......·rc• plac...-d on the testpads. covered with clay. and planted wit h centipede grass . The surface.. ~ ere thc-n leli to the ravages of nature . L1DA R first-return data of'thc tesrpad .. processed using lOW
a re presen ted in Figu re 10-1'01. A shaded -reliefv ersio n onhe I[)W OS I,,,j is sho wn in Fig ure ]{)·Xb . Note that one-halfot the trees were re mo ved in the northern hnlf'o fthrcc ofih e test pads and not on th..., custcm -mo« control testpad The clear ed arc us on the three ll:slpads were sodde d with nell cc ntip....dc grass at the time ufd.ua co llect io n.
T he las t-return U [)AR da ta w ere filtered using automated und manua l proced ures to de rive thc har e- Eart h DT ~l shown in Fig ure IO-l,l,1. A s ...xpccted. almost all of the trees present in the first-return lima (fig ure W- X,,) hav e been removed De~ r itc its usefulness. it is not possiblc 10 visually extract quanti tative intorma non about the nat ure of the Icstpads from the bar e- Eanh DT\1 shown in Figu re 1O-9a . [I is onl~ when wc der ive con tours ur other sy nthetic ]·D rep resentat ions from the bare-Earth DTI\I thai we can appreciate the thrce-duncusional nature of the restpu ds aDd
~A R
347
Pr incipl es
UUAR nata or t heTesl pa ds on th e Sanlll na h Rin- r Sill'
3. t n\c~ distance weighted firsl- relUm elevati on.
'.
-ie
ur
-se rc w
-d n
•
u l.
"s
b. Shaded-rctief' version of (a).
y )
"j
Figure 10-a 31 Inverse di~ilnco: wcighting applied 10 first- return dna, NulO: tho: 1'1\.""<.'1k:0: " f l....,... ~ on rhc 1.-stIMt!S and in the fores t to the east. bl Shaded -relief version ,If(a l
•
10
348
UDAR Remot e Sensing
AccU I
Contours Ext rac ted Ircm thc Bare-Earth Digital Terrain :\Iodd of ti ll' Testpads T, bI
me
IcS
-
• ., L
-------
a. Inverse distance weighted bare-Earth elc....a uon,
--......,_..-...,.,.,,.....,~-~
h. v
;, 2 t I
b. Contours (0.25 m interval) derived from (a ) OVC'Tl3ld on a shaded-relief model of (a).
Figure 10- 9
•
al ln\ erse distance "cighh:d b are-Earth elevation. ;";010: rharihe uee, hale been ~11I" \o:
349
lceu racy 01 L1DAR Me a surements
Vcrucal accuracy of L1 IlAR-i.k ri\·ed elevation data collected for the Savannah River Site on Oc t...bcr 10, 2004. using the G""'f'<,r/tll I'm/rion .k l'lI'C1C1·SI,moardv Pan 3: ,\ ·m /on
'able 10-2.
Vendo r :l.1IlOOm.lnc.
LIDAR sensor Uptech AI.TM
2050
Dat e 10-1()..1)4
Ho rizontal datum un t NAD 83 l one 17
Unit s
Verti cal d atum
Number of c heck· points
m
;';AVOIl8
vs
NSSDA RMSE
NSSOA Vertical ac curacy at 95% confide nce Interval (1.96 x RMSEI
6.6 em
12.9 cm
• subtle depressions. espot'ciall~ on the most eastern tIlpa
Sensing (AS PRS I ASPRS ..feeurun · Sial/Janis fw WIXt.'&/111' .\f<.qIJ published in 1990.
-......
Th e Gt'o.\f/i.J/i /J / An·,lr
.~
Accurac y of UDAR Measuremenrs
LlD:\R is a rclauvely new technology . As such. there is Vllth)' skc pt icis m abou t its ability to provide x,v, and r -e te\'IlIon mformat um as accu ratel y as rraduional ill situ su rvey mg and pho togram mctry t e.g.. Bahsavia s, 1999; ~1cGlone. !(04). Fortun ately, there arc acc uracy assessment standa rds dial can hi: used to provide an unbia sed assessme nt of the accuracy o f LIDAR---de rived prod ucts.
IISSDA Horizontal and
venice; Ac cu racy Assessme nt
Iodetcrminc the at'CU HKY o ta L1 IlAI{ ---dl' rived dig ital surfAce model (DS M I or bare-Earth J igital terrain model IDTM), it is customary to ide nti fy in si lll x,v.;: checkpoin ts lhmughnu tthe study urea us ing a higher accuracy technique. such as to tal station sun ... ytng o r diffe rential GP S. E~Kh ill l i/ll checkpo int is thc n loca ted in the 1.IDAR -dc rived DS r..t or DTM. The nearest L1 DA R-
•
R sts E
~"
L a'
=
(1 0-6 )
t.=.l.-
and ,\ is rhe difference between an in suu check po int measure me nt and a remote scns mg-dcnv ed measu rem ent at the same locati on. The standard rec ommends tha t a m inimu m o f ::!O ch eck po ints toe used . i.e.. 11 > 20. The check poi nts sho uld he o f substant ially h igh er acc uracy than the rem ote sensi ng. de rived product und er invcstig ation.
u.e., circ ula r sta ndard error) assessment at the 95% confi denc e level is co mputed us ing
t tonz ontot (/("('/lro(1'
( 10· 7)
Vertlca! (1('C/I/'(/ ( \ ' assessm ent at the 95% confi de nce level is compu ted usi ng I ." /I<
1.9hx RM$E
,
( IO·S)
Equauons 10-7 and 10-8 assu me the e rro r distribu tion for .r,
y, and z arc norm al ly dis mbuted. FEMA built upon these criteria and pro vides detailed accuracy assess rncru proced ures fo r its flood-hazard ma pp ing partners ( FE MA. 2004). The vert ical accu racy of the L1DA R-derived elevations o n the Savanna h River Site " as evalua ted using 95 c heckpoints (Table \0..21. T he spatia l dismbunon o f the checkpoints on the Mixed Waste Mana ge ment A rea and the tes tpa ds is show n in Figure 1()"lOa.b. The vertica l acc uracy of the
• OIAI'I EK
350
,\ ~ s c ss lll c n i
Chec kpoin t Locations for UDAR Accuracy
,
a. Checkpoints on tho:
~l ix.:J
10
LlDAR Remote sensing
011 the Sa vun uah River Site
a. Checkpoi nts on the to
wa ste Management Facility.
t
pads.
c. Relationship Between In S itu Ground Sun ('~: Eleva tio n a nd IJUAR·dcrin·d Etevanen for 95 C hec kpoi nts fin th e Sa vannah River Site " .00
-
9':UI I
1/
y = I.OO27.f · 0.253
eo
" E
R2= O.'l'N2 9!.OO
.•1f•
V
/"
~,,,
~.,
,
.,w
c.~
,J!:
"" If'''
". rr~
». ft
f"
HIUIO
~,
LJ·~ 1I7.UO
X7.00
XlU)(}
10:\1.00
'X1.OO
<11.011
<,l2.01l
'HollO
ll-l ,l)()
LIDA R-J eri \'oo Elevation (meters ) Fig ure 10-10 a ) Lo canon o r c hcd ,p'.linb on 11t.:- "'!Xed Wa~IC \1 anagc mcnI Faci lity. r hls area IS clay-cap ped and covered with Ccntipetk ~rass, h) Loc utions or c h~"Ckpoi nts on the teapad s. c) Stat ist ical rela tionship bet wee n
;11 Table 10-2.
l
I
:DAR-d eri ved Veget ation In forma t io n
UoAR da ta according to the :"SSDA specificanens was Qem. As e xpected . the U DA R- dc rived ele vation values ere highly correlated with the GP S insuu eleva tion meaems (Figure 1O-1Oc). iJJer(2004) stilted t hat LIDAR- derived vertica l accu racies r: usually in the 5 to 30 em range. Hut does this level of It\lracy hold up when the terrain is steep? Does it ho ld up IIr all land-cover types (e.g .• bare soil , grassland . shrubJ mb. fores t, desert, water, shallow wa ter, icc. snow , urban EJaslructurerl Unlike photogrammctric surveys, can UOAR be used success fully dur ing leaf-on co nd itio ns? II is ecfulro consider some of thes e questions .
)r;"uence of Land Cover, Slop e, and Leaf-on/off Condition on UDAR-derived Elevation Accuracy
~lany
scientists are invesl igating the e ffect s of la nd cover;
1l1pe. and lea f-on/o ff cond ition on L1DAR-d('ri\'('d elevaIloo accuracy.
;..~
......
<...
U DAR-derived VegetatiOn Information
'
The ability of LlDAR technology to obtain returns fro m hot h vegetation and the ground surface has useful appl icatio ns in measuring vegetation attribu tes. Weltz et al. ( 1994 1 used a profil ing L1 DAR system to map vegetation height and canopy cover at the Wa lnut Gulch experimental watershed in Arizona. This study demo nstrated the ahi li t~ of L1DAR to distingui sh between different \ egctauon comm unities and ground-cover type s. 1'\il s~on ( 19<)6) exam ined the usefulness of 1. IDAR fo r csrimaung timber volume as a pan ofS.... eden's Nationa l f o rest Inve ntory.
Zimble et al. (2003) were ab le III ex tract vertical forest s tructure information from small footprint L1DAR data. They obtained tree hcigfu information by subtracting the bareEarth DT M from the Ist-rcturn DSM. i.e.• tree height DS~I • ht return DSM - bare Earth DT~1.
Hod gson et al. (200 5) invest igated thc effects
ri land cover and surface slope using leaf-off L1DARiI:ri\'ed clevanon data for a watershed in the piedmont of ~orth
351
Carol ina. Survey-grade elevation checkpo ints ( 1,225)
ferseven differen t land cove r classes were obtained. Lil lA R elevatton error fur points associ a ted with the seven landrover classes ranged from 14.5 em ill low grass to .~ 6 . 1 em or dense shrub/scrub. Eleva tions found in pine and deciduforest e xhibucd mean errors of 27.6 em and 27.3 em, respectivel y. On average, the Ll DAR-derived elevatio n . 'I"- pred ieted true elevation regard less o f land-cover rype. The under-pred iction was signific ant. and ranged up to 23.6 ClII under dense pine land cove r. QIIS
!II another study, less-dense pine exhibited elevation errors pavCI11':lU and low gras s ( Hodgson and Bresn ahan. 10(4). The finding that scrub-shrub and deciduous landcover exhibited the highest error appe ars 10 be consistent regardless oficaf-o n/leaf-o lTcondition (e.g., Hodgson et af.• 2OO3ah; Hodgson and Bresnahan. 20041. Basically, it appears that the more dense scrub/shrub and deciduous landrever keep s laser pulses from reach ing the ground, ca using tIJt interpo lated elevation surface to he derived from the few points that do reach the groun d. The res uhing DSM or DTM may contain error. I> low as
Carbo n sto rage in moderate to high biomass forest:> is d ifficu lt to estim ate with conventional opt ical or radar sen so rs. Lcfsky et al. (2H05) compared the re lationships between LlDA R-lIIeilsured canopy structure and co incident field measurements of forest stand structure at five locations in the Pacific Nort hwest. T hey obtained Coefficient of Determination values (R ~ l for LAI and ab oveground biomass of Kl % and 9.:! ~"'. respectively. "orris et a l. (2005 ) used L1DAR data 10 chara cterize the etcvaticn habitat of two salt marsh spec ies in North Inlet, Sc. Approximately IU)"/. of the Sf'/lrtmll alterniflora exi sted within the narrow elevation range from 0.22 - 0..181 m ASL whi le 80% of the } III/<'US roamerionns existed within the elevation range 01' 0.296 - n .9S 1 m ASL.
LlDAA-derived Urban Information
• LJO,\ R--
the
locarion and
elevation of milily
transmissionJines (Maune. 200 J ): Hodgson ct al. (201l5) foun d that over the small slope range In their study area (0" to I tn . there was no t a struisucu lly ligni ficam increase in L1 DAR -d crivcd elevation error as rhc dopes increased . However. Ihey did find that slope errors from L1DAR-dcrived produ cts increased with increasi ng saface slope, typically undc r-prcdic un g true slope by 2 c.
obtai ning accu rate building elevation (c.g ., Mn, 20(5 ); meavuring the elevation c haracterisuc s of transportation infrastructure such as highw ays. bridges and overpasses (~CRST. 2( 04):
F
10
352
L1DAR Rem ote Sensing
L1IH I~-d l'rivt'd Ele vation uf :Xl'W Yurk C ity. r\Y. afte r Septem ber II , 21111 1
Fig ure 10 -11
Perspective \ icw of ]\"cw Vorl Cit}'. l\'Y. aficr September I I. ::00 1. 1111: pik uf rubble i~ associated with lhc Twin To... ~ !h.! \W'rld Trade Center IIJ IMR data courtesy of Eanhltata lntcmanonal; Jen sen and Ilod gwn. :'!ClO·I; 10llof>j.
identifying optimum routes that require the least cu t and till (e.g.. Cow en ct al.•1UOOJ; and urba n cnviroruncru visualization [Q ucija ct 31..1(105). Be fore and after L1 DA I{ -dcrivcd elevation data a TC t'SPCcially useful for calculating the J llW UnI of ma ter ia l cxcuvated (scoured }or deposited m a regio n (e.g .• Shresth a et al.. 200 51. hIT e xample, LIIJ AJ{- ..lcrivcd elevation in fo rmat ion were used to compute the volume ofrubble assoc iated wi th
the Twin To wers of the World TmM Center in New York City (Figure 10- 11) (Jen sen and Hodgson. :!OO(l).
The Future of LlDAR Remote Sensing
future (e.g.. LA I. biomass ). II wi ll also be use-d e xtensi~r!! to oh l;lin three-dimensional urban infrastructure informaia (e.g..• huilding foot pnm s and hcigh t). U l)AR in"trulOOl1l will eventually he flow n on unmanned aerial vehicles.
z:~
References
""Baltsavias. L r.. I 'N ' I:l. " A C"ll1p.nisu!1 between PhorogramrreIT) an d Laser Scanning:' IS!'!?.'> in/mwl "I PlmloKrammeJrI' & 1<"1'1111 ,' S('II ,·/II!:.
5-1:~ J --<,I-I,
Haltsnvias. E. I'.. 1'1'1'/1>. "A l rl>orn~ Laser Scann ing : Hasic Rela. l io ns and Formulas." ISI'HS Journal (!lI>lwl(}!
Ll DAI{ remote s~' nsing tt'chl1ology has rcvnluno nizcd the co llection of digital surface models and d igualtcr rain modcis. LID:\ R sensors obtain hundreds ofthousands of mass po ints per second Ih.1I already possess accurate x~\". and acoordinates without the necess ity 1)1' uerutna ngularion. The accuracy of the onboard GPS and l'AUs continue to improve. The number (If pulses per seco nd transmitted continues ttl increase. The abrluy to measure the pulse range co ntinues to improve. U DA R sensors arc becoming mo re affordable . All of these factors result in ever improving Ll DAR-deri\'ed dig ital etevauon information. U DAR will provide con ..idcrnblc vegetation canopy info rma t ion in the'
Boland. J, and If> co-authors, 2UU-l. "Chapter 8: Eameras IIiId Scn~ing
System-s." in MeGI" llc. J, c., [ Ed.)• .H" m", j 0/ Pil
/ORramwl'ln', Sth Ed., Bet hesda : ASI ' & RS. o2'i----il3o. B,,~~1c r,
J. 1>., Jensen. J.
I~ . , 'vtcM a ~ll·r.
R. II. and C'.lhzQS. ~002
Hom,.,,1 .. i ( ; ('0 ,/,<111,,1Sr i l'm' ,- 'Ill" T ' i!rlm% gy, London: fal'
lor &
l:r Jncl~.
(,! J p.
Cowen . Il C . Jensen. J. R.• Hen dr ix. C. L Hod gson, M,E.1llId :).IC Schill. !(l(MI. " ,\ (j l~ -Assistct.l Ra il Construction Ecocc-
F
353
erences
eemc ,\ I(",ld that I n .' or por ;l lc ~ llO . \ R Da la : ' PIIOI" g,r"m ...'Im ' EII.r;i"...·ring ,~ H" mol" S,·/l_i,,}.: . ""Ill j : I 32.'-1 U K.
Jensen. J. It . 200 5. fmmJIlClm'Y /) ig iw l Image J''''('f!.umg ,· A He"'''/<' Se,,,,,,).! l 'a.'I,,,.'li ...,. 3r <.l E<.I.• Upper 5 a<.l<.l le Ri ver :
Prcnuce-Hall. 525 p. . ~OOO. P"'f"m"lII' <: SI'...·iji..
)UI'\e~ ing .- in
"'i",,"
~i",,-, J'" fI"!,,r" .\ I""" i,,).! 1''''111<'' " , Wa.-. hinglo n; Fe.kral Erncrgcnc y ~ 1 .ma gelll':lll Agen cy. 59 p,. .... ww.tc _ 1IlI , ~0' .
\IA. ~(l(J..I . " Appcndiv :" : Oa t,l Capture Standa rds," in .1f,,1' WoJern i:"I,,,n: Gu,,/"'ill<'~ m ,,/S{'t>('ifir"';
\"li""
of
lood. \1 .. and n . G utcliu s. 1'1'17. "Commercial lmplications of Topographic Terrain Ma pp inl! I '!;-Inl: Sca nr un g Airborne Laser
Jensen. J. R. and ~ 1 , E. Il o<.l l:~on . ~U()f1. " Remote Scns kngof Natura l and Mau-madc Il a l ard s an d Disas ters," in .\ I(1I",,,f uj Rt'mot," S"ll~i"g: S,·//h·m,·,,". M . K . Ri<1d (Ed.I, Bethesda: ..\ -;' P& RS, .tOI_~.t-l , Jensen, J. R.• Hod gson. \1 . E.. \lacke y. Jr.• H . E. and W. Krabill . l inn . -Corrclauon Bet.... een A ireral\ :\IS5 a nd lID.-\ R Remolel y Sensed Da ta on a Forested WeI land , Gt'''.:""o InternaliOl" ' /. .t:3<) 54 Jensen. J. R. a nd :\1. E. Il od j;M.n. 2004. " Remole Sensing of SelCC1."an Phe no menon" III
Konecny. G . 2003. G. ,,,i,,j,,'m,lIi,.,, ,' R""",/,· S"m;ng, Ph.arogramm",,,r (",d G""grnplric InjiJrm."ioll Sy"em". london: 'l ajlor & Francis . 241( p .
R.1da f.- l'IWI" Krtm "".·I" .. 1"_"Kill.·.·rml! ,{ R"mul,' S<-,um.l!.
Iy -n ts
63:J~ i .
Ikndri\. ( '._ I'1'N . 1''''''''''<'I,',-i;:,I/I''''
Lefsky, M. A.. Hudak. A. T.• Coh e e. W. H. and S. .-\. Acker. 2(105. "( 'el'gra phic Var iability in Lida r Predict ions of Forest SI;U1d Structure in the Paci fic Non hw est.- Remote S,'m;ng of F. 'II';nm m,'nl. <)5:532- 5-1 1< ,
Leo nard . J.• JlOO~:;un .
\.i .E. aed P. Brcsl1a h:m . ~ nll,t -Accuracy "f Airborne' Lidar- Derrv ed Elcvanon : l·.mp lrica l A ~ s(.·" m(.·nl and Error
.4f'fJ lYJ'l< h fi" L1D.~ R AI·qrli..i,ion Frede ric k. r-.1Il : t-:arth ll ala Inc .. ~o p..
~ 005. r,·rlminll
alld l'mn"',liug,
'" '" w.eanhda ra.corn.
Budget." /'Jwl"~,.,,,m"<' I"I< ' I::11~u"'"ri1/J< & R,''''''''' S"lIsill~.
,
:\\;1. K.. 2110:'\. " 1>1- \ 1
70(J):BI -33'). god gson. M. E.. Jensen, J, lL Schmidt. L , Sch il l. S, i.111
ljSGS Le vel l and Le ve ll DI:M S : ·/kmo" ·S, 'lI.I i,,x of Envi-
Lidar I>a la." 1'/"" " KrwlI llI,-lr k E" /o! ;n",,l'i' lg & R,'I""'" Se " ..-ill~. 7 l(i): R.t7 1I5·\. Maune. D, F.. ( Hd.}, ,2011 1. /) lg ,I,, 11;.·/t' I'tl/iml ,\/" ,/", T<:d/llIJ l ogit'J ulld AI'I,/i"Uli'l/I,I': Till' DE.H Un''''' J/,IH""I. Bethesda: ASI' & KS.
"" 111"'11/. H 4(~()()J ) :2' )~ -' OS,
runts.
Hndg:;nn. M. Eo. Jensen. J, IL J. A . Rio rdan. K. D .• :1l1 <.1 C. r-.1. Archer. ~003 h. "Synergistic Usc "I' U [M R and Co lor
~ -Ill
p,
MeG lon c. J. C.• ~ Ofl4. '\(' ''' '1<11 of!'I"" og''''' ''',,"Il")'. Sth Ed.. Bethes da: AS P& KS. 115 1 p.
Aerial Phm0l!raphy for \1:lr pmg Urba n Parcel Imperviou s-
ness." f'/"'(lIg'''IIII1'''I'-I< El1x mn'l"i llg ,{ HL'mull! S,,"IlI1g. fli)('Jj :')73
·') ~ n
Mille r. S , D,.
~n04.
-Photog ra rnrnctric Prod ucts," in Mc(i \o n(',
J,. (Ed .), \/(/"11,,1 Ilf PI"" "g''flI"mt'lr~... 5t h Ed.• Bethesda:
ASI' & RS. ',1113 -11)[ 3. Hodgson. \I. E.. Jensen , J. R.• Raber. n r.. Tullis. J. A.. Davis. H. A.. G Thompsun a nd 1<: . Schuc kman , ~005. -An Eva luation of LI1HH -{jcrlvC'
"/"""-I(''''''I/I..,,.i,· EIIf:mn',illX .<
illg.711 11:1<1 7 S23
R,"'WIO!: S.,,, .<~
Mikhail. F.. M.. Bethel, J. S. an d J, C. \1 eG lon(', 2ClOI. " ,,",Jul'/101110 .\to".',n l'I"'lUgr"m""~'ln'. :,<, Y: John Wile) , .t79 p-
( ·IlA l' n :w.
354
Morris, J. T., Port er, n., I'\ccl. M.. Noble, r. A.• Schmidt. l.. La pine. L A. a nd J, It . J..n ~ e n, 20 11S, "lntegrann g L II)A R El-
cvc uon 0 '113 . Mu ltisp ectr a l Imagery. an d Ne ura l Network \l"" k ling fur Marsh Ch aracte rization ," lmernanonal J""rn
~OO4. X"rirmal CO/Ifor/Illm Ot/ Rt'''w /t,' Sen ring in
t"thutn",,,", Santa Barham : r-.:CGIA De· partment uf Cic u!!ra ph) . lJC SH; Was hingto n: DOT. 2 p.• h up :1 ,I.... '" w.ncgia.ucsb.c d u/nc rst researc h ncgia.html.
10
LIDAR Rem ote Sensing
Vegeta tio n poim Remova l Pr ocess ," Phu/ugrummclfICUt n<'('r i"IJ & Hrm"''' SrmmK. 61'(( 12) : 1.'07-1 31 S.
Snhclc. G. an d G vossctman, 200 ·t " Expe rimenta l Compel of Filler Algori lhm s fo r Hare- Eart h Extraction from Airb.:o Laser Scanmng Perm Clou ds:' /SI'RS J nurnai of P/l()/OfN" "'<'Ir)" & R,,",o l (' .~·IL,mg . 51);85 - 105 .
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Nilsson. M.. 1996. " Esum a nou of Tree Heights and Stand Volume using an Airbc mc L1DAR system." R."mm e S':lu i"g of Environment, St>( I): 1- 7. Quc ij a. V. R.. Sto ker. J. \1 . and J.J . Kowv ich. 2005. " Rec en t U_SGS . Ap plicati on s of L1 () A I{ . ~ I'h(lfo!?ram m..,ric En!?,.
" <'erin/{ &
Re"llJle .~·".""I/'.
Sanborn. 2UtlS. LlD.4R Tf!.: llRu!uK"II. Colorado Spri ngs: Map C"mp.;lny.• w~·w.san born .com .
Shn:'lha. R, L.. Caner. W.. Sarto ri, \t.. Luzum. B. 1. and ~ Stillion. ~OO ~ . " Airhom.. La, ..r Swath Mapping : Quanti~ Changes in Sandy Rea ches (WeT Time Scales of Weetl Y..ars . ~ !SPRS ;"'''RU! vj I'Jrul''Kru",motlry ,( R~lrlOle Steing . 59 :222-2.32.
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U.S u S.. 200t>, SJV'lJ.trd_ fur DIK' ful He"vllOl/ MoJ..J). ing ton : USGS ~ at i onal \l app ing Div ision. hnp:! ping .usg ~. I!0\"S1 andard ~ index . btml.
71( 1);1-5 .
Ra be r. U . Hodgvon. \1. 1:::. and J. R. Je nse n. 211(1(,. "I m pact o f L1O:\ R Nominul Postmg Dcus uy till Il £\1 Accu racy. Hyd ra ulic M odeling, a nd Floo d Zo ne Delineation ." f'/"'/(Igr
Wel t!'. \t o r\ .• J. C . Ritchi ... an d II . D , Fox . 11)9 ·t " Compm. o f Las.., and H e ld \t..a suee rnc ms o f Vegctarien Height .Ca no py Co' e r: · 11 m.., Ruvu,.. ..j Rej'"u",·h. 30151:1311D 11).
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Llmblc.D. A.. Evan s, D. L.. Carlso n. G C .• Pa rker. R. L Ot!doh . S C. a nd P. D. Gerard . 2003. "Characterizin g Vo:nial Fore se SlI1.1 l·tU": U ~ i n g Small- footprint Airborn.. U DAR," H,'mo/. ' S" Il.\/IIX '~I £1I\'i rullm " II/. 117 ; 17 l - l l'i 2 .
Remote Sensing of Vegetation
11
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PprO),imatel Y 10 percent of the Earth 's land surface is covered w ith vegctation. Fun rmcre. vegetation is one of the most Important components of ecosj stem s. K no.... ledge about variations ill ...egetaticn species and community distributio n patterns. alterations in "q;elll.lioll phenological (growth, cycles. and rnodificauons in the plant physic Ob'Y and morphology pro' ide valuable lO~ight into the cl ima tic . edaphic. ge\)logic. and physiographic characterisucs or au area (WCiCTS ~ al.. 2004 ; Jack - and Jensen. 2(05). Scienlists. hav c d,;"HliOO significant effort 10 develop sensors and ... isual 3nJ dillilal image processing algorithms to extract important '"-tlctatiIJIl bicphyslcal information from remotely sensed data te.g.. Town shend and Justice, 200 2) . Many o f the remote sensing tec hniq ues are generic in nature and may be applied 10 a variety of vegetatedlandscapes. including : agriculture
o
d
forests rangeland v. et land
man icured urban' cg etation, lo is ch apte r lnrr odaccs the fundamen tal conce l::i associated wi th vegeta tion biophysica l c hara<.' tcristlcs and how rem otely scns<.' u data cun he proc essed to prov ide un ique info rmat ion about these parn melers. It t hen sum mari zes some of the vege ta tion indi ces deve lope d to ex trac t h iophysil-al vegetalion informa tion from digital rem ote sen sor c• ta. Seve ral o f the memes used by land scapc ecologists to extrac t meanin ul param eters ahour vegeta t ion patch sha pe. s ize, etc.. us ing remote sen su data arc then sunun ari/cd. C ase studies arc pro vided throughout the chapter n remote sensing ofngriculturc. inland wetland , coastal wetland. and biodiv ersity, Photosynthesis Fundamentals
Oil and coal today prov ide mor e I n 90 percent of the energy needed 10 po wer automobiles. trains. trucks. Sl lpS. airplanes. facto ries, and a myria d o f elec trically energized ap pliance s. comeuters, and co mmunication systems _ The energy .... uhi n oil and coa l wa"...,riginally " ca ptured" from the Su n by
355
356
plants grow ing millions o f years ago that were transfo rmed into fossil fucls by geological ti;l TCCS. Therefore. photosyn thes is. at least mdir ec tly, is n OI only tho: princi pa l me ans of enabl ing a civilized soc iety to func tion normally but al so the sole mean... of sustaining lite - ('
(" H A I' (Hol
11
Re mo te Sensing of Vegetation
leaves and canopies appe ar sp ec trally .... hen recorded remote sensi ng instruments.
Spec tral Charact eri stic s of Vegetation
A healthy green leaf interce pts inci dent rad iant flux ( ~ directly from the Sun or from d iffuse sky light scattered the lea f Th is inc ident elcctromagncnc ene rgy interact; the pigrn ems. water . and interce llu lar air spaces WIthin plant leaf. TI1.: amount of rad iant nUI\ reflected from the101 ( $p I. thc amount of radi ant nux abso rbed by the l~f ( ltl. and the amount o f rad iant flux transmitted through tilt IelI ( ~ T ) can be carefully mea su red as we apply the ene~ b!!ance eqoanon and atte mpt to keep track o f what haf'PCD$ all the inci dent e nergy. Th e ge ne ral equation for the m\tn:· tion of.\]k(·lml (i. ) rad iant nU_\ on and \\ uhin the leafis
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Divid ing eac h o f the variables hy the origina l inc ident ram. ant IlU\, 41,••
(ll-j yiel ds ( 1 1 ~1
where P l.. is spectral hemisp herica l reflectance ufthc leal is spec tral hemispherica l ubsorptancc. and "ti. is Spcl1ral he mis pherica l trans mittance by the lea f Most remote ~cn)· ing systems funct ion in the 0.35 - 3.0 urn reg ion mcasunng pri marily re fl ected energy, Th erefore . it is useful to thinkor this relationship a s Q ).
Phomsymhesis is an energy-storing prec ess that lakes p lace in lea ves and other green part s o f plants in the presence o r ligh t. T he Iighl energy is stored in a simp le sugar mol ecu le (g lucose ) that is produc ed from car bo n diox ide (C0 2) present in the a ir and water l 1120) absorbed hy the plant p rimarily throug h the mo l sys te m. When the ca rbo n d ioxid e an d the water arc com bine d and fo rm a sugar molec ule (e(>B 1:° (» in a ch loro plast, oxygen ga s tOll is re leased as a by-product. T he oxygen d iffuses out imo the at mosphe re. The ph otosy nthet ic proc ess begins " he n sunlig ht str ikes ch!o /TJplm ts. small bodies in thc lea f tha t co ntain a gree n substance ca lled chlorophyll.
I I 1-5)
.... he re the en ergy reflected from the plant leaf surface is eq ual to the incld em energy mi nu... the energy absorbed d irect ly h) the plant fo r photosynthetic or other pulpOSt'I and the amount of energy tran ...mined d irectl y through tk leaf onto other leaves or the ground beneath the ca nopy.
Dominant Factors Controlling Leaf Reflectance Plants have adapted their internal and ex te rna l structure to perform pho tosynt hes is. Th is structure and its intera ction w ith electromagnetic energy has a direct impact on ho w
Pioneering work b)' Gates et at. ( 19M ), G au ...mann er at. ( 1969 ). M) C~ (I nO) and ot hers demonstrated the impor·
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357
ral Characterist ics 01 Vegetati on
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Spect ra l rcuectancc characrc rbucs ofhcahhy green vegetation fur the \\ ilvc!l:nglh inlcn al 0 ,4 2.(' 11m, Th e dominant fact ors comrolhng k at" reflectance a n: the various leaf pigments in the pnlisadc mes" phy ll te.g.. chloro phyll (/ ami h. and li-ClI rolle" c). the .call.:ring o f nca r-mfrared ener gy in t he spongy mcsophyll. and th..: al11 (1unt "f" atcr in the plant. Tho: primary ..:hlowphyll al>~\lrp(illlll>alld ~ IIccur:1I n,·O _ 0.4 5 J.Hn and 0.1i5 _ o.o li).Jm in the ,i slhl... region. rh c primar y wate r .d',orpt inn bauds llccu r ,ll {)<)7, U I/, 1.45, 1.')4. and 2.1 1Jrn,
ance o f unders tamling ho w le a f pigllle'llIS , inter na l scatterIl@.. and leaf water content affect the' reflectance and ansminance propert ies of leave s (Peterson and Runnin g, 9~Q }. Dominant factors co ntro lling lea f re flectance in th e egion from 0,35 - 2.6 11111 arc summarized in F ig ure II - I, laihle l.il);hl huera ctton wi th l·i ~ml.'lIh i n t he Pal i..a tlc 'll'W p h ~ 1I
Mrddle-iutra rcd
Nc ar- infrared
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carbon diox ide (CO:)
T he carbon dioxide fro m the a ir a nd the wate r p rovided by the root a nd ste m syste m repres ent the fu nd a m e ntal raw ma te ria ls of photo..ynrhcsis . Sunlig h t provid es the irradianc c
The process of feod -mak ing via phottl s} nth..:sis determines
IE~ 1
Joy.' a leaf and the associated plan t ca nop y ac tually ap pear 21iomc trically on remotely sensed images. A hea lth y leaf eeds three th ings III mak e food :
sccuon of a Iypical green leaf if> sho wn in Figur e 11-2. The
that powe rs photos ynthes is.
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358
( ' II\ I"IE R
Phloem tissue
11
Rem ote Sensing of Vegetation
Xylem lis..sue
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air space Figure 11·2
Spongy pnrcncbymu mesophyll cell
a) Hypothetica l cross -sccucn o f a typical hea lthy green leaf, showing b oth the lUI' a mi unders ide uf th... leaf. The chl(lfoph~ll pigments III th... roalis;HIc parenchyma cells have a signitkam impact on rhe ahsClrpliu n and reflec tance o f vis ible light (bl~, gr..-cu,
species and e nvironmental condinons Ju ring gro wth. Carbon dioxide enters the lcaf'from the atmosphere through tiny pores called stomata or stnmu, located primarily on the underside: of the leaf on the /0" '(''' epidermis . Each stomata is surrounded by gmJr(1cells thai swell or cont ract. Wh e n they
swel l. the stomata pun: opens and allows carbon dioxideIC enter the leaf. A typica l sun llo w cr leaf migfu have 2 millioD stomata. bur they make up nnly about I percent of the leafs sur face area, Usually, there are more stom ata on the: bottom
s
Spectral Char acteristics 01 Veget ation
aleaf; howeve r. on so me lea ves the stomata arc c\ en l) brributcd o n both the upper a nd lower epidermis top layer of lea f IIPP"" epidermis cells has a cuticnlor ace thai diffuses hut re fle cts very lillie light (Philpott. 971). It is variable in thic knes s hili is oflcn on ly 3 - 5 tnu ~ i d, with cel l dimension s o f approximately 18 x 15 x 20 ~. It is usefulto think ,ll" it M a waxy. mmsluccnt material smila r rorhe c ut icle 31 the lop ofyour fingern ai l. Leaves o f 1Wl)' plants that gruw in br ight sunlight ha ve a thic k cutic le till can fi lter out so me lig ht a nd guard ag ainst e xces sive .wn .... ater loss . Conversely, so me pla nts suc h a\ terns and bll~' shrubs on the f(lrt.~1 Iloor must sun ivc in shaded conMions. The leav es of many of these p lants have a thin cu ntle"'O thai the p lant can couec t as muc h of the dim sun light "possible for pho tosy nthesis. Yany Iea\t."" in direct sunllg.h t have hairs gro\lling out ofthe IlppCT (and 10\-lcT) e pidermis. cau s ing them 10 fed fU/.z) . l1Ie~e hairs ca n be hendid:a l, ;ls they reduce the i nt c n ~i l Y o f Ik Incident sun light h' the plan t. Nevertheless . much o f the li,ihle and near-infrared wavelength ene rgy is transmitted d1 rough rhc cuticle and lIppl'r epidermis to the pulisude Nlrench) rna mcsoph y II cells a nd spongy parenchyma mesopbyll cells below. PhoIosynlhesis occ urs inside the typical green lea f in tw o uoo:> of food-making cells - l'alisIlJ~' p<1Il'lIchyma and lP"'ngy parenchyma mcsop hyl! cells. \100;,1 leaves haw a disIIFICI layer o f lon g pa lisad e parenchyma cells in the upper put of the mcsophyll and more irregu larly shaped, loosely eranged spon gy paren chyma ce lls in the 10 \-1 cr part of the eesophy ll, The pal is,l(!l' cel ls ten d totorm in the portion o f the mesophyll tow ard the side from which the light enters :he leat: In most horizontal t pla nophile j l e ;l \'C~ the: palisade ceils will be toward the upper sur face. but in leaves that grnw nearly vertical [crcctophilc ]. lhl' pal isadl' 1'e1 ls may fonn from hntll side s. In S(1m~' Icilves the clongat~'d palis,lde «:lls arc entirely abs ent anu only spo ngy pllrl'llehyma cell s .,ill ex isl within the mesop hy l!. Ibl' ed lular slruc lure of the lea f is la'l!e co mpared to the of ligh t tha i inte ract wit h it. Pali ~uc cel ls arc typically 15 x 15 x no !Jm. whi te spongy me"llphyll parench)'ma ce lls are sma ller. T he- pa lisade paTl'nehy ma me:
The ch loro pbsts arc gcnera lly 5 - 8 11m in d iamet er and 1bout I !Jm in w idth , As m..m y as 50 chloroplasls may be in caeh paren ch)'lI1a cel l. \\'ithill the chloro plasts arc long slender grlll/(/ slrands (n"l sh".... n l wi lh in whkh th..:
prtSl'nt
359
chlorophy ll i.. actuall y located (approximately' 0.5 urn in lengt h and (l.OS urn III diameter) . The chloroplasts are generally more abundant tU" ;lrd urc upper side o f the leaf in the pa lisade cells and hence accou nt for the darker green appearnnce o f the uppe r lea f surface co mpa red with the bottom Ii~ht.:r surface. 1\ molecule, wh en struck fly a wave or phot on of light ,
rencct s some ofthe energy or it ca ll absorb the ener gy and thu s enter into a higher energy or exc ited state (refer to Ch ap ter 2 ), Eac h molec ule absorbs or re flect s its ow n characterb uc \\ a\ elengths o f light. Molecules in a typical green plant have evol ved to abso rb wa velengths of light in the visihlc region o f the spectrum (O.J5 - 0 .70 !Jm ) very well and arc called pigments. An absorption spec trum for a part icular pigmcru describes the wavelengths at whi ch it can absorb light and enter into a n exc ited stare. Figure II-Ja presents the absorp tion spec trum of pure chlo rophy ll p ig ments in so lut io n. C hlorophy ll " and b a n: the mo st impo rta nt p lant prgm ems ab sorbing blue a nd red ligh t: chlorophyll II at wavelengths of 0.43 und 0.(6)Jm a nd chlorophyll b at wavelengths 01'0.45 and 0.65 um (F arabee, 19( 7). A re lative lack of nbsorpnon in the wavelengths bet ween the two c hlorophy ll absorp tion bauds produces a trou gh in the absorption e fficiency at approx imately O.5-l !Jm in the green portion of the ele ctromagne tic spectrum (F igure 11-3a). Thu s. it is the r..: lat h el ) lower absorpt ion of green wavelength light (ccornpared to b lue and red light ) by the le af that causes healthy green folia ge to appear green to ou r eyes. There are othe r pigm ents pre sen t in the palisade mesophyll cel ts that are us uall y rna- ked by the abundance of chlorophyll pigments. For examp le. then: are yellow " ",n lt'" e.' and pule yellow xlImhopJry/l p igments, wuh strong absorption primarily in the blue wavelength region. T he [l-carotene absorption spec tra is shown ill f igu re 11-3b wi th its strong ah~orptinn band cc nt('rt'd (It abo ul 0.4 5 !Jm. Phy coerythrin p ignwllts Illay a ls,) bl: prescnt in the k af wh ich ah~o rb predUlllinaruly in the gree n regio n cent ered at about 0.55 !Jill. allow ing b lue an d red light to he reflected, P h.l'C ·(lQ l/Ili/l pigIll.:ntl> ab sorb pri ma rily III the gre",n and red reg ion .. cen lered al abl,lut 0.(>2 )Jill. al1u.... illg mueh ufthe b lue and som ... of the grt.'C1l li£ht ( i.e., the com hination prod uces eyan ) to he rel1 «t~ (Fi gure 11 -3b ). B«aus.: c hlo rophyll a and b chloroplast s a~ atso pr,,">Cnt and ha\e a si mi lar absorption band in I hi ~ h lue reg ion. the y tend 10 dom inate and mask the effecl of the other pigments present. \Vhcn a plant underg0C5 St.·l h:sce ncc in the fa ll or eneuunlcrs SITOS. the chlo rophy ll pigrnl'llI may disa ppear. allow ing the carolenes and other pigmen ts to hecome domi nant . For e xamplt: . in the fal l. chloTIJ phyll pruduction ceases. causi ng the ye llu w t'o lom tion <)1' the c,lrotcncs and ot her l>p.:c iti e pigm ents in the trce tol i·
ru \PT U I.
360
11
Remote sensing 01VegetatiOll
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.;I) Absorpnon spectra of chlorophyll (l :md h I'igm<:ms. ( 'hl" w phyll "and " pigment' in a tea f'absorf much ofthe incident ~ .IIlJ red wavelength cncq:y. b! Ab sorpncn spec tra uf~-cawlcllc, which absorbs pruuarlly in the blue. Dthcr I'i gmcnls that mi@ll he foun d in a lea f inclu de Phyc oe rythrin which
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red light Iutlcr Farabee. 1,-)<)7).
age 10 bec ome mo re visible to our eyes. In add it io n. some tree.. produ ce grea t quanti ties of
The gree n leaf (a). ye llow leaf to). and red k a f (e ) were qi o n the Swee tgum tree at tJ1\: time o f data collec tio n. The dai brown leaf (d l was collected on the ground beneath tile lift.
Fhe t w o optimum spec tral regions for sensing the chloroph:-11 absorption characteristics of a leaf arc believed to be 0.45 - 0.52 urn and n.M - 0.69 11m ( Figure 11-3a ). The
A GE R 1500 (Geophy sical & Env ironmental Resea rch be handheld spcctroradio mctc r wa s used to obtain speanI reflecta nce measuremen ts trem each otrhe leaves . The speenuradiomcrer obtained spectral re flectance mcusu rcmesas a 5 12 bands in the ult raviolet , blue . green . red , and near-infrared spectral regions fro m J 50 - 1050 nm . Percent rclkctallre meas ure me nts were ob tain ed in the lab by measuring l~ umounr o f energy reflected from the surface of the leaf (lhe target) di vided hy the amou nt or ener gy reflected from i Sp.:dralonE re flecta nce re ference (percent reflectance = argctJrefe re n,,;1.':X 1( 0) The re fl ectance measurements for eadl o fthe lea ves fro m " OU - W5U nm were ploued in a pl'1l.'CIl reflectance graph (Co lor Plate ll -Icj.
fo rmer region is characte rized by strong absorption b)' caroteno ids and chlorop hylls. whereas the latter is characterized hy strong chlorophyll abso rption . Remote sensi ng of c hloroph yll absorption within a canopy represe nts a fundamenta l biophysical variable useful for many biogeographica l investigations. The absorption c haracterist ics o f plant canopies may be cou pled wuh other remotely sensed data to identity vegetation stress. y ield. and other hyb rid vnriahlcs. Thus. many remote sens ing studies are concerned wi th monitori ng wha t happens to the p J",ro.wnth.-/it"ulll·
s
The green 1ea f (C{llor Plate 1I· la) wa s still photos yrubeseing and yielded a typica l heal thy green re fl ec tance sp«tn With stro ng chlorophyll absorption bands in the blue and red reg ions (a pprox imat ely II percent reflectance al 450 nmand 5 percent at (150 1111\_ respec tiv ely). and a peak in rc flectarce in the green reg ion ofthe vis ible spectrum ( I I percent al550 nm) . Ap proximately 76 percent o f the inc ident near-infrared rad iant nux was refl ected from the leaf at 000 nm.
I Characteristics o f Vege tation
~ellow
leaf [Co lo r Plate I I- I b ) was und ergoing sencsAs the in fl uence o f the ch lorophyll pig ments dimin relatively greate r amoun ts of gree n (2..J pe rcen t 31 550 landred (3:! pe rce nt at b50 nun lig ht "ere re fl ected from kaf"result ing in a ye llow appearance. At 750 nm the yetleaf refl ected less ncar-in frared radi ant tlux than the Ith} greenleaf ]lIlW",, \ er. ncar-infrared reflectance
leaf (Co lor Platt: I I - Ie ) re flected 7 percent o f the at ..J50 nm, b percent ofrhc green energy at 550 nm, and jere cnt o fthe inc ide nt red en ergy at 050 nm . Ncar-i n frareflectanc e at 900 nm dropped 10 70 pe rcent . 1'1'.11
dID. brown lea f (Color Pla t... 11-1d) produ ced a spect ral
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tanc... cu rve with low blue ( 7 percent at ..J 50 nm ), gr een pmtlll at 550 nm I. and red reflectance (I ll percent at tl50 ). lhis co mbinatio n produ ced a da rk brown ap pcurunccear-in frared reflecta nce d ropped ttl..J..J percent at (JOOnm. j, important to und erstand the physi ulugy of the plum s
r iI1\ estiga tio n and cspeci;llly thei r pig mentation ch armsrics sothat we ca n ap preciat e how a typ ica l plan t will ar w hcu chlorophyll absorption starts to dec ree sc. euher 10 seasonal senes cen ce or environm ental stress. As dcmted. when a plant is under stress an d 'or c h ltlroph~ II ion dec rea ses. \hI: lac k o f ch lo roph yll pigmentat ion I} causes the p la nt to absorb les s in the c hlorophyll ion bands. Such p lants will ha ve a muc h hight:'r huncc:. pa rtic ularly in the green and red port ion of the .,mrum. and therefore may appea r yello wish o r chlorotic, fact. Carter ( ! 9
be
Leaf spectral retkctan . . e is mllSI likd y til ind icat e p lant .;; Ii ~t in the sensitive 535 - MO and 6~ 5 - 700 11m \isi light wavelength ra nge s. Increa sed re lk'ctance ncar 700 ~e nts the o tien reponed " b lue shi n of the r~ ~dge :' ,the shi ll IOward short~r wa \e lengt hs o f the red-in frared ition l;une that occurs in stres~d plan ts when retlccis p lo (led w rsus wa ve lengt h l C ibu la a nd Can~r. ~f. The shi ft toward short er "3\'ekn gth s in the region 650 - 700 nm is part icular ly eviden t for the yell ow and III ren~cta nee eurws shnw n in Co lor Plat..: II-Ie. I{ernt'le rIlSing wilh in thes.: spect ra lly narrow ra nges may prov ide IIplO \ ed ca pability 10 detect pla nt stress nol ollly in imliv id.1I ~a\"es hU I for whole plan ts ,tllll p<."rhap s for dl' nsl' ly \'t'gf.lloo eanopics (Carter. 19'13; Ca rt.:r et a1.. 191}6 ).
36 1
Normal color film is scnsiuv c 10 b lue. green. a nd red wuvc len gth energy. Color-infrared lilm is sc ns mvc to gree n. red . and nea r-infra red energy a ttcr m inus-blue (yellow 1filtrat ion (re fe r to Chapter -I} T here fore, even the mOSI si mple cume ra with color or co lor-infrared fi lm and approp riate ha nd -pass filtrat ion ti.e.. o nly certai n wavelength, of light IIr~ allllw.:-(1 to pass) can be used to remot ely sense d iffe rences in s pectr a l rcft cctnnc c caused by the pigmen ts p resent in thl' pa lisade parenchyma layer of cells in a typica l lea f However . to dctc-ct very subtle spectra l re flectance diffe rence s in the rclarivcly narrow ha nds suggested hy Cibula and Carte r ( 1<,1 <,1 2) and Ca rter et at. ( 1<,1 4(,). it may be neces sa ry 10 use a h igh spectral reso lution imagi ng spcc troru d iomcter that has very narrow hand" idths
Near-tnrrared En erJt' In t...ract iun with in th e SponJt' " lc\f1llh~' 1 1
Cl'lI \
In a typ ical health y green lea f, the ncar-in frared re flectanc e 12U() nm. inc reases d ramatically in the reg io n from 700 For e xample. the health y gr een lea f in the pr..-\ iolls example reflected approximately 7(l pe rcent of the incident nearinfra red e nergy at 900 nm . llcnhh y greenleaves abs orb rad iau t ene rgy very etficicnrly ill the blue and roo po rtiolls ( I I' the spec trum wh ere incidc nt light is req u ired for photosy nthes is. BUl im med iatel y to the lon g w avclc ngth side of the red chloroph y ll absorption hand , " hy does the reflectance and tra nsr niuancc o f plant lcave s inc rease so dra mat ica lly. causin g the absorpianc e 10 fall to low values ( Figure I I - I f! Thi s co nditio n oc-curs throu ghout the ncar- infra red wa velengt h ra nge " here the dir ect sunlight incide nt o n p la nts has the hul k o f its energy. If plants a bso rbe d this energy with the sa me ertie ierl"-) as Ihey do in the \ isit>l e region. they could becom e mu d l 100 w an n and til\." prot e ins w(lulu be irr,,: vcl'5ibly' de natured. ..\ s a resu ll. plam s h;l\ e adapt ed so thcy do not use th is massive ;tI1ltl llnl ur n ea r-i n fra r~ d ene rgy an d s imply re!lect it or trans m it it throug h 10 underlyi ng leaves or til\." gWlInd . 'l"h.: spo ngy lll~sliph y l l lay..-r in II gree n k ill' "-\lntro b the amount of nea r-in fr
e ll \ I"T[R
362
=-
Hi ~
IOH
11
Remote sensing of Vegetation
Btucst em Grass Absor ptton, Rcn ccran ce, and Tra nsmitta nce
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Fig ure 11-4
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Hemisphe rica l refle ctance. transuuttancc, a nd absorpuon characteris tics of Big l3luc stCI1l jp"a, s ada xiallea f su rfaces obtalIKl! using a labvrat"I)' Spl'(:ITor-adio Jllctcf. The reflectance and tra nsmittance curv es are almost mirror imagl'S of one anOOie' throu ghout the _lsi" lc and nea r-infrar ed portions o f the clcctrornegncuc spectrum. The blu e and red chlorophyll ill planb» sum much o f t he incid...'llll'llcrg)' in till:' visible poruon o ft he spo:clrum (0 .4 - 0 .7 um r tatter Wa lter-Shea and Hrehl, I Imaging Spe'CIWIl1t:tCA such a" AVI RIS arc capable of Idl'll\lf~ i n~ small changes in IIJ<.o abwrpt ion an d relk.:t i..,n.:h.trxtmf. tics of plants because lh.: sensors Ofl~'Tl have channels Ih.u J.I\' onl} 10 nm lipan. i.c., WI: could have 10 channelv in !hefePi" from 0.6 - O. 7 urn (f>(ltl lo 700 nml .
images of (JOe anot her. as show n in Figure 11·4 (Wal ter·Shea and Bie hl. 19l)() .
The hig h diffu se reflectance of the nca r-infrared (0.7 - 1.2 11m) e nergy from plant leaves is due to the intern al scattering at Ihe cell wa ll-a ir interfaces w ithin the leaf (Ga usmann el al.. 1969; Peterson and Running . 1989 ). A w mer vapor absorption band exists at 0.92 - O.9g um : consequently, the opumum spect ral reg ion for sens ing in the near-infrared region is believed to be 0.74 - 0.90 11m (Tu cke r. 1978). The main reasons that hea lthy plant canopies re flect so muc h ncar-in frared energy arc : the lea f already refl ects 40 - 00 perc ent o f the incid ent ncar-in frared energy from the spongy mcsophyl l ( Fig ure l f -r j. and
the rem ai ning -IS - 50 percent (If the ene rgy pcTldrar.:s ti.e.. is tra nsmitted ) th rough the lear and can he relll:\1d once again by leave s below it, This is called k l/( addtnve If / /eUllnCe. For e xample. amsider the re flectance and transmissio n characte ristics ofl!lt hypo thetical two-layer plant canopy sho w n in Figure Il,~ Assume tha i leaf I re flects 50 percent o f the incident I'd infrared energy back into the atmosphere and that lit remaining 511 pt:reent o f the ncar-infrared e nergy is tr.m"lli 1I..·d thro ugh leaf I (Into lea f 2 , The trans mitted energy tIlCII falls 0 11 lea f.:! where 50 pcrecut aga in is unnsmiucd ( ~ 5 p.~. cent (11' the original) nnd 50 perce nt ts rcnccted Tht re flec ted ene rgy then r a" cs hac k through leaf I which <1110 \\ s ha lf (If tha t ene rgy l or 12.5 percen t of the originallll' he transmitted and haltrctlcctcd . The resu lting total energy ex iting lea f I m this two-la yer exam ple is 02 .5 percenlo ftbt inc ide llt energ y. Therefore. the greater the num ber of
5,
r
ral Characteristics o f Vegetation
363
.a ddu tve Reflec ta nce from Leaf I a nd l.('af 2 Jot l ..
T,
Retlcctcd
flux. <,I'T 112 4>, -50"0
raJ idHl RJ ~
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Rgure 11-5
112 R.
I l fl 4>;)
A hypothetica l exam ple of uddinv c refl ec tance from a canopy with lwo leaf laycrx. Fitly percent of the incident radiant flux. <1>,. 10 leaf I is Tetleck<.l (K, l. and the other 5(1 percent is transmuted,lI1to ka fl (Til. rifly pcrccm ofthe radiant Ilux incident 10 leaf2 is tra ns mitted through k af2 (T!); the other 50 percent ISreflected toward the base of leaf I ( R~). Fifty percent ofthe energy incident errh.. ha...e ofleaf I is ua nsnuued through il (T ,) "hik III<: remaining 50 percent (R,) is relk cl<,..,J to.....m J leaf 2 once aga in. AI Ihis point. all additional 12.5 percent (1 iiI reflec ta nce has been coetribeted hy leaf 2. bringing Ihe 100al reflee ted radra nt 111,1 '" ttl 02 .5 percent . H OWC'\ C'f. to be e ven more accurate. on..: "
hyers in a hea lthy. mature canopy, theoret ica lly the greater
me infrare d reflectance. Conversely, if the canopy is only »mposcd of II single. sparse leaf layer then the ncar-inf rared etlecranc e w ill not be as great because the erwrg.:- thai is nns miu ed throug h the leaf layer may be absorbed by the !!OOnd cover beneath . t"Gmges in the ncar-infrared spec tral properties o f h<"a llh) ~'11 vcgetanon may provide informat ion abo ut plan t scncseece and/o r stress. For exam ple . co nside r the Ii-l UI' leaves lid their spectral reflectance ch arac teristics shown in Color ri.llc I I- I. The photo sym hesizing g reen Icaf (:!) c xhihired I(fIlng chloro phy ll abs orption in the blue anti red wavelength ~giol1s. an und erstandable increase in green reneelance . and lWroximatdy 76 percent refl ectance in rhe nenr-in trared ~on , Afte r a certain point. nca r-in fra red refl ec tance i:ma~ as the leav es scncsccd [b - ti l. 1I0 w ever, if the
leav es were 10 dry out significamly du ring senescence.....c would expect 10 ~ L'(' milch higher reflect ance in the ncarinfrared reg ion (Ill be discussed short ly ). Sc icruists han' known since the 19(.,(ls tha t a direct re lationship exi~ls betw ee n res ponse in the near- in frared reg ion and various biomass mea surements . Converse ly. it ha s been shew n that an ifll't'He re lations hip exists between the res pon se in the vis ible reg ion . particularly the red . and plant biomass. The best way to apprecia te this is 10 p lot all of the pixels in a ty pical remote se ns ing scene in red and ncarinfrared reflectan ce space. For e xample. Fig ure 11-6 a depic ts where app roxima tely IO.GOl) pixels in a typ ical agr icu ltural seCIK' ar e located in red and nca r-in frared mu his pcctral featu re space t i.e.. w ith in the gray area ). Dry bare soi l fields and wet bare so il fields in the scene ....ould be loca ted J t opposite ends of the soi l line . This means that a wet bare
•
11
364
High can"p> closure "r biomass
Di vtr-lbuti u n of Piu·1s in
Red a nd xea r-Inrrarcc S jwclral Span'
Rem ot e Sen si ng of Vegetation
H igh (;In,,I"'>' closure or
M i;::ralioll of a Pix el
in Red a nd x ear-tnrrared
biomass I" PC)
S pe cara l S pace During :, G ro wi ng Sea..on
A1 Jl\"~1
ripe
lnterrned iatc canopy closure or b i.>m.\M
lI a rH'l>!C'd ;
"' " 'egcWlloo
rrt''lrnl ,m dry 'It.il
Pla nted: Wei ba re "Oi l
1\0 \~('\.;Il"""
pr esen t on mOist so il It.-J kctk...tance b.
k ed Re flecta nce
a, Figure 11-6
a) l ht: ul"lnbl.lli,Hl of a ll the pitch in a scene ill red and n.:.II-in fr.ar. J muluspcc trul space is foun d in the gruy s.hado:ln. Wet and moist bare soil fields arc loc ated along the soil line. The greate r the toj" m,lSs and.o r crop c3m'py closure. tile ~ Ill<: ncar-uurarcd rer fec iance and the I".....·r the red refl ectance . Th is cUll
ular dlrec nou away from the soil line. 11 )The nugranon of n single wgel;l1l'd agricultur al pixel in red and near-infraredmull. ~pt.'l:trnl space during a grtlWlIl1! season is sho wn. After Ihe cr"p elllergn. II de pan ~ fw m the ....,il line. eventually readlill: complete canopy closure. After h;lr\est ing. the pixel will he f" und on the «ulImc.b m perhaps in a drier soil condition.
soi l would hav e very low red an d ncar-infrared reflec tance. C onversely. a dry hare soil urea would probably have high red and high nca r-infrared re flectance. As a vcgcuuion ca nopy matures. it rc rlccts more nca r-infrare d e nerg y \\ hilc at the same nmc ahsn rhing more red radia nt tlux for phetosynthc ric pu rposes. T his « lllS!.'S th e spectral reflec tance o f the pixel 10 m ove in a pcr pc udiculn r directio n awa y from the soil lin,' . As biomas s increas es an d as the plant cn nop y cover inc reases. th e field's loca tion in the re d and nca r- Infrare d s pect ral Sp,lCC mov e s farther aw ay Iro m tbc soil line . Figu re 11-6 b demonst ra tes how j ust on e ug ricull ural pixel
mightmove abo ut in the red and nc ar-infrare d s pec tra l spac e during a typical growing seaso n. If the field was prepared properly, it 1.\I1u 1J proba bly be loca ted in the mois t ban: so il region o f the su il hue with 10 \\ red and low ncar-infra red reflecta nce a t the oc g in ning o ft he growi ng se aso n. A fter the crop emerges, it would de pa rt fro m the soi l line. eventual ly re ac hing com plete ca nopy cl os ure . A t th is poi mt he refl ected
near-infrared radiant tlux .... ould IX' high and the red ren eelance .... ould be ksw. Aller ha rvcsuug, the pixel .... ould prob-
ably he found once ag ain on the soi l li ne hut perhaps ill drier con du inn.
The rl"l al ill nship between red and ncar-i n frared eanllp)' reflectan ce has resulted in the developm ent of numer~ remote s,-ns ing vegcunion indices a nd biomnss-cstimauq techniques that utjliz c m ultip le measure me nts in the \'isib~
aud nea r-in frared reg io n (e ,g.. Kichurdson a nd Eve riu, 1992. Lyon ct ul.. I')l)H ). The result is a linear com bination lh3r may hi: more highl y corr elated with biom ass than cithentd o r nea r-infrar ed mea-oucm en t alon e. Several of these algcrithms arc summarized in the sec t ion on Vcg.:ta tiun Indira in th is c ha pte r.
Mlddle-Infr ured EII,' rI:J huera ctj ou with W at H in tk S IIU II~)"
_' Ie ~ op h) 1I
Plants require water to grow. A lea f ob tains wa te r th~ the plant 's ro ots. T ho: wa ter tra vel s from the roo ts. up til SI,'I11. and enters the lea f thro ugh the />I'/;O/t' _ Veins ~ .... a tcr 10 the cells in the le af. If a plant is wa te red so tIw:.
,
I Chara cteristics or Vege ta t ion
lIS as much wa te r as it call poss ibly ho ld at II given .ir is said \0 he fu lly nogtd. Much o f th e water is found IJIe spongy meceph yll port ion of the plane If we lilrgct III the plant or ra in fall decreases. the p lum w ill comain a n t of wa tcr thai is less than il can pote ntia lly ho ld. Th is led its relative tW1F,Mity . II would be usefu l to have a M.:nsing instrument that wa!!. sensilL \c to ho .... muc h
lias actua lly in
it
plant leaf. Remote: sens ing in the
le-mfrare d. therm al infrared (C hap ter X), and pa ssive wave (Cha pter 9) po rtio n o f [he elect romag netic sp ec'lIIl can provide such informa tion to a limited exte nt.
id water in the atmosphere creates 11\ c major abso rption in the ncar-in frared through m iddle-in frar ed portions I!I( electromagnetic spt."i:lrum at O.Q7. I.IQ. 1.45. 1.94 . 2.7 um ( Figure I I-I ). The fundamental vibrational -absorpuon band at 2.71101 is the stron gest in th is pa n lhe spectrum (t here i ~ ilbo one in the thermal infra red on at 6.27 J.Im ). Hu wcvcr.thcre is also a strung rel at ionbetween thc reflectan ce in the midd le-in fr ared reg ion 1.3 - 2.5 J.I I1l and the amount of water present in the es of a plant canopy. Water ill plants absorb mc idcnr between the absorption ba nds with increas ing at longer wavelengths. In these middle-infra red elengths. vegetation reflectance peaks occur at about I. b 2.2 11m. between t he maj or atmosp hcric water absorpbandsl l-'igun:: 11- 11.
'.
365
Leaf re flectance in the middle-infrared region is inve rse ly related 10 the ubsorptancc of a lay er of water appruximurely I mm in de pth (Carter. 19( 1). The d egree 10 which incident so lar energy in the midd le- infrared region is a bso rbed by vegetation is a functi on of the tota l amount of water present in the lea f and the lea f thickness. Ifproper choices o f sensors and spe ctral ban ds are made. It is possible to monuor the re lative turg id ity in plants. \1 os1 optica l re mote sen sin g sy stem s (ex ce pt radar) are ge n-
orally cons traine d 10 func t ion in the ..... uvclcngth inte rvals from 0.3 - 1.3. 1.5 - 1.11 . and 2.0 - 2.6 u m due to the stro ng atmospheric wate r absorpt ion bands at l AS. 1.9-1. and 2.7 J.I m. Fortunate ly, as de monst rated in Figure 11-7. there is a strong "carryover" sensitivity 10 wat er co ntent in the 1.5 1.8 and 2.0 - 2.6 urn regions adjacent to the major water abso rpt ion ba nds. Th is is the reason that the La ndsat Themat ic Mapper (4 and 5) and Landsat 7 Enhanced Th ematic Mapper Plus ( Ell\-l ') were made sensuive to two hands in this reg ion: band 5 ( 1.55 - 1,75 ).l m ) an d ban d 7 (2. 0X- 2.3 5 pm ). The 1.55 - 1.75 urn middle -infrurcd band has consiste ntly de mon strated a sensitivity to ca nopy moistu re content. For exam ple. Pierce et al. ( 1990 ) found that this band and vegetat ion indices produced usin g it were corre lated with canopy wa ter stress in coni ferous forests. Much ofthe water in a plant is 10 51 via transpiration . Tranoccurs as the Sun warms the water insidc the leaf ca usi ng some ufthc water to cha nge its stare to water vapo r that escapes through the stomata. Th e follow ing arc seve ral importam funcuons that tra nspi rat ion performs:
,lp ,,.lIf;OI/
aer is a good abso rbe r o f middle-in frare d e nergy. so the tel' the turg idit y of the leav es. the lowe r t he mid dleiIated refle ctance . Co nve rse ly. as the mo isture co ntent o f es decreases. reflecta nce in the middle-infrare d region mascs substanually. As the amoun t n fp lant .... ater 10 the ellular air spaces decreases. this causes the incident delle-infrared energy 10 be more ink-nse ly sca tte red at the -=rface of the iruerccllulur walls resulung in greater m id-infrarcd reflectance from the leaf. FlO I' exa mple. consider spectral reflectan ce o f Magnolia leaf samples at Iivc difMOl moisture co ndiuon.. displayed over the wav elength 31from 004 :!.5 um (fig ure 11-7 ). The m iddle- infrawavelength interv al, from abou t 1.5 - L k pm and from - 2.3 urn appear to be mo re sen~it i\ e to cha nges in the . ture comcr uof the pla ms than the visible o r neur-infra ltd portions of thc spcctnlrn (i.c.• the )'-;I.\is distance lmI'('Cn Ihe spec tml reflel:lancl' I: ll T\ t'S is grealer a ~ Ihe DOislurc r.:u lllenl de c re a ~ e s ) , Also no le lhi.ll su b;,ti.lllti\c JIilIg.::s in the visi b le relleelance Cllr\-'es (0 04 - 0.7 J.I m ) did l:H:gin to appear until thl' pla nt moist ure in tht" I.:a ve s kttased 10 aboul 50 pt::rr.:r.:nt. When the rdati,·c wa ter co nof the p lan t deereases 10 50 percent. a lmost an}' ptlrtion \h(- visibk. nea r- and m iddle- inlrnred reg ions might prowme \ a lua111e spectral re nl'Cta nr.:e infonn alioll .
II cool s the inside o f the leaf because the escaping water
\ apor coutams heal . 11 keeps water !lowing up from the root s, throug h the stem. tothe leav es. II ensures a steady supply of d issolved m inera ls from the MliI. As molec ules of wa ter vapor at the top of the lea f in the tree arc lost to trans pirat ion. thc l'm ire colu mn of wat er is pulled upwa rd. Planls lose a r.:o nsidr.: rable amou nl o f waleI' thro ugh transp irat ion ear.: h day. For ex ample. a sing le com p lant ca n I\lse aboul ..j. quarts (3. X lilers) o f wate r on a very hot day. If the roots o f Ihe plant ea unot replar.: e this water. the l ea \ ~s w ilt. photosynt hesis stops . and the plant d ies. T hu,>. mo nitoring the m,. islure con ten t of plant canopies. which is co rrelated with r.tll'S of transp iratio n. r.:an pro vide \ alu ab le in lonnalion on the health of a crop or sta nd of vcgl'tatio n. Therma l infnt rcd and passi \e m icmwa\ c remote S(' nsing
11
366
Rem ot e Sen sing 01 Vegetation
Spectral Effects or Progressive Lear Or) illg
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Wavelength. um Figu re 1t -7
Reflectance l\.- :;pOI1\...• of H ~ingJ.: magnohalcaf ( Mugnofi
have pmvidc-d va luable plan t ca nopy eva potranxp jrat jon
infonna tion. The IUt'S! practical applica tion o f plant mois ture mforrnation is the regional asscssm..' llt o f cro p water co nditions for irri gat ion sch e-duling . stress assessmen t. a nd y ield mod e ling for ag ric ult ure. rangeland, and fore:st!) manage ment.
Adv anced , '('I:t't:llion Sp('clra l Rcncctanee C ha rac le r islics: t he It ldlrcct jon a l Hdleclanl't' Dlstrtbuucn Functlun ( Il RHF) It would he wonderful i f a vcg vtatcd canopy suc h as a mature com crop or Loblolly pine plan tat io n reflected the sam e amount of radiant flux to wani the senso r irrespect ive Ill' I ) the solar incide nce and uznnu th ang les, Dr 2 ) thc sensor viewing geo metry , Th is wou ld ntcan tha t the vege tated can 0ry was a true Larnbcnian surface. i.e.. it reflec ts incide nt energy eq ually well in a ll directions. Un fortuna tely, considcrublc rcscurch has demonstrated that this is not the case (e.g., Kimes . 1')1\) ). tn fact, the: spectral radiantn ux leav ing a veg etation can op y is si~mi ficamly imp act ed by a nu mbe r of factors. man y of wh ich are listed in Table 11-1. We briefl y d iscuss the primary vegetation pa rll met c~ and then delve more de ep ly imu Sun illumina tion and sensor syste m geometric chaructcnsncs.
The: amoun t and spectral distribution o f mdianr Ilux leaving a veg etated ca nopy is influ ence d by the t)'f'C o f ve getation
tIle_
presen t. Fur example , grasses ho pefully re flect ~ Iifcrcmly th an a matu re stan d of trees. Some vegetated ~ pies heve 100 percent C{/ llllp.l · clasurr meaning thal lll: understory and soil be neat h arc n OI visible through. !hee. t' PY. l"ol1\cn;cly. some canopies have < HIO percent camr. closure. allow ing portions o f the un dervtory and or soilI re flect ene rgy into the ins tantaneous field of view (IFO\i)li/ the senso r, cre ating a hybrid o r mi xed pixel. It is po,si~I:'lI d isenlang le the -pcctrat con mhu uon fro m the indiv'idllll land covers. but it requ ires co nsi derable image proces>ing e xpertise. Some vegctnuon is oriented randomly. while ot her wgeution is o ften syste matic all y arr anged in row s in a c ~rdin!l dir ection ( O - 36 0"). Indi v idua l tree cro wns o ften halt unique shape s (c.g .. a conic alPonderosa pine crown or citeuler Blackja ck oak cro w n) with unique tree crown diameters that ma y be mcacured. Tree: trun ks or plant stems ha\~1 cert a in de ns ity (c. g.. numbe r I l l' trunk s per uni t area! lIift uniq ue diumeter-at-b tvust-ltvight (D BH ) values.
Lca(-m n l·imk'.\ (L A I) is th... total o nc-sid cd (or one balfd the tota l all- sid ed } green tea r area per un u gro und-surfxe area. It is a n important hio logical para meter beca use )) f defines the area that interacts w ith so lar radia tion and prt'" \ ide s m uch of the re mote se nsi ng signa l. an d .2 ) it is the >Itfa ce that is res ponsible fur ca rbo n absorpt ion and e, cllanrw ithin the atmosphere (Chen and Black. 199.2). Some ceepi cs hav e subs ta ntially higher lent-area-indic es than Olhm.
I Charact eri stics
at Vege ta tio n
367
Sensor
o ..j , ,-
O S~
•it'
'ii' if
0
Iii
o
..
o
". +75&
_
I-'e11-8
+01 5"
backward scattering view
The bidsrecuona l reflec tance dli:c t 00 • field of I).:gfas", (Lt..Jium pell'nJw L. 1.~~'<1 umk..r dim..rl·nt \'icwing an g l~'S in the solar principal plane from a n GO S mounted camera. Solar zenith angl ... was at 35" as indicated by tho: dashed arrows. The sensor \ n:\t ing angl~ are ~hown as black lines at nad ir (0') and at =~5' and ::!} 5° otT·lll'Idlr(atk'rSandffil"icr and luen, IQW ).
:k
irontal plane (c.g., plan oph ilc leaves in many broadlcaf
s]. while others arc oriented vertically k .g .. ercct ophile
of coastal cordgrass marsh 1,
of these vegetation factors can have a significant impa ct
k reflection o f incid ent lig ht toward th e sensor sys tem.
reforc. it is bes t to ho ld as many of them a . constant as
>INc when atte mpting to extract bioph ysical information
ras primary produ ctivity Of biomass usi ng multiple d ates ( mute sensor dura. Even if we held these variables as sam 3~ pos sible, the zenith and azimuth angles o f the dem solar radiat ion and the azimuth and Ilk-wing lingle l( sensor sys tem can introduce sud! dramatic effects that Day not be nblc to compa re our spec tral reflectance menmcnrs obtained at on e tim e with those o f a nother, FonuIy. if we know n gr eat deal abou t the veget ation actcrisrics of the ca no py (ju st d iscu ssed) and obtain einformation abo ut the bidi rect io na l reflectanc e chaructics ofth c solar angle-of-Incidence a nd the se nsor viewgeometry. it is poss ible to calib rate the remote senso r to extract useful biophysical info rma tion.
rectlonal Reflectance ni~trihll l illn Fun cuon OF): Earl)' measurements u f hid irecuona l refle cta nce bed over vario us vegetation and soil s urfaces ..le moned that mo st terres trial surfaces ex hibit non-Larnbenian IOlropic) re fl ec tan ce cbar acrcris ucs (K imcs, 1983), In Ill.'il. bidirect ional reflectance effects of the land sur face
did not pia) a maj or role in global chang e and ecologic al ana lysis, although they are ass u med to be crucial for mu ltitemporal studies with varying Sun incid ence ang les. Thi s was mai nly due to a lac k of bidirccnonal data avail able from remote se nso rs or acquired in fie ld campaigns . The impact o f the bidirectiona l re flectance d istribu tion funct io n is st ill not well und erstood desp ite the fact thai we know it e xists in mu ch o fthe remotely sense d data co mmon ly used for Earth obs erv atio n. especially for SC INI~ w ith large fiel ds ofview such a s the ?\OAA AVII RR t.l x 1.1 km da ta , A gre at amou nt of data fro m Sl'n son with off-n adi r vie w ing capa bi lity is becoming a vaila ble. especially From comme rc ial Slltellite s such as Space Imag ing 's IKO?\OS, and NASA's u:1'1Yl MO D IS and ~l l Sf{ (C hapter 7 ). To prop erly app ly these dat a in lund-usc change and ecolog ically relevant studies, the BRDF sho uld be wel l understood to ca librate the data t w elte r-Shea and Hichl. [I)l)n; Ahuelgnsim er al.. ll)lJl'). Mos t terrain surfaces (soi l. veg etation. a nd even wate r} revea l a relat ionship between the am ount of re fle cted radiance . and I ) the geometric characteristics ofthe Sun's irradianee, and 2 ) the sens or viewing geomet ry, Hence the term bidirrcttonal. Dep end ing upon the speci fic irm dian cc and sensor viewing ang les. mos t sur faces ap pear brighter or da rker. We ha ve all witncsse d this e ffect. lf'wc wa lk around a patch of b-'1'3SS or a poo l of deep wa ter, it may appear brighte r or darker de pending upo n our vie w in~ ang le- in relation to the co nst ant iucidcm ang le of the Sun, For exam p le, Figure I I-X depicts a portion o f a rye gra ss lawn (LAIi" ", perenne L ) illumin ated by sunlig ht w ith a co nstant so lar ze nith ang le of J 5 ~ , Ind iv idual photographs of the same
CII \PH'N
368
Tabl e 11·1.
11
Spo
Rem ot e sensin g o f Vegetatioll
\1 J.j ur varia bles al1i:, ting the bidirectional Telk e lance distribution func tion ( I-I RDF) of J. Hgctmc"tl
canupy.
Variab les Aff ecting Bidi recti onal Refl ectan ce f rom a Vegetated Canopy lIlumi nal i" n
• Geometry
• Sun angle cfmcidencc ior RADAR) - azimuth • Spec tral characteristic» ( ), j • G
_angkof \'iew [e.g .. 0 ° nadir] • azim uth loo k direc tion (0 _ 3(>0°) • Spectra l SeTlsilh-ity O. l ' IFO V (m ilhr.l<.hans l
.'
• Ca nopy - ()ire
(pl:mt or tree nominal ' lass)
• clos ure (%) • orientation - systematic (c.g .• rows 0 _ J(i O"j • unsystematic (rando m ) • Crown • shape te.g.. circular. con ica l) • d ia met er {ro l • Tron L or Sian
- density ( uni b per 011) diamctcr.ur-breasr-hcight (DAHl • Lear
R gure 11·9
A hot , p,,1 ncar the k li 1i,lud ,1! mark 011 a 1(llQ aerial I'hu(ograph of Ih.. . Savan nah River ~W illl\P South Carolina, The t'vprcvs- Fupelo f"r,"led ~ kutd ha' rdati\ dy uniform p<: rc.'rll cllIlI'JIl c in thi-, area Ill' tone and texture should I ppeliIlllI tivcly hon~eIK"lU~. but th~~ do not. A Ike I\lll produ•.ed when the anglc of illurmnatton and \ ,..:wing angle arc nearly itil•mtical andm W plane
• 1r«
-fcaf-arca -indc x ( LAI ) - leat-angh..-disuibu uon (LAO) [pla nophilc, erectop htlc )
same- as veg etat ion
s"u
• T':\ I"",
• Color • Moisture con tent
grass canopy arc obta ined at nadi r ( O ~ ) a nd at '::'4 5° and ~75 ~ o ff- nadir (Sa nd mc ier and ln cn , ]IN '1), The terrain is genetall y brighter wh en the sensor records bac k-sca n cred ene rgy as opposed to Iorward-scancrc-d energy as the d iagra m rev eals u.e.. the image o n the le li prod uced b)' the -75° back-scattered energy appears 10 he: the: br igh tes t!. No te. howev.. . r. tha t the +75" an d _75° images are ho th much brighter than the image acqui red at nadi r. n°. The bid irect ional effect in remote sens ing data is most obv io us wh en the ang le o f illum inatio n and sensor vie wing ang le are nearly idenuca t and III the sa me plane. Thi s can prod uce a hul spos ( Lc., a shado w is nol visible]. The solar principal plane is formed when the sou rce. target . and the sensor a re in the same plane (in the sola r az imuth a ngle). Th is is where the
BRDF e ffects arc I1W, t pronounced. A n example of a bvl SpOI in ae ria l photograph y is shown in Fig ur.... [ [.11.
Fort unatel y, scientists have dC\e111p...d instru me nts to IIlQsu re the bidirect ional rctlectance d il'trihutinn runctiocl van ous surfaces . O ne or the most u.....ful insuumcms }!fJ/lio" u ·f.'r . Here we brie fly rev iew the tiel d goniornclll sys tem (FU iOS) dcsign....d by S . Sa ndrn eier. FI( iOS cons o fa compmcr-comrollc d GER 3700 specrrora diomcrer ~ sittvc tothe wa velength imcrvn! from 300 - 2 ,4~ O nm in 71~ band s with a spectral resolut ion l\f 1.5 nm [or the inlervl! 30n - 1.0 5f1 nm and K.4 IUn for the interva l 1.050 2A:;l nm . It consists of three major parts: a zenith arc rail. an ill' muth rail. and a motorized sled \\ here the radinmdef mounted (F ig.urc 11- IOa. h ). The a lum inu m goniOOlCUl we ighs a pproxim ate ly 230 kg and may be transported fie ld si tes as show n. Mount ed o n the goniometer. the '
is.
Thus. it i\ possible in a very short period orrime while lit Sun is a ppr oximaret y in the S3ITH.' zenit h are ( 0,1and virmlll ,~ ), 10 vary the posiuon of' the rad io mete r 10 determine ifik amount o f rad ian t flux in \..:t') sp... citie wavelength regioos
.• ( ' 11 \ }' I
370
te.g.. blue. gree n. red. ncar-infrared. middle -infrared ) lcaving the target is intluc nccd by the senso r angle-of-view ( B, )
t:I{
11
-I V/F(O·O ,'I , . " '9" ... qI~,A
and azimu th (9', ). I r it is nol o thc n we do II nl have 10 worry
abou t UROF effects. If the reflectance results arc not unifonn as wi ll he demonstrated, then we may need 10 conce rn ourselves with allj u~ling for BRDF effec ts i f we want to compare rO:II1II10: sensor data obtained on multiple dates (\00 ith varyi ng Sun azmuuh and zenit h angle ) or by se nsors with multiple 1( 0 ),; ang les te.g.• S POT da ta acq uired at 0" nad ir on
day 1 and
20 ~
olT-nad ir on day 2).
T he tndirectional reflectancr dl~fnhlllif}n Jimaio'l I"R DFl. f,. IS(I ). is formally defined as the ratio uf the radiance dl., (\\.' m'! S( I nm"] reflected in one direction C8,~,1 to the Sun 's inc ident irradiance .1/:,', (\\' m '~ nm-I ) from direction (O,.rp,J [Sandmcicr. 1999 ; Sandmcicr and Inen. 1999): . .).. . JL~( O,. '9,;0... '9,:)..) f~(O " '9,.0.. 1+1,. I dE ;( 0,. '9,•• .) ) .
(11-6)
Note tha t clL, and ,If; an: directional q uant ities measured in solid angle st..-raJ ians (sf I ) as sho w n in Figu rc 11-101.'. Normally. a bidirecnonal reflectance factor (HRF. a bo referred to as R) is computed . whic h is the radiance dL, reflected fro m a surface in a specific direction div ided by the radiance dl....,. re flec ted from a loslo- k~s La mbertian reference panel measured under ide ntical illumination geometry tSa ndrnc icr and tue n. lIJ1N ): (11-7)
where R,,/ is OJ ca libration coe fficient determ ined ror the spect ral refle ctanc e pane l. Hidircctionul reflectance Factors (BR F) are d imen sion less. Both HRF and BRIJF take on va l, lies Irom zero lO inlin ily, Va llies > I fo r 13RF and > l in for BRDr arc ob la ined in pcak rc llel'l:111ce directions. such as the hot spnt. where th... rcl1ect ed flux from a ta rge t surface is h igher thallt he I1l1_' fwm il La mberti an sur face.
11 is als o possihle to de n ' lop an (/IIj\'o/ll lflrfacror, v.hkh is used to analy/ e Ihe spc o.:t ra l vari abi lity ;n BRD F uata. An iMltmpy f;lo.:tors (A:-.l IF) all" ....' s... par,u illn of speclml RRD F effects trGrn the .~ pectra l ..ignat ure o f a targl'\. The)' are calcul:lted hy 1l110l1alil.ing bidirectional rd l cc ta nce data R to nad ir re ncc tance. R.. (Sandmei.::r ct al.. 1991!a: Sand meier an d Itt.:n. I'}(}l)j:
Remote Sen sing 01 VegetatlOll
·
R(O tt . -e ,n ·A.I " ....,. ,. ....,. R (0 'AI
(I
" " '9"
So what do thcs e mea..urcmcms tell us about the BRDF typica l ..urface? To answer this question. consider the normali rc-d ORDF data (i.e .• the AN IF data ) of pertUl f)cgrass (l.olillnl perrnnc L) shown in Fig-ure 11·1Od. ing goniometer data collection the Sun zenith angle \\a:;' Spectra l results from ju"t four of th c 704 spectrcrad. bands arc presented using just the viewing zenith a.1p the solar princ ipa l plane . It reveals that BRDF etfects very pronounce d in the blue (4!'lO nm) and red (6-5 chlo rophyll absorption ban ds previously discussed. w in the green and particularly in the- low absorb ing Ilea!" feu range, relauvcly low ORD!' effects were observed persons using remote sensor da ta might consider rad cally adjusting: th~' brighrnevv valu es assoc iated ",ith the and red bands, hut not necessarily the nea r-infrared under invcsriganon. Typical for vegetated surfaces. 111 iw hands exhibit a how l shape. hot spt)t, and forward-
component.
It is even more in ter~ting to view the ry... grass ani, facum, for the Iour w avclcngths of interes t according to only the viewi ng zenith angle of 00 but in a range from:.', ( Figun' I I-II ). Ideally. the enure three-dimensional ,urin sho uld be relatively n at ;I" '" ith the 750
nm near-infl1l!r.
example. meaning th..t meas ure ments in this specific ball arc relatively free of HRIJ F effec ts. Conversely, the ~80 . and 675 nrn ban ds exhibit significaru anis otropy factors. II the h i g h . ;I h ~ (lr h ing tl.c.. low-reflecting! wavelength ra~ mu ltiple scancnng enects arc reduced due to the relativell10 \\ uuunnn o f rad iation in the canopy. TIIUS, the (ontl'l!lt between shndow cd and illuminated canopy co mponenu se en hance d. which then en hances the BRDf effects. BRDf effects arc rather sma ll in rbc low-absorbing (i.c., highre fle cting] gree n and ncnr-iu trarcd wa ve length rang es whm multiple scattering effects are strong and d iminish the ca. tra ~t in lhe o.:
I·ulure fie ld re ~e
371
Speclral Chara ct eri stics of Ve getation
')
a r-
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rr n
e
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"
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-. e. Figure 11 -11 Anisotropy factors (nadir-normalized flRDF dala ) of ryegrass (/.uli"", ("'N'fIIU'I.. ) fur f"UTspectral band, acquired with the l'I( iOS instrume nt wnf a Sun , ...nuh angle of 350 (atk r Sandmei er and Inen. I'I'N).
One should he care ful not to infe r that Bf{[)F eff ects a rc all hod, Qi et a]. ( 19tj 5 j point our that mult idirectional remote easing me asu re ments ofthe terrain (e.g.. al view illg ang les off.nadir) ca n provide comp lementary info rmation to that ;'l'O\'ided by the nad ir measurem en t. In fact, a sing le nad ir \1(11 remote sensing measurement obtains in formatio n eout the surface 3 S if the surface had no ve rtica l struc tures, ehich is usua lly nor the case in practice , w hile off -nadir \icw measurements reveal diffe rent aspec ts of the ve rtica l eucrurcs such as vegetation he ight. Consequently: /(J objecIMly charocteri: e vegetanon hlOphysteat parameters. axinte \'iewi tl~ ~t'(} ltwt,.y te.g., at " ", Jir} mav be ifl.m[ficient.
:\l mlcling Canop y Refl ectance Scientists hav e attempted 10 predic t e xactly how much radian I energy in speci fic ..... nvclcng ths should he e xiting a given leaf or vege tated ca nopy based on a numher of factors . inclu d ing (Danson. 11191\ ): the le af -urea-ind ex (L A !), soi l re flect ance prope rties be low the canopy, amount of d irect and/or d iffuse skylight onto the canopy, th e lcaf-an gle-dis tribu uon (ranging from erer tophile ca nop ies w ith vert ica l leav es at 90 0 inc lination to plano phile ca no pies do minated by horizonta l leaves ....ith 0" incl ination), and the RRDF intlu cnced by the- S un an gle and sen sor vie w ing angle geomell)' just discu ssed . For e xam ple. the S A IL model {Scattering. by Artntran ly Inclined Lea ves ! has been w idely used in re mote sensi ng rese arch for investigating the spectral and d irectiona l re flec tance properties o f vege tauon canopies. II
11
372
uses radia tive trans fer equa tions 10 mood en ergy interac ting wit h a veg etation canopy in three d ist inct streams. includ ing a downward Il ux o f dir...ct rad iati on and a dow nwa rd and upward nu x of d i!fuse radia tion. [I ass umes thai the canopy may be rep resen ted hy sma ll abso rbing a nd scattering etcme nte (e.g .• leaves } w ith known op tical prope rties . d istrib utcd randomly in ho riLonw l 1a)crs and w ith kno wn angu lar dis tribution. The model has been used 10 simulate the effec ts of otT-nadir viewing. to simulate spectral shills orthe red edge. and 10 estimate canopy properties directly from re motely sensed data.
Similarly. the Li-Strahlcr model (1985. 199~) yie lds cstimates of the size and de nsity of rrecs from remotely se nse d images. The signal received by the sensor is modeled as consbting of reflected light from tree cro w ns, the ir shadows. and the backgroun d .... ithin the fie ld o f vie w of the sensor. Tho: reflec ted si~nal i.. modeled
Rem ot e Sensing of Vegetation
lrnuging spe ct rometry 11<1-' gr<:a l potential for moniliXll! veget al ion lypt.' and b iop hysica l c haract eristics (Goi:tt 199;). Vegcnuion re fle ctanc e spectra are ofte n qune inrl! mauv e. cont aining information on the vegetation chkno phy ll absorption bands in the \ isihle reg ion. the SUstalM h igh reflectance in the ncar-infrared reg ion. and the df~ orplaru wa ter abso rption in the middle-infrared region. Geolog ists have been using hypcrs pcc uul ima pcry for:-m to d iscr imi nate between different rock I>pes based ontbci spectral renec tance and absorptio n characteristics. Tlr!' have prepared all c....hausuc e spec tra l library of 1M important minerals, soils, an d rock t) pes t e.g.. Clan l.'lIl .21)(13), When calibrated aubome hypcrspec rral imagt'f);It acquired. the) oft en compare lh..: spec tra obta in..-d from it airt-om..: data ttl the spec tra stored in Ihe database to deler· mint' mine ral type and ot her c harartcrisrics. Several l.''<» ple, arc PUl\ ideJ in Cha prcr I ~ I Remote Se nsing of Stit Mine rals and Geomorphology]. Ideally. there would be a veget ation spectral databa nk 31m. able thai con tains in formation on : I I the spectral relk'CWl.'t and em itta nce c haracterisncs (>1'every tYf'< o f \egcl3tiooill tho: regum from 0.35 1.4 u rn. 1 ) how these data appearlK differe nt dal es throughout lh.: pcn inen t gro wing seasce, and .' 1 what these spec tra should look like in the cI'ent of sires.. or insect infestation. Un fortunately. suc h a daLll:m:: docs nOI yet e\ist, Inste ad , it is Mill usua lly necessary to colICCI ;" ., ;1/1 ' pt.'clro rad itlml't.: r J al a of rhe \eg<,talion of inter, est ut the time of the ove rflig ht and the n usc this Wt3lO cuhbnnc the spect ra l re fl ectanc e information derived frOl'll t h~' airhome sr el-troradio lO\·te r. "" hcn this is performed ca rd'ull}. il is pl.lssiblc 10 ..:x tra~'l \'cgeial illll typ..: and condi· lion in ltlrnmlioll fro m Ih\' hypcr~l'erlr~l l d;lla. F Ill C\lll11pk. cIJllsidcr lhe A\"IRIS dal;r co l1c.:tcd o\ er thl S;il1 Luis Va[k y of Color;rdo on Sl'rlL'il1h~'r 3. I (jI) J , shol\n in l 'nlnr Plat~' I [-2a (Cl ark t:' t at., 111(5). Th .: 224 ,~etral ch unnds o f 20 x 20 III " VIR IS data wcr e r;"ji nlllelrkally Ctl lTecl~ d 10 fl'1110V': th.: d"ee l~ n f atm osp heric wal er vap« and gco l11~tr ic al ly n:cli!;el[ III a sl;lndard map projcrlion. lJ. nd em 'er Ilf snm c oflhe Helds al l h~ ti me oflhc m erl1lgl1 arr annlllaTcd in col or tlll to p Of lh~ single r\ VIRIS channel ill r o lor Phne 11-2a, i\ V1RIS re l1el:lance "I~ctra for stlmeof Ihcsc fi dJ ~_ ind uJ ing ptlta lo. a ll~ lfa _ ba rley. O
The a lfalfa , can'lla. oa t h3) . and S uggel potato sJ)ectra ~ the plallls 10 b<.' gree n and h..:a lthy t Figufl' 11·12a). Barle:' had Inst all of ih c hl\lrnrh~ 11 re';pI.'nse al the time of the o\'l: rl1ight (Figurc ll- 11bl. ~tlrkot.1h potatocs were not b<.'ing irrig all-d as they \wrl' aholll to Ix' har.o:sled. and COl-
373
I Cha racteristics 01 Ve geta t io n
bare field
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11·12 al Spectra of healthy g l"(1..'11 vegetation in th<." SJ n Luis Valle) of Colo rado obtain..-d on Scplelllo..-r J. I')'13. using AVI RIS; ~~ -l channels at ~ O )( 10 m ph,ds. b) \-lost of IJ1<:l.c' "Ih~..,. vegetation t)~ c xhit-ilcd r.."dIK<."<.1 chlorophyll allwrpt i"n effects. Note lboll lhe spectra are 011'-':1 h..-c1an t) (alter Clark ct al.. 1')
ruly the), show w eak Chlorophyll and cel lulose ahsorpwith soil (clay) absorpnon from e xpo sed s.;1I1. Field rgano n revealed that the puL1IOCS \\ L'I""- also being JlQiOO with a de folia nt. Thus. the)' e xhibit decre ased chlo)'11 abso rptio n along w ith a shift of thc red-ellgl· til Mer wavelengths as we wou ld expect. The Chic o and pa st spectra exhibit combinations o f chlorophyll and ccltu(dry veget ati on ) absorpt ion . The spectra from the n fields w as USL'tI in a special com putcr program called h urd,·r. dc, eloped at the U.S. Geologi cal Survey . to iden~ other pixels in the study area with simi lar spectral 'flilllnsr (Clark ct al., 1( 95). Th e result was a clussificurion "lap that was approximately 96 per cent accurate ((' oIM 11-2b). ..' I al. ( 199 5 ) poi nt out tha t the long -wavelen gth side o f chloroph yll absorption [approxima tely (I,oX - 0.73 ~m ) RlIms on... of rhc most extreme slopes fou nd in spectra til' ~lUfally occurring co mmon mal ... n'l ls , The ahsnrpTion is II)' very intense. ranging from a lo w relllX'tance o f < 5 ~nt (near O.6R ~m) to a ncar· infrared re flec lan..·e m3xi · ~ of ::: 50 percent (at approx ima tely 0.73 ~ml . Wh~ the rophyll absorption in the p lllm dec reases. th... ove rall .'iJrh of til.... absorplion ban d d"creases. Tll...s... facturs eause Ilhift to shorter wlIvcle ngl hs as Ih..· "'hlorophyl l ahsnrptinn meases. This is known as the " red --cllge sh iti'" or the "b lue 'ft of the I'l"d edge" pr~"\ iou sly discusS<,.-d and can Ix: caused
by natura l ....... nescence. water d c privation. or tox ic materials. Clar k et al. 11(95 ) fou nd that thc ,\ VIRIS data could dercc·t red -edge shirts o f < 0 . 1 nm . The red -ed ge shi ft information was analyzed llsinl: the I ricorder program and used (0 id....ntify \ cgctaucn und c tg oi n~ an y ty pe of stres s in the study urea (('olor PialI.' 11 · 2e ).
Temporal Characteri stics of Vege tation
Tim ing is very important \\ hen aucmpting to idenlify d iffer em veg....tanon types clr 10 cxtract use ful vegeta tio n biophysical informa tion te.g .. biomass. ch lorop hyll characrenstics j from rem..'tely sensed data . S....lccnng the mosl appropriate datL'iS) for dna ccllccrion requ ires an inti mate know ledge of lhl' plants' tem po ral I'IWllofogicflf (gmwlhl cycle. Plants \.\ hose leave .. drop seasonally Uri.' deciduous. Plants whose k a\"....s rema in from sea son to sca~\Jll are ('I Ylglt't'lI . A ntllt"d remot.... st"nsin g ......il;"llIist. [)a\ S imonett. o ft.... n sa id " Green is gn.:e n is ~recll. " B)' thi s he m an tthat iftwo different L' rops /L'.g.• com and collon) were plant J m the slim .... time and had complele callilpy eklsur IJll lh sallW date as the rellllllcl y sc nsed dula were co lkcl d . t he spe"'1ral rctlectan..-c eham..· trrist ics o f Ihe IWO crop'" woul d mosl likely
374
appea r to be very simi lar throug hout the visible and ncarinfrared port ion of the spectru m. His commen t was based on tho: U~ of the rel ati vely broadba nd sensors ava ilable in the 1970 5 and I ()gOs. We no w have hypc rspcctral sensors that allo w us to samp le in re latively n a IT OW portions of the spectrum. hopefully ident ifying unique abso rption featu res tha t will allow us to discri minate betwee n one vege tation type and another or 10 extract biophys ical inform at ion.
C H A PT ER
t 100
11
Remote Sensi ng of
Cl' lIlnJ Va lle)' Californ ia
~ 75
Vegetalio~
xcreb Central
1',";~ ''"''' 50 ~
] 50 :... 25
25
J F MA \ IJ
J FMA MJ IASOND
Nevcrthclc-ss, Si moncu 's observation is still correct in man y instances. Often our on ly hope of disc riminat ing between 1.....0 crops using relat ively co arse spec tra l resolut ion rem ote
J A S O~
[ :n ltrn
lE1 ;~
sensor tina (e.g.. Landsat Thematic Mapper, SPOT. l KOl\;QSI is ifthc cro ps were :
25
planted at slightly different times in the growing season Ie.g.• 10 days apa rt), .....hic h caused o ne canopy tn l'IC tes s develo ped (lo we r pe rce nt ca nop y cl osure ) than the othe r; on e cro p rec eived sig ni ficantly different irrigation than the other. ca using it to prod uce more or less biom ass ; one crop mat ured mo re rap idly than the othe r (e .g.• throu gh fcniliza uon o r care ful weeding ]: the row spacing or field o rientatio n w as dramatically diff erem fo r the t w o crops; or on e crop has a d ifferent canopy struc ture. The differen ce in crop pe rcent ca nopy clo sure . so il moi stur e, biomass. or the differen ce in row spacing or orientation might cause on e crop 10 ha ve d ramat ically di fferent re flecranee properties due to the influence of the background soil or understory materials present. Therefore. it is often the proportion of hac kg ruund material present within the instantancous field ofview ofthe sensor system (c.g.. perh aps I x I It for high reso lution co lor- in fra red aer ial ph otography: 30 x 30 IT\ for Landsat Thema tic Ma ppe r imagery ) that allow s us 10 di scr imin ate betwe en the two vegetatio n types. The amount of und erstory backgroun d material present is largely a function of the stllge o f rhc plant in its phe no logica l cycle. Therefore , if a scie ntist is try ing to differentiate (classify ) betw ee n several crops. wetland. or fo rest types usin g remote sen sor da ta. it is essc nua l to kno w the phenolog ical cycle characteristics o f all o f them . This in fc rma uc n is then use d to dete rmin e the opti mum time of yea r to co llect the re motely sense d data to dis criminate o ne lan d co ver or ve getatio n l)-PC fro m another. Anot her important te mporal factor ca nnot be o verlooked. Plant s req uire ....arcr to gro w, Th ere fore . the ir most prod uc-
J FM AM J J .... SOl'O
JFM A \l J J A , O~
Figu re 11·13 Predicted percent cloud cover in four arnsiD. Unne-d Sta tes. TIle greatest amount of cloud ct'I1:I is flflen a~..octated with the: heigbr of the plIf season. except for California. This can signi~ wmplic:ale: the: collection of remote sensill~ data ir ve:ge:llIliun analysis.
tive growth pe riod is oft en ass oci ated wuh the most inte!llt periods of prec ipitation and ass oci ated cloud cove. Fa example, Figu re 11- 13 ide nti ti es the annual percent clNl cover statistics for seve ral areas in the United States. E~~ for Cal ifornia, w ith its low humid ity and low cloud coce most o f the areas have thei r greatest cloud cover at eu,,'1ljthe time when sci ent ists may want to collect the maxune amoun t o f remote se nsor data during the growing Sl'a500. Consequently. scientists mu st jug gle the identi fication ofthf optimum date of remote sensor d ata using the phenologicl calendar with the likely spec tre of co nsiderable cloud COle! be ing present This is wh y w e need h ighe r temporal rescu rion sensors. T he dev e lopment o f'tore sts, gra ss land . and wetland canopies folio,," relatively pred icta ble cycles each year except .... he; they are und er stres s from a pa thogen or w hen un seasooab~ high or low temperatures occ ur. S imilarly. all managed agricu ltura l crops ha n ' rel at ively well-kno wn phenologies cyc les w ithi n a gi ven region , bu r these ma y be modified b indiv idua l farm ers . Th e refore. it is usefu l 10 re view the phfnologica l cy cles (If bo th natural vege talion systems ani ma naged agri cu ltural sys tems to gain insight into 1m impo rtant the cycl es are when using remote sensing III ex tra ct ve gerarion biophysical info rmatio n. Several casc studies are pro vided .
)
375
poral Cha rac te ris t ics of Vege tatio n
~raJ
Phenological Cyc les
Smoot h C " r cl l-:rlIs s (Sportina altvmiflorav ISOO
. plan! species found in Iorcsrs , \\ etland, ran gela nd. .jave relatively e mquc phenological growth cycles. leaf-out. grow to maturity, and senesce at approxil~ the same time each year. Howe ver, unsea son ab ly er wcrrn tempe ratu res in the spring or 1'311 can shi ft thei r I phenological cycle'S by as much as thirty days, Therethe analyst must be aware of whether the remotely data were col lected in 3 typ ical or atypical year. If a is! is attempting 10 classify \ l1!l'lation using remote data. it is often wise 10 collect the data early in the ing season "hen the vegctanon are developing at di f; t rates. which yield different percent canopy closures. fully creating diffe rences in thei r spcctna 1 signatures. tumple, if one is attem pting to discriminate among varinland wetland species (e.g.. cattail. "illo", burton.l in the southeastern United Stares. it is bes t to collect •• from February IS through May I. After May l , of the wetland vegetauon has achieved com plete can.-closure.and the spectral sigJlat urC'J. of the various canobecome similar, i.c., "Green is green is green:'
,IlIlmc1y. if the goal is 10 moni tor the biom ass of the veg'on. it is useful to co llect remote sensor dat a at the he ight lhe growing season when the maxim um biomass ex ists. wring biomass through ti me ca n provid e important ormation abo ut the stability of the nat ural ecosystem and \ether ~ ignifiea nt cha nge is taking place. The fo llowi ng eucn demo nstrate s this logic appl ied to mo nito ring coasta l 'moolh Cordgrnss wet land ( Figure 11 · 1..1).
Pbenolugica l Cy cle Il l' SJuth Ca rolin a
('c Hl ~ ta l
S moo th C o r d gr ll\s in
lbe annual phe nologi ca l cy cle o f evergreen Smoot h Iordgrass (5iJl/l"lin
biomass occurs from Ju ly throug h Oct ober. Thi s is k optimum time for remote sl'nsing data collect ion. It laws liulc purpose (0 obtain imagery of the Spartina in Ja nIIIYlhro ugh Marc h. whe n it is in a scncsccd [dorman t ] state. Stlli,one often encou nters pe rso ns who aucm prto U'C winter m1ger)" collected for some ot her purpose to monitor the Sfarril/Il wet land .
-0-- Live biom ass
1250
~~
- 0 - Dea.1 bi'lma'l.~
~
'd
1000
•
§ :::: 750
~ ;.
s
54JO
250
J
F
1.1
A
\t
A
S 0
'\l
0
Figu re 11-14 rh,:nolot;kal,;y,;le of Smooth Cordgrass (Spurt/nu dll"rlI!flnml hirnnass In Sou!h Carolina. The greatest ameura of live biomass is presen t from Jul} through October. Tbe greatest amounl of dead biomas~ is present from Janu.uy through ~' arc h. The marsh conta ins 31'f'roximalely equal proportions of li\ e and dead biomass ill December and June rencr Jcn"-l'TI ct al., 19'-11'1,
Fig ure 11·15 disp lays nine bands o f) x 3 m NASA Ca libratcd Airborne Muhis pcctral Scanner (C AMS) data of Murr ells Inlet, Sf. obtained o n August 2, 11J97 , during the high biomass nmc of year. In situ S moo th Cordgrass tota l dry bioma ss ( g/ m ~ ) measuremen ts were ob tain ed at 271 0e a· uons on A ug.u~t 2 and 3,1997. T he ill situ data we re then corre lated with indi vid ual band brig hruess valuc s and veg etation rranstorrus of the orig inal CA MS data (J ensen er al., [ 991\), Om' of the mus t imp ressive relat ionsh ips was between (he fundamental ncar-infrared band 6 CA MS data and the in situ measurements, wh ich yie lded a correlat ion coe fficie nt of (UIS and an ,-'-valuc o f 0 ,774 meaning thai ap proximatel y 77 percent ofthe vari ance \ HI S ucc uuutcd for ( Figure 11· 10).
Colo r Plate 11-3 is a ma p of the spa tial distributi on oftotal dry biom ass for a small portjon o f Murrel ls Inle t on August 2, 11J1J7. It WIlS produced llsinl!! the reg ression equation; I' =
3.4X9 1.t -23 .9
(11-1 0)
whe n: y is tota l biom ass (glm!) an d .1' is the C' A ~ IS blind 6 " rightness value. Stud ies such as this pro vide impo rtan t baseline biophysical informa tion that can be co mpared against future studies ttl dctem line if dele terious ch anges in
11
376
Cali b rated Air bo r ne Multispectra l Sca n ne r (C AMS) Data
Rem ote Sens in g of Vegetation
or ~Iurr cll s Inl et, SC
Band J (red: 0.60 . O.6ll1m)
Band 4 (rro 0.63 • O,Mll m)
Rand 7 (mld_onfrared:
l.~~
_ 1,75 1J ml
B~n.J
5 (ncar·in fr-~tcd 069 . O.76 ll'n )
Band ~ Imid-infrdred' 2 n~ - 2.l5 I,m)
Band (, Inear-infrarcd: 0.76· OQO l-Im)
Banrl Q Irhermnl-infrared: 104 - 12.5 ).1m )
Figure 11·15 Nine hands of J x J m Cahbrared Airborne Multispectral Scannc e ( CA~1S 1 tlala of \-lurrd ls lnlet. SC obtained on A~UlI ;' 1997. TIle dalil .... ere .. !>tained at 4,000 1\ abo ve ground level.
biomass arc occurri ng in the inlet. Comparative bio mass studies would req uire that most of the system and environmen ial variables remain con stant (c.g.. approxim ately the same sensor system con flgurauon and viewing geo metry. altitude above gro und level. atm ospheric conditions, unni-
versary dale. time of day. a nd tidal cycle j. The limitalioo of using a regression approach w he n predicting biophysici variables using remotely sensed data are summarized in Qi et at (IW5).
T
~ra l
Characteris tics 01Veget ati on
377
110
Y
= JA~Nlx
160
R2
, •j ,
=
0.77
.; lJ1}
• •
120
•
, 100 ~
,, so ~
t 'a
s
60
.,
- - -I
•
"
0 .......
o
10
•
-• .
.,. • • •
rh eo ll l(l~ iC3 1 Cycle of li a r d Red wlnter Whea l in t he 'Iid \\ esl l'nitl'd St a lcs
•
--'
20
30
40
CAr-IS Ban d 0 Ncar-infrared (0.7 0 _ 1I.'1l) ~ ure
County agric ult ural extensio n agents and la nd-grant univc rsi ly scicnnsts know the loca l and regional cro p phenolog ica l cycles very well . T hey oncn represent the most impo rtant sources for valua ble ( W I' phe nology and so ils informatio n a nd any id ios yncrasies ass oc iated w ith loca l fanning practi("cs. lt is instructive 10 provide exam ples ofsevera l agric ultura l phenological cy cles that spa n the geog raphy o f the conte rmi nous Un ited States to de monstrate the importance of \ cgetatiotl phe nolog ica l mtormation. Th is w ill includ e case studies conc c·m ing ha rd red w inte r wheat in the Midwest Unite d Slates. several major crops in South C aro lina. and remot e se nsing of su gar bee ts, cotton. an d al fa lfa in the Impe ria l Valley, CA. Each exam ple includes de tailed phenolog ical mto rmauon displayed in diffe rent forma ts .
• •
- 23 .9
50 ~un )
11-16 Relaricnsbip 1Ic1"-1:1:11 Calib ruted Airborne Multispectral Scanner (CAMS) band 6 brightness values
and in ,~II" measur ement of Sparli"" ulkrni/loru toral Ur)- biomass (J;.im 1) at twen ty-seven locauons in Murrells Inlet. SC obtained on August 2 and J. IIN7 {Jensen ct al., 19')I().
Iianaged Phen ological Cyc les
Crops associated with mechanized forestry ami agri culture Irecstahlished, gro wn. and har ve sted accord ing to rela tively pedictablc phenologica l cycles. It wo uld be wonderful if a lJ t.mers. planted the sa me crop o n exactly the same dat e in a pven growing season . This w ould make the ana lysis (If tlITloldy sensed data straight fo rward. Fortunately for us. ,110 eat the bread o f the ir la bors. they do not do this. but adltr plam the crop base d on c urrent meteorologic al condi. the availability o f equipment, and heurist ic rules of m h. Therefore, nOI all cro ps of the same spec ies are pbnl~d during the same month o r ha rvested during the same eonth. If two identical com crops are plan ted twen ty days lpan, the ir spec tra l signatures will likel y be very d ifferent b'OUghllut the ir respective phenolog ical cycle s . T his co nd i00n may ca use prob lems when attemp ting 10 pe rform c rop ~enlifica lion using remote sen sor data ,
The detailed ph... nolcgical cycle of hard TI:d winter wheal (trific
Cy c le of
.-\~ricu lt u ra l
C ro ps in Stlu th
C a r olina The pheno log ical cycle... o f natural and cu hivated veg etation varie s gre atly by region. Fo r exam ple. ira scie ntist wan ted (0 mo nitor the cond itio n oft he w heat crop in So uth Carolina, it is I/O/ possible to usc the Mrdwe"!>t w heat phenologica l info rmat ion presented in Figure 11-17. Th e phe nolog ical cycles lo r wheat and South Caroli na 's ot her major cas h crops are presented in Fig ures 11 - [S and 11-19.
C H ,\I'T E R
378
11
Remote Sens ing of Vegetation
Ph eno log) or Winl er Wheat
- - - - -
SlO P
DK
Ot:1
linow cover
]A'l'
~.op,..al>I .. hed
'"-11>- 1-- to 14 5o,," t Ttllcnng
---+-
I O ~ d~)' s
14
Dorm ancy
Emc rl1ence
h.ad i"l ......,. l~
14
Grcv•• h Jo ;m ;nl1 resume s
,
,., "
21<
479~
IIca<.h n l/ ROOI Soft
",,--,..._";:"L~--,
Uead
n,.
Ha rd do ugh
dUligh
Figure 11-17 The phcnoillgical c ycle of ha rd red winter wheal in the Grcat Plums of the Unit..-d States. l' he crop is established in Oc~ and November.
n ucs dormant
under snow
,,0\''' ' until ~hrch. when g row th resumes . Th e plerus green Ilr
in April. produu'
head... of grain in May. and mature by mid-JuncoThe wheat is usually dead npc and harvested by early July. Re motely ~ data acquired In Oc tober and Novem ber provide information on the a mount o f la nd prepared during the nor c51ablilohmcrr. period. Irn ~~eT) acquired during the green-up phase in April and 1\1 ~y can 1:>0: used to e~ lfitd infonnauon un standing-crop IlK>mass and perhaps predictthe harvested wheat yield,
Whea t beads in late May and early Ju ne in the Midwest. Wheal heads ill early May in So uth Carolina . ap proximately 15 days ahead ofthe Mid we st phenol ogic al cycle for wheat , pr ima rily du e 10 an ea rl ier and long er Fros t- free gro wing season. Imagery acquired in the Mid west in June mighl be va luable for invento rying whe at produc tio n, wh ereas imagery ob tained in Jun e in South Ca ro lina m ighl well revea l that the whea t crop has a lready been har vested. T he crop cale ndars also rev eal that it should he straightfo rward to ide nt ify whe al production in So uth Ca rolina by acq uiring a sing le image in March or ea rly Ap ril whe n \\ heat is th... only cro p in existe nce with a compler... can opy clo sure. Conversely. il may be difficult to diffe rentiate between tobacco and corn un tcss we ob ta in a m id-J une image and hope thai th... tobacco is jea fed out more than com. resu lting: in a d ifference in spc ctral res ponse. Similarly. it may be po ssible to discrimi nate be twee n soybeans and cotton if a late July Of early August date is selected and soybeans have a greater ca nopy closure tha n cot ton . If all the pheno logical
cycles o r the major C fllP~ we re ex act ly the same for Souu Caro lina. wuh complete canopy clos ure ut rhc same time of ye ar, 11 wou ld he diffl culrro usc remotely sensed d ata t(ldir. crimi nate between the vegetal ion I ) pes. How ever. because thei r phen o logical cycles arc sl;lggc rcd throug ho utthe growing seaso n In som e degree, it is possible In dis criminate between them ifthe imagery is col leered at nptimum times in the growing season (Sa vitsky, 1986). Phl' /luIUl!iclil C )cll' o r Acrieultura l C roj», in t he Imp erial VlIl1e)·, C A
The I mpe ria l Valley o f Cahfomia i.. one of the most ptoductivc agr icult ura l ecosystems in the world, produ cing greer qua ntities of' sugnrbccts. co lton, and a lfatta . The phenolopca l cycles of se veral of its major crops ere summarized ill Color r latl' I I.... (G RSU, 1( 99 ), Each cale ndar dep icts a single field monitored throughout a twelve -mo nt h period using 7
To
'llIlporal Characteristics o f Vegetation
379
Phenological Cycle or Soybeans and Co r n in South Ca r olina
,>- '00'"
~"
/
50
115
/
em height
JA'\'
a.
So~ hn n~
I
f+U
I :'dAR I ,\ 1'1{ I
Dormant or multi-c roppe d
\1 A Y
1000/. ground co ver
5~.
I JU,\ I
I Initial grow th
- jOO
I .\ l lt ; I Sf'.J'
WI
l OC I
=
mc
MlV
Harvest
Mat urity
[) nd "l'n1cnl
I
Cern
hi
\
- 250
-
1--100
I I
100"/.
I-
\
150
f- ,oo
/50%
I-
75
l-
50
r
25 e m heig ht
JA'
I
I'F D
I
MAR
I ,\ r R
Dormant or multi-c ro pped
.: \ 1AY
x-le af
JUN
JUl.
I
-
--
\ ,\l)(j
10 12·\ 4 Tao, le lJI"tcr
leaf
-
I
~E r
Dcntfl lar ..es t
OCT
I
l\C1\ '
I P IT
Dorm ant or multi-cropped
i'lgure 11-18 Phenological cycles of soybeans (al and com (b) in South Carolina (Savitsky. 19&6),
jreater the amou nt of biomass and crop cano py' closu re, Sugarbects are established in early Se ptember. emerge in Xovember, and are harvested in April and early May, B~' !allo', cotto n must be planted in March and harvested and plo.... ed under in .o vember of eac h year to control Bole l\'cn il. In 1982. the plow-down date \\o as January I, Alfalfa
is planted year-round and may be harvested fi..'e or six times per year as dep icted in the crop calendar.
It is poss ible to identify the type ofcrop in each field if imagery is obtained at rimes of the year that maximize the spectral con trast bet w een crops. Fo r example. Figure 11-20
11
3BO
Rem o te Sen sing o f VegelatlO!1
Pbcnolouical C ycle of W heat. Cotton. and Tobacco in Sou t h Ca rolina
----
I~I
~I
W inlt'r Wheal
"
'0 r-
~S
lOO"~
grou nd cover
em ~l l",..
Boolmg
Tillering
Ij~
I\()\
HI
J"
J"
Dormant or m ulu-cro poed
H :l IY e<;I
ISO
b. Catto n
_ l .! ~
l Oll
"
ll)(l""
gm unJ
so
COH'T
2S em height \1,\'1
J\
-
O[C
"'
Sc<:J i n ~
[)" nnanl or m ulli·uoppo.:d
MJ hm l)"harve st
12< -
1\
l Oll
TOblu.eu /
75
H~ J'.
J
'" 2~
em height
J,"
I
lU I
I
\1.\R
Dormant or multi-cropped
\1'R
I
\,lW
,
~ II",
I JLr-. I ,
l'fJllsp)anlinJ;l lk ,
.Il! L
1,,1'
1 c.
-J
\ ,\ l {i
Mil lu rily/h;lf\ C~1
SU'
- ,
0 (1
I
\JlJ\ "
I DEC
I
Dcumur uut muln-cropped
Fig u re 11 -19 Phcn
depicts SCH'n bands of Landsat Thematic Mapper image ry obtai ned on Decembe r 10. II)K2. Six ofthe ha nds are at 30 x 30 m. while thc therm el infrared hand ( h ) is at 120 x 120 m
spatia l resolu tion, " grou nd re ference crop map provided b:the Imperial valley Irrigation Hoard is a lso included (Haarl and Jarnpoler, 1<)'15 1.
parol Cha racte ristics of Ve g e ta tio n
38 1
La nd sat Thematic vlapper Im agery or Imperial "aile)'. c.\. on December 10. 1982
a [land I (tllue: !lAS - 0.51 j.lm)
tI. Band 2 (gr<:en: 0 ,52 - O.M ) J-l m)
d. Band 4 (ncar-in frared : 0.76 ·0.9(1 j.l m ) t Band 5 Imid-infrared: 1.55- 1.75 j.lml
e . Hand J (red: 0.63 - 0 ,69 ).1 m )
f. H3nd 7 (mid -infrar ed : l.Ot! - 1.35 J-lm )
1.(,J:..n d :
SU!!arbcet~
D g na nd (, (mid-i nfrared : 10 ,.\ - 11.S ~lm \
Alfa lfa
I:{:I 0
Colt""
Fall""
Ground re ference information
Fqure 11-20 lndividual bands of Landsat 'Jhematic ~ ' appw imagery of a po rtion of lilt Imperial Valley, CA, ob tain ed oil December JO, J·' S2. Hand, J - .5 a nd 7 haw
( m:ar- iJ1 fl;l r~'dI .
"hich is dark ( images courtesy Space Imaging, tnc.j.
four color co mposites show n in COIM Plate 11-5 dcmte the import a nce of the mid dle-mfrurcd bands whe n piing tu d iscriminate am o ng crop I ~ pes . The fundallr:II131 \ isiblc ( RG B = ha nd;; 3.2.1 ) and nea r-infrared co lor itt's ( RG B = ba nd s 4.3.2 , arc not nearly as e ffect ive \ isual determination of the crop types as the \ is iblc an d je-m frarcd cumpllsit,;-s (RG H = ha nds 5.3.2 and RGH = Unds 7.3.21. :\OIC that all the suga rbcct fields show up as
blac k in th... m iddle -in frared ector co mposite (Co lor Pla te ban ds 5.3.:! ) and in the ind ivid ua l hand 5 1I ·5e: RG B image ( Figu re 11-20). Bec ause o f the significa nt spectral co ntra st among the cro ps in t h i~ December 10, 19X2, Landsat Ttl.! image. il is possible 10 per form a vis ua l cla ssification of the H OpS based on an exam inatio n of the individ ual bands in Figure 11-20. FOI
11
382
'raeiett -a.
Tona l charac terisucs of ind ividua l crop typo:s in Nac k-and-whue L andsat T M images of Impena l Valley. C A, (Figure 11·10 ) obta ined on Dec ember 10, 1
Crop Type
TMI
T"' T"' T"'
Sug~
II
D
II
Alfalfa
II
D
Conon
G
fallow land
G
TM'
TM7
B,
D
D
D
B,
G
G
G
G
D
B,
B'
G
G
D
G
G
ex ample. aft er care ful e sa mi nauon we see that the heuri stic rules summarized in Table 11-2 co uld be used 10 cla ssify the
scene. It is also pos sible to program a co mputer to take into account the se sa me spectra l che ractcrisrics and perform a cl assifi ca tion . Color Plate 11-5e displays a remote sensing-derived d igita l cla ssification ma p of the study area . When compared with the grou nd re feren ce map in Figure 11 · 20 . il is abo ut 85 percent accura te . It was produ ced us ing TM ba nds I - 5 and 7 and a supervised maxim um likelihood class ification a lgorithm [please re fer t(l Jense n (2 005 ) for informatio n abo ut d igita l image classificatio n ]. Haack and Ja mpoler ( 1994 , 199 5 ) evaluate d this same Lan dsa t T M sce ne and achieved an overall accu racy of 90 pe rce nt us ing different bands.
The accu racy o f a remote sen sing der ived cro p cla ssifica tion map is a lways depend ent upon there being a significa nt differen ce in the spect ra l respons e between the various crop types. T he on ly way to identify w hen th is max imum contrast amo ng spec tral response sho uld ta ke place is to eva luate the pheno log ica l c rop cale ndars lind se lectthe approp riate date s o f imagery fo r analys is. TIlCn classification ma ps, such a s the one shown in Color PI::l1e 11-5. ca n be used to pred ict the amoun t ofacreage in spec ific cro ps at a given instant in time . Such information co upled with ugncultural-rnctcorologi cal models can be used to predict crop yie ld .
Rem ote Sens Ing or Vegetation
relat ive abund anc e an d ac tivity o f gree n veg etation. i~
ing leaf-area-index (LA I). po: rcc ntage gree n cover. cbJoco. phyll conte nt. gree n biomass. and absorbed phOl0SY~ ~· a lly active radia tion (A P,\ R). A vegetatio n index .~ ( Run ning et a t. 1994; Hucte and Justice . 1')99):
maximize sensitivity 10 p lan! biophysica l paramc!rn.. pre ferably w ith a linear response in o rder that scnsitilll: be availa ble for a wide ran ge o f vegeieuon co nditioRS. atll: to faci litate vahdaric n an d calibratio n ofthe index: norma lize or mod el external e ffects suc h as Sun . view ing ang le, and the atmosphere for co nsistent spaIiI! and tem pora l comparisons; norma lize inte rna l e ffects suc h as ca no py back~ variations•• incl ud ing topography (slope and aspect), soi vanauons, an d d ilTe-ren ces in senesccd or \Iiooc!:' vegetatio n ( non pholos yn thet ic ca nopy co mpo nents); be co upled 10 sllme specific measura ble biophy;d para meter such as bio mass. LA!. or APAR as pan of the val idation effort and qua lity co ntrol.
T he re ar e many vegetation indices. A few o f th e most \\' ide~ ado pted arc summa rized in Table 11-3. ~ a n y are funcrieea lly eq uivale nt (re du ndant) in inforrna rion con tent IPtn: and Laute nschla ger, 19S41. and some pro vide unique billph ys ica l info rmation (Q i c1 31.. 1(95 ). It is use ful 10 rCliri' the historica l dev elopment o f the m ain ind ices and PTOli« in forma uo n about rece nt adva nces in index devclopmea De ta iled summaries are fou nd in Runn ing et at. ( 1 99~)and l yo n dil l. (I 'N X). \.1;I11Y indices ma ke usc of the inverse relat ionship between red and nca r- infra red reflectance associnted with healthy gree n vegetation ( ri gu re I [-2 Ia ), Simple Rat!o -
Sit
Co he n ( 199 1) suggests that the ti rst true vegetation indet was the Simple Ratio (S R), which is the rat io o f red retlcctel radi ant Ilux (p,...) to nca r-infrare d radiant flux (P.,,) as described in Birt h and Mc'vcy ( 19M!):
Vegetation Indices {lI-11J
S ince the 19OOs, sci enlists have extracted a nd mod ele d various vegetation biophys ica l variables usi ng remotely sensed data, Much o f this e ffort has invo lved the use ot vegetation in
The s impl e rat io p rovides valuable inform atio n about veg~· tenon biom ass o r LAI (Schlerf et al., 2005 ). It is especially se nsitive to b iomass and /o r l r\ l vari atio ns in high-biomass veg etation such 3~ fo rest s IHue te et al., 2002b),
v,
383
tali on Indices
, I I ·• • .~
C aru tenuid anti
r " lillr
ch lfl nl p h~ J1
~
re rtec ta nce
a bsorption
I
~
"'1:-- - - -
,-
.i .-' - - , Eo
/
1•
t
.......
S(\\\
.......
2
.
Li4 uid .. a tcr aw.orJllion
•
.
.......... .... •.•••••
(r
;···v :: ..:'
,
".
~
~ .:
\
V .\
o
.
a, 2~ 300 )504UO <1,0 :
«so 71M)
7~O XlM . ~ ~u ~J(J
Wa\'cl...'Tl~l.h.
IIU I 12!>U
1500
1750
2000
22SO
2500
run
Rdationship Bcfn t.'('n Sim p)" R:lI in an d :""1)\'1
'0
/P~CO
c>
z 0.8
'.
•
" .~
a
"
Cl
0.0
~ ..;.I ~
"u
~ 0'
•""-e
," ~
o
"
,
Wdh:r
•
Arid
*
Se mi-arid
0
( ira"s
0
Con ikHMJ.~ IOrc~1
0
Deciduous fore st
(1.1
z h.
•
15 10 Sim ple Ratio. Red/Nea r-infrared
'"
rh~s iolq:ical hasis toe developing \~cla: ion ind,,:~ Typ.....a l spec tral reflectance characrensucs for hea lthy green grass and bare ..II) Sl'lil f,'II" the Il a\ etength rmerval from 250 to 1.000 om. bl Th e ND, ' I i~ a ncrmalizc... ratio o f lhc ncar-in frared and red bands. The I'D'·I is functi ona lly C\juhalcnt to and i~ 3 no nlinear tran sform (If the simple rati., [adapted from Hucre et al.. 2OCI2b).
F'9ure 11·21 a l
384
C II -\I' I
Table 11-3 .
S~I.'(:k--d
11
t: ~
Remote Sensi ng of Vegetation
1
remo te sensing vcgcra uon indices.
Ref erences
Equ atio n
Veg etatio n Indn
Binh andMcvey.
Si m ple Rat io (S R I
SR
I~
Colombo et al.. 2003 Sch lcrf~"l al., 2005
Normalized Dittercnce Ve-gelation Index
~ ()U-;(" et al., 1974 Dee ring et al.. 1975 Hoete et al., 2oo2a Schk'Tf rl al.• ::005
Pni, - P..·J P"" + p'~J
rrcovn
.VD V/
Kauth-Tho mas Transformation Bnghmess Greenness
La ndsat Multispectra l Scan ner V.1SS) B = O.332 .\fSSI"- 0.603 'ISS! '" O.675u~'ij
'"
0.262 1Ci.,'i4
Kauth and Thomes. 1'17(> Kauth e\ al .. 1979
G = - O.283.llSSf - 0.660 \IS.\'l-+- 0.577 .4o.-U" 0.J!'i8.1.1SS4
Ydluw stuff Son.'-.",ch
r .. - 0.!'i9<).\'&1 '" Oo4::!lhoS..'';' 0.07l:> \.&J .v '"' - 0.0 16.ussl -+- 0.13 I -'lSs..' -
0.04 1MSS-#
GA5::! ltSSJ ';' 0.81<2~Sl
Landsat Thematic Mappe r (T M) B '" O.2Q09 T.lfl - 0.24'l3 T \12 -+- Oo4IIOt:' TM3 .;.
Brig htness Greenness
055MI T.H4 .;. 0.4·HlIDf5 ... 0.17'* Dn
Wetness
G
= -
O.::!7:?l1T...fl - 0.2174 T.\l2 - 05 50llTM3 .;.
0.722 1TM4.;. 0.0733T.lf5 - O.IMll nn II' .. O.I44(>T \-I1 .;. 0.1761 TM2
-+-
Crist and Kauih. 19% Lune tta et al.. 2002 Price ct al., 200::! Rogan et al.. 2002 Jin and Sade r, 2005 Schlerf et al., 2005
0..H22nn ...
0.3396 T,\ l4 - 0.62 10T 115 - 0041116 T An Normalized OilTercl\Cl: Moi~lu rc or Water lndcx (1'\0 \11 or "nWlj
NIJ .\fI or NOW/
.\'fRTl H - \l itJl R r M5
,VIR l1 H.;. ,\ fil/f R r m
lIardi ~ky ct
011..
19113;
Gal.'. 19%; Jackson cl 011.. 2004 Gal\'30 ct al.. 2005 Jin and Sade r, 2005
Richardson and Wiegand.
Perpendic ular Vegetat iun Inde x (P YI)
19 77
Lea f Rela tive w ater Content lndcx ( LWel l
-log[ I ~ U.,'I RTm - "'fi d l H. T.If~) J
I. WCI
Soi l Adj usted Veget ation Inde x (S ,>\V I) ami
Modified
SA VI =
SAY l l ~l SAV Il
- Iog1I - N I R TM4 - Al idlN. I'II ~I' I
( I + L)(P"ir - Pm I1 P"ir + PrcJ + L
Atm ospherically Resistant Vl." g.'ta ti, 'n Inde x
(A RYl)
Soi l and Atmos pher ically Resistant
lion Index (SARYI)
P* "" ~ P* r~~
( p*",r '" p*r'J
AR V/
Veg~a
S AR Vl =
Enhanced Vegelation lndex (EVil
fVI
Hunt ct ill., 1987
p*,,)r - p*rb P*",, +P*rb + L
G
P• 'I"
p. "" -p",,.J , l foL .... C 1p. r~" - C ~ p. I>I,,~ ... L )
Hucrc. 19R8; Huere and Liu. 1'194 ; Runnin g 0:1 al., 1994 ; Q i et al., 1995
Kaufman and Tanrc,19'l~; l l ucte and Liu. I YOM
II1Ictc and Liu. I'.N4: Running et 31.. ICN4
I lllckctal., I9Q7 fluctc and Justice. 1m Hucte l-t a1., 2oo2a l'BftS. 2U03
385
'legetalion Indi c e s
table 11-3 .
Selec ted rem ote scnsmg veg etation indices .
Eq uatio n
Vege ta tion In de.
Sf;'\\-' Vegetat ion Indc.. (NVI)
Reference s (jupta et a l., 2001
.VVI .. P 7n - P 747 Plm
Aerosol Fret' Vegetation Indc x (AFRII
(P"i' - O.o<>p I~ "m) (P"" - o.eeo 1 ~I, m )
Kamid i lot .II., ~OOl
(P"" - 0.5P 21 pm) (P.."
+
0.5P2 1I' m) Brogc .and Leblanc, 2000
Triangular Vegetation lnde.. In' ll
Reduced Simpk Ratio \ RSR)
RSR ""
P"i' ( 1 P...J
R1Iuo TCARI ,'()SAV\
P..." - P.....,"',,, ) p...·,, "" u + r..."..,,,
3[(P700- P670)- O.2(P700- P~~)(~::)]
TeAR/ "
Chen et .II.. 2002
OSA VI ~ (I + 0. 16)( p!lOO -Plo7u) (PlIOO + P670 + 0. 16)
Kim cl al., 1lJ94 Rondca ux et al., 1996
Daughtry el er, 2000
Habcedane et al.. 2002
TeA R/
OSA VI Gitclson
Visible Atmospherically Rcsistam lndc.. (YARIl vormalizcd Difference Huilt-uplndcc I\'OBl)
ND B / =
,\/iJ/R",~ - N/R " " . . Mid/R T,\ f~ + N/ RT.\I4
hui tt- up",.,,, Red-edge Position
=
krence
11(';,:,-",lIiO/l /11,),'.1 (N OV I ):
NOV I .. P"i' - p,,,J
p""
(\1 - 12)
+ P,~J
TIt..: r.;OVI is funct ionally eq uivalent 10 the simple rnio: tha i u. there is no sca tter in an SR vs. SOVI plot, and each SR
.II., 2002
Zha et .II., 2003
,VDB/- ND V/
REP " 7 0() + 40 [P ( r~-4 cJ~c l -P I 7t11) ~"\l] P P 41lnml - P 17I\lnm) where
Rouse 1.'1 a1. t 1")74 1 developed the generic NOnJ/llkl',1 Dif
~'1
Ckvn . , 1'194
Dawson and Curran, I'N S Baranos ki. 2005
value has a fixed :'>J DVI value. When we plot the mean NOVI and SI{ values tor var ious biomes, v.~ li nd that the NO V I a pproximates a nonlinear tra ns form or the simple rol lin {Figure 11 -21 hI ( Huctc 1.'1 al., 20()2h J. The :'>J OYI is an important vegeta tion index because:
Seasonal and inter-an nual ch anges in vcgctauon growt h and act iviry call be mo nito rc-d,
("I IAPTE~
386
The rauoing reduces man) forms of l/Iultiplin lfi H! noise
di"ilJva nla~cs
Remot e Sensi ng of Vegetation
:\ UVI Im llt.:t' «r C hllr l."tun. SC. l. a n d ~1I 1 Th.'IIHllic :\ l lIp pl' r Data
(Sun illumination d irfcr cnccs. clou d shadows. som e atmospheric attenuation. "1'01 <: \op ngl1lphk variat ions) prese nt in mu ltiple bands ofm uhiplc-datc image ry.
Following an: the
11
[)l.· r iH'd rmm
of rhe ;,\OVI tHuete cl al.,
10023; Wa ng ct al., 2005):
The rauo..b'N: J index is nonlinear and can be influenced by u""itin' noise effects such as atmospheric path radiance (C hap ler Il). ~D V I is uSU311y highlyco",:LJIL-d with \ cgctatlon leaf area index ( LAII . However. the relat ions hip may not !)C as strong Ju ring per iods of ma xim um LA I. apparently due to the sa tura non {lf ~ DV I when LAI is WI'} high (Wang <:131.. 20051. For exam ple. Figure 11·2 1h revea ls that the NDV I dyna mic range is stre tch..-d in favor of low-bio mass conditions and co mp ress,.-d in hi gh-biomass. forested regions. The opposite is tru e for the Simple Ratio. in w hich mosl of the dynamic range encompasses the hig h-biomass fores ts wit h lillie variation reserv ed for the lowe r-biomass regions (grassland , semi -arid, an d ari d biomes ].
II is ' 1.'1)' sensitive to canopy back ground vari at ions (c.g.. SOli vis ibk thro ugh the canopy). 1\1)\ '1 \'3111CS are particularly high \\ ith dar kl'r-Callup y back grou nd s. The N DVI indcx was w idel y adopted and appl ied 10 the o rigina l Land sat \l SS d igital remote sensor da ta. De-cring d al. ( IQ75) add.... d 0.5 to the !\' I)Vlln avoid negative values and too k the square roo t of the resu lt to stabilize the var iuncc. This index is I'd c n ed to as the Tr,IIl.I! il/'llll''' Vt'j!t'f
Many sc ientists continue 10 USl" the N DVI (c.g .. Miura ct al., 2(}f )1: Tr ishcenko et :11. , 21102: Galv ao ct al.. 2( 1)S). In fact. two of the standard \ IO OIS land produ c ts urc s ixteen-day co mposi te NOV! d.nas c(s of'thc wo rld at a spatial reso lutio n o f SOO m and 1 km (Huc tc c t nl., 2002 a ). An N[) VI image derived Iroru Charleston Landsat The ma tic Mappe r dataset is shown in Fig ure 11 -22.
Ftgu re 11-22 Xorm ali .....-d olill,:rcncc vegetat ion inde.\ {~D\l imagc o r ChilrlC-;lon , ,-C derived using UnlU Thematic "'appcr l'...nds 3 and 4.
index rG I. ).:110\\ stu ll" ind c,\ OJ , and no ne-such ( \-1 Tk names attached III the nc " axes indicate t he c haracter isio the indices were intend c J In mea sure . The coe ffic ients art (Ka uth ct at.. 19 71)): 0 .33:! IlI.H < 0 ,(,(13,11.....1'.· t Of,iS ,lf ssJ
lJ
O. :! 8 3 lf~"' 1 - O.(,(>IlM,\',~ _' +
C
o.sn
+ O.:!6:!MTI4
\I.~\·J
( 11.13)
+ O.311 fi ,I!5S4 111·gl
r
- O.fi<)' )II.\S I i
0.4 2N11.1',\_"+ IJ. Oi (, l/.\SJ - 0,1)4] ,1r;S4 111·1;1
/I'
0,tll(, ,\(,\.1' I
II. 131 M,\\_' - 0 .4 52 .\I.\S.I + O.l(x:! IN 4 ,(11.16)
i
Cr ist lin d Kauth t 19 X6 ) derived the visible. ncar-infrared and midd le-infrar ed coc tfici....nrs tor transformin g Landsat Thematic \1<1 Pl'c r imagery into hrig hlness , greenness. ilnd wet ness variables : II
n ,4 ~()(, TAIJ
O.:!'lO,) TJIl
+
0 .24'13 7 All •
O.55Ml n /~
~
0,44Jll 1 .\( 5 + O.170f.lT,\n
Ci ~ - O.:!72XT.\ /1 -
o.~
+
174 1 M2 - 0.5508 TM3 +
Ill ·ISi
11.72:!1 1'\14 + 11.07.'.\ T\15 - H.I 04>1 n n
Kauth a nd Thomas 111)7" I prod uced an orthogona l transfermutton o f the orig inal Landsa t \i SS data space to a new four-d ime nsiona l featu re space . 11 wa s ca lled th.... fa.H elnl cap or A:m.th· ThlJma.\ fmml",.,nmion . lt created four new 3 :\CS : thc soil br ighmc'!>S index (B), gr........ nncss vegetation
II' _ O,1 44/'> 1.H I + 11.1701 f At), + n..H :!21',HJ-
(11 -191
O.-'JW,Ht4 - 0 .fl21117"'5 - (l.-1 l x6 n n . [t is called the tasseled ~'3P transforma uon bec ause of its C3p shape (F igu rl'S 11-23a c) , C rist and C tconc ( 1QR41 identified
v
!!gelatio n Ind ices
Table 11-4,
Index
""'-
Gn:mnM~
,-
...., ''''
Su.
387
Tasseled t ar coeffi cients for usc with I.andsat 7 Enhanced Thematic \o1
TM.
TM2
TM3
,,.,
wn
J~
..J ~
·.3'>-1
. ,ol'>t-
1()~ 1>
,21 ol1
U>lt~
_.Mel
...
-.020
•.1!~
" ~
IT
TM'
TM' . t ~%
· .01ol
- :t.J
CW2/>
-
~~ll6
M,.
..~I>l
d l9
,..,.
_. I,1l
~n:
_,m
-,
M"
·. U 9
_, n ~7
J 'J~
TM' ~.
"""
_. HW
. _
:'II or lll llli l~'d
[) ifr~'n'lI c c
Mots turc or W:t1cr Index -
:'11 1)\ 11 or \1)) \\ I Info rmation abou t vegetation water conte nt has wide-spread utility in agri cu lture , forestry. and hydro logy (Galvao cr al., 20(5), Hardi-k y et 81. ( 1~K 3) a nd Gall (1996) found tha t the Normulized D!ffi:1l!//I·.' .\foimlll: or 11<11e,. IIIJ.·x (N D.\l1 or :'>IDW!) based on La ndsat T ro. l near- a nd middle-infrared bands.
,VlHII or S H WI •
/1'1H. r.IN - MidI R nt. :\' I H. n f4 + MI "' R n/~ '
(11-20)
~
I1tHrd component that is related to soil fe-ature-s. including ecisure status (Figure 1I.:!3d). Thus. an important source i soil information is avai lable through the inclusion of the liddle-infrared bands of the- Th e-matic Mapper (Price et al., lXl~).
The' Charlcsron Landsat T.\' scene I ~ tra nsformed 11lIO lIrightnt.oss. greenness. and wet ness (moisture] content .ages in Figu re 11-24 based on the use of the T M tasseled tzP coeffic ients I Eq uations 11-17 through 11-19). Urbanikd areas arc particularly evident in the brightness image . The greater the bio mass. the brighter the pixel value in the !'tt"ncess image. Tbe wetn ess illlagl: provides subtle in formation concerni ng the moisture stat us of the we tland cnv iratmenr. As expected. the gre ate r the- moisture co nte nt, the lri~ter the rl:sIX11N::. As ex pected. wa ter bodies arc brig ht. Inst and Kauth (1IJH6) identified the fourth tassele d cap iWameter as " e ing have.
was high ly correlated with ca nop y water content and more closely uacked ch anges in plaru biomass and wa ter stress than did the ND\T Jackson cr al. (:!~) found tha t the: "ID VI saturated whi le the 1\1>\\11 conun ued to document chan ge s in com and soy bea n \egclation water content. Jin and Sader 12(05 ) compared the ~D\,tt and the tasseled cap wetness rransforrn auon lo r detec t ing forest disturbance.
Pe r pen d ic ula r
Y("~e l :uiun
Inde:\ -
Richardson a nd Wiq :a nd (1977) used the perpendicular distance to the -soilliuc" as an indicato r of p lant dev elopment . The "soil line : ' w hich is a t.... o-dimensional analog o f the Kauth-Thomas soi l bright ness index. .... as csurnatcd by linear reg ress ion. The r .'rl" 'I/, /i clI lar Vi..g<'/alioll 111IIe_,[ ( PVI'l based o n !\lSS hand 4 data was
I
PV I • oJ (",)~' Ir~SI
I ' I~~
'
m s.') - • t o \'~ ,\ 'SS) _ 1I , ~ S1 AtS'\:J
Lcut w nrer Cnnt cut ludc The tasseled cap trans formatio n is a glo bal vegetatio n index. Themetica lly, it can h~' used any .... here III the w orld to disaggrugall: the amoun t of so il luiglnncss. vcgc tutinn, a nd mcis1~!\' content in ind ividu a l pixels in a Landsat \i SS or Ilematic M appe r image. Pract icall y. however. it is bette r to ro mpute the coc fflcicms based on local cond itions. Jackson (1983 ) prov ide" a computer program to r this purposc. The Kauth-Tho mas tasse led cap transfo rmation continues to be widely used (e .g .• Lunetta et al .. 2002; Price cr al.. 2002 ; Rogan et al., 2002) . Huan g ct at (:!00 2) developed tasseled QP coefficien ts for use with Landsat' Enha nced Thematic 'tJppc r Plus at-satell ite re flectance data. These coe tflcie ms are most a ppro priate for regional applicauons wher ... atmospheric co rrection is not feasible . T he cocfflcicrus arc SUl1l earizcd in Table II - t
I'n
r, (11· 2 1)
I.\ \' C I
Hunt ct al. ( I\lX') dev elo ped the L('lI( lI'tJle!" Content i ndex ( l Wei ) 10 asse ss WOller stress in leaves:
t wc t
- Mi,J1Rn ls )J ( 11.22 ) - log [ 1 (NIR r M 4" .Hi,J1R r ,lf5"lJ'
- l,)g [ I -
(NIRt ,\f~
where ft represents refl ectanc e in the- specified bands when lcaves arc urthcir maxi mum relative wate r content (fully tu rgid: I{ \\T) defi ned as : I{ \ \ 'C =
'ield we ight - o\'en dry wt.·ight x 100 jl l-23) turg id .... eigh t oven dl) .... eig ht
The utility ofthe nonna tize-d difference \ egetaucn index and related ind ices for sa tellite and airborne asscssrucru o f the
.......
nI API E~
388
11
Remote Sens in g o f Vegetation
Cnaractcrts ncs of t he Ka uth-T ho ma s Ta \ sdrd Cap Tr an vror manon
,, •" ~ (br
C
Bn~htnc.'S~
II Cror de...~k'!"ffi"ll in ee !a'l...... I«I cal" bri gh mess-greenness 1r.1Il~ formation .
Hrigh tn.",
II t.ocauoe of land "'''\<''1" "hen r lolled in lho: hrighll\C'<, .gtecnr\C!<.' ' J"'.'("ll':Il sr ace.
Bri!!hITll;s.o;
c..Actual r lOiof brig htness and b'Tecnncss value'< Ior an agricultural area . The shape ",f IlIC ,ji~tnbu IJun I""ks like a ca p.
d . .\rrm, imaIC dH\'('1;on M moisture variation in the pla ne " f , ,, ils. The: arrow rOlnls in the <,li l.:<;llUn o f k"" m" isture.
Figure 11-23 C har acteri stics o ft hc Kauth-Thomas tasseled Clip transformation 13,13J'lt'd fmm ( "risl , I 'll<:"; C rist and Kaut h. 1'I!(6). ThcliSselcd cap transformation is applied eUITL"1:lly if the tasseled cap's ba..: is parallel " ith Iho:: brightness, axis.
Earth's veg etation cover has been demonstrated for alm os t three decades. The time scri ...s analysis of seasonal NOV I d ata have pro vided a metho d of esti mating net primary pmduc uon ever varyi ng biomc types , o f monitoring Ilhenol ogi ca l paucms ofthe Earth's vegetated surface, and o f asse ss ing the lengt h of till.' gro wing season an d dry -down periods ( Huete and Liu, 1<,1 <,14; Rumsey ,'I al.. [(95). Fo r example. global vegetation una lysis W:l S initially based on linearly regressi ng: NDY I valu es (derived fro m AVHRR . Landsat \-l SS. Lands
by ill snu measu rement w ithin each glXlgra phic area yetwi rema in constant und er ch ang ing atmos pher ic and soil bedground conditions [Huctc and Justice . 19'N ). l'bcrcfc rc. emphasis h;l~ bee n giv en to the dcvelopmcmcr impro ved vegetation indices thut lak e advan tage of ralibrated se nsor syste ms such as the Moderate Rt"Slllutioo Imag ing Spectromete r (MO DIS ) {Running ct al.. 1 994~ A lthou gh the NDYI has be en sho wn to he use ful in esrimain!;! vegeuuion prop ertie s, many important ex ternal and internal influences restric t its g loba l uti liry, The improved indic es typically incorponu c u soi l background and/or armosph eric adj ust ment factor. The Soil Al(ill.l1<'d l 'cgl '!lIlion Index (SAYI) is S:W I =
( I + I. HP"" - P,,.,j l
rIO ,,'" P,,,,t + /.
where L is a ca n,lpy backgrou nd adjustment factor tl:w account s lor ditfcrcnual red and near-infrared exuncnce thro ugh the canopy tH uete. 19K"; Huete
C(
al., 1992; Kam:-
clioet al., 2(0 1), An L va lue of 0.5 in reflectance space \lo a:;
v
369
tatton Indices
a. Brightness.
Kauth-Thomas [Ta vselcd Cap) G reen ne..... a nd wetness Transformation of Landsat Thematic lj ata ror Charleston, SC Bri~hln l"\s.
c. \\'cmcss. Figure 11-24 Brig htness. greenness, and wetness imag es de rived hy applying Kauth -Thomas la'Sl-kd cap Charleslnll, SC, Thematic Mapper data \6l>.1ndsl.
foond to minimize soil hrighll1l.'SS variations and e liminate ~ need for additional calib ration for ditf crcnt so ils (l luete ed Liu, 19( 4). The utility of SAVI for mini milillg the so il "aoise" inherent in the N[)VI has been corroborated in many iIIldies. Qi ct al. ( 1l)l)SI develope d a modi fied SAVI, called \lSAVI.l hat uses au iterative. continuous L function to opti1111.1: soil adjustmen t and increase the dynamic range of iWI.
SAVI ....as made less sensi tive tl) atmosphe ric effects by nor.Iiling the radiance in the blue. red. and nea r- infrared jeds. This became the A/II/lu pht'rio /Ill' Resistant l e~L'/u 1M Index (A RVI):
uansrormaoon coefficients to the
(1 1-25)
( I J ·26 )
TIle technique requires prior correc tion for mo lecular scarIcr ing and ozone al'l snrptjon of the blue. red. and near-infrared remot e sensor data. hence the ter m [1•. ARVI uses the differe nce in the radiance betwee n the blue chan nel and the red channel to COITcct the radiance in the red channel and thus reduce at mospher ic effects . Unle..s the aerosol model is kno wn a prior i. gamma Iyl is nor mally equal to 1.0 to minirnizc atmospheric effects. Ka ufma n and Tanre (1\)1)2 ) provid... guideline" w here d ifferent gammas might be used over
390
11
O 'A I" I t:H:
continental, mariti me. desert (c. g.• the Sa he l). or heav ily vegetated areas.
\l UI)tS t :nh a" ,·.-d "'oK.'Jalj "n " "t n " 'r'''\ t",t01 ,,"r r II"" ", \"o~rl.l'"
~" r",ali l<'d Il jffn~"ct \ ·,·~.'t " t j""
10 .0
Soil a nd
Atmosflh rriellll~
Resistant ' "e!:d al ion Ind t''l.. -
S.\ R \ ' )
-e
-., .
Ji
Huett' a nd Liu ( 19Q-l) integra ted the L funct ion from SAVI and the blue-band norma lization in A RVI [0 derive a Soil (111.1 "'tll/ 'l.lpherica!(I' Rrsistont I' X t'/utio!l lades (SA RVI) that corrects for both soil and atmos pher ic noise . as would II mod ified Si\ RV I (MS I\ RV I):
SA RV I :
p. It;. - p• •h
( 11· 27 )
p· "" +p*,,,+L
Remo te Sensing of Vege tation
oS
~ e.e
1 I I I I I 1 I .-+, I I M>Vl ,lmoN
"''I' > ""'I"lIId' '' j/
• ·~';'F· t"'''''-ti·
, -+-
r-
..
:
J ,. \ ..'\
01
. --.
.
I
,"'-
..- -
I-+-f.'...,'• .:'"'" " ,t·,.t;-..; ~ '-+''' 1-1 ,;,' •• : .-i~ r: I I
1iO
'.
....,. ~'."
.. -.~~~·lI ,-+-1-+": ' ....I.•.. r ~
J!
:5 2.0 -r-t-r- _. 1l
• ~ a, , ::-'--"-1 ' - '. EVt" ol"t~ -.#>! "+~r:" r-'1
. ,' ,!
""'_ ~' - "'--.-
'_+--+_+-1
)., .... .i-:- "~ ·_ . -f-·I--I-H , ::''11·'" -r-i--+--+--j-I-I-H • •,
...:... ';- +--+- +--+- +-+-1 1 --I-,..~ " ' -'I' +++++++-1 r .··,..,:'-t-+-+-t-H-+-+-+--I + ~
en
1
-2.110
0 00
H UCh.' [l!IU Liu ( 191)4 ) perf ormed a sensitivit y analysis 011 the
orig mal .\IDV I and improved vege tation ind ices (SAV!. ARVI. SARVL MSARVI I and drew these concl usions :
(p",y - O.66P I6I,m) AF RI I.6"m -
If there we re a partial atmospheric correctio n 10 rem ove the Rayleigh and MOlle component s, then the ~I vegetation ind ices wo uld be the SAR\ 'I and ~I S A R V I. wnh the r-; OVI and ARVI being rhc \\ OThI.
become slightl y wo rse hut sti ll wou ld have the least ove rall no ise . T he NDV I and A RVI woul d have the mtl~ l nois e and e rror.
Acreeol Free \ 'Cl;:Clal ion Inde ' -
An U
Kamiel i er al. C::!{)(JI ) fou nd that unde r clea r sky con ditions the spec tra l ba nds ce ntered on 1.6 and z.t u m arc high ly corre lated w ith visible spectral bands centered on blue (0.469 11m ). gree n (0.555 11m ), and red (O.M5 11m ). F. m pirica l lincar re lat ion sh ips such as PIJ4~~ m - () . 2 5p~ 111m' PO ~~~ m : O.33P2 111 m and POb4 ~lI m - O.66P I I\jl m were found to be statistically significant. Therefore. based on these and e ther retationships,l\\ oAerm ol Free lege/,ll/On InJICt',~ (AFR I) were developed:
am
600
Figure 11·25 A ccmpanscn of the sensitivity of the MOl)I').de. rived Norm alized Difference VC~"lali()fl Illlb (NDVI) values ami MODIS Enhanced V~ IOOe' ( EVil val ues for dense vegetation (Did-. :::002).
If there we re a total atmospheric correcuon. then then: wou ld main ly be " soil noise.' and the SA\ ' I and MSA RVI would be the best equ ations tu usc. and the N OV I an d A\{ Vl would be the worst.
If there we re lill atmospheric correction at all {i.e.. 1\(1 Rayleigh. ozone, or aerosol correc tion], the SA RVI \.I ou ld
2.00
!,,,ba nco,):VC~'·'," i<'n !oklo, 10J
(11. 2XI
MSAR\I
0=
(P II "
+ O.66 p I "Ilm)
and
( PilI' - O.5 P ~ .ljl m )
(1 1-)0
ro.." + O .5P ~.llt m) Under
cle ar
sky
cond itions,
the
(11-191
A J'Rls
(especief
A FR I~.I I,m ) resu lt in values vel)' si mi lar to NDV!. HO\\"CleI, I if the at mosphe ric colum n co nta ins smoke or sulfates then the A t.'Rls are su perior to NOV ls. T h is is heca use the electro magncuc energy cen tered al 1.6 and 2. 1 jllll is able to penetrate the atmospher ic co lum n better than rL'
392
C Il -\ 1'1 ~:R
11
Remote Sens ing of Vegetation
Lane
used the SenSOT10 nMp the leaf-area-index o r Canada. The
760
Nt'dut't''' Si lllf'/r HI/f io ( I{SJ{, is:
IheS'
bane
RSR '" w here
Pm r (
I _ P " - P ""',,. ) Pr,.J P ,,"'... . . p ·'TI'''n
( 11-33)
P,.._,,, a nd P...,,-... arc the m inimum and max imum
SWI R reflectan ce fo und in ea ch image and deli ned as the I pe rce nt min imum and maximum cuto ff points in the h istograms o fS W IR reflectance in a scene . Tho:major advantag es o f RSR ov er 5R are a) the differenc e be tween land -cover typ...~ is much red uc.ed so that tho: acc uracy for leaf area index retriev al for mixed CO\ C T I)-J'('s ca n be improv ed o r a sing le LAI alg or ith m call he dev eloped ....ithour resortin g 10 coregjsterc-d la nd-cov er ma p" as jhe first apprcxunarion, and bJ the: backgrou nd (UndeI'MO!)', litter, and so il) in fl uence is suppressed using RSR because th... SWIR band is mo st sensitive to the amount o r vegc tauon co ntaini ng liqu id wa ter in the bac kgrou nd (C hen ct al., 20(12). Chloroll h~ 1I A bsl .rpt iun ill Kcncetlillcel nd c\ - C A KI; .\ Iod ifk d C h lo rllllh) II A" s.. r pt iun in Ke Ilcct an ce Indc \ - Urc..\KI ; 0pli mi/cd SlIiI.Adj u,t\'d V{"J.:I'l aliun I nd el - O SA\"I ; Iblio -I CA Kl iO S.-\\" 1
Ma rty scientists are interested in the amoun t o f chloro phyll in vege tation [e.g.. Daughtry C! a l.. ::!OOO). Kim CI a l. ( 199-JI de ve lope d the Ch/olTlJ'hy/l Ah.lOrl'tioll ill Refh- clilllce Index leARI). It was modified to becom e the Transformed Absurp tioll ill Relh'("f
It uses bands corresp onding to the min imum absorption of the photosynthetic pigments, cente red at 550 and 700 nm . in conj unc tion with the ch lo rophy ll (I ma ximum absorp tion h:111d. around 67 0 nrn . The choice of 700 nm is dill' to its location at the boundary be tween the region where vcgctalion reflectance is dominated by p igmellt absorption and the beginning of the red ed ge po rtion where veg etatio n stru cturu! cha rac terist ics {i.c., the SPOllll ) mcsophyll] have more infl uence (In reflec tance (Ki m cr al., 1994), Un fortunately, TeARI is still sc n~ il i \ c III the underly ing so il refl ectan ce properties. purticularly fo r vegetat ion with a low leaf area inde x. There fo re , Daugh try et nl. (2 UOO) proposed that TeA RI be combined with a soi l line vegeta tion index like the 0 l'lim i:<'" S"/l.Adjml.·clli·gl'f
bilit wau
T hc ratio bec ame
Te A RI OSAV I
W ill
and is hig hly correlated w ith vcgeta uon (llaboudanc er al .• 1002 ),
chloroph~1I
wI>
7 • WII
Many reso urce mana gers would like vegeta tion fracbI in fonn ation te.g ., 60"10) (R undq uist. 2002 )_ Building the Atm osph erically Rl'sist.ll1t \ 'egl'talion Index, ~ developed the Vi_tiMe Afm(lJI'}/I;riCll /~l' Reslstar u (VARI) comput..-d as (Gitclson cl .111 .• 2(02):
inc!
R.
n 'p
The index was mi nima lly se nsitive to atmospheric dedi. allo wing est ima tilln o r vege tation fraction with an error Ii < I 0" ;' in a wide range of annosphc nc optica l thickncr.s.
b< Co
" S
:\url1l ali/l..J Ditferen ce Built-up Inde\ -
,\ IUII
Many professionals " 'Or"in!:: on ur ban/subu rban problellll art.' interes ted in monitoring the spatial distribution aDd gr ow th or urban built-up areas. These da ta can be used f(ll: watershed runoff prediction and ot her p lanning applicatica Zha ct al. (20 03 ) calculated a Nonnolized Difference B~i/l' Ill' tudes (,,"'O BI ):
(l 1·3S\ wh ere
"if".'"
'1"";"-'""'"-,,,.';0":,";,' fi" = ,.-.';;
.V1R r \l4 + .\fitIlR rM~
(1l,39)
Th is resulted in un ou tpu t in1>lge that contain ed only built'lJ!l an d barr en pixe ls haloing ptlsiti\C values whi le all other land cover hada va lue ot'u or - 254 , Th e technique was reponed to be 92 pe rcent acc urate.
The ncar-in frared hands found on Landsat Til.l- J\OA.~ AVIIRR. and the Imlian Remote Sens ing Linear Imaging Se lf Scan ning ( LlSS) sc nsor al e in the region 770 to 860.
b r I
n
1·35 )
·3 6)
393
scape Ecology Metri cs
10 9(10. and 725 to 1100 om. respectively. Unfortunately, rear-infrared region s include wa ter v3por ab sorp tion Therefore . 10 improve the biomass mon itorin g capn. of the 1\OV I. G upta cr at (200 1) c hose (0 exclude u por abso rption hands in the creat ion o f a ,VI'\\" leg.··
as their biophysical (e.g.. LA I, biomass. APAR) a nd struc tura l (c .g.. pe rcent eanu py closure ) properties. \llln itllrin g these churactcnsucs thro ugh space and time will prov ide valuable information for unde rstanding the Earth as a system (Townshend and Just ice. :.!OO2).
fndt'x(f\V I) :
Land scape Ecology Metrics WI :; P7T/ - P 14 ~
uent
lion
PO"
tists
1I 1.....(J)
P to73
Pm . P 7~7' an d Pto' ) an: the rertccra nc-cs cen tered at ,7-17. and n73 om. respectively, in J- 10 IO-om bandhypcrsp<."Ctral data . Outer narrow -band veg eta tion are found in Jensen (2005). 2e Podtlnn Det ermination -
Rt:I'
-dex
3 7)
rts,
of
TIS
od
abrupt cha nge in the fixO-liOH om region of retlecrance of lea" ..." !; l:3 UM.-d by tho: combined effec ts of strung. hyll abso rption and leaf internal scattering is called ltd edge. The red i'tlKI' position ( REP) is the m int o f urn slo pe on a vegetation refle cta nce spec tru m een the red and ncar-lg wav ele ngt hs. The red edge was descn bed by Collm s ( l IJ7K). a nd is perha ps the mo st ied feature on the vegetation spectral cu rvc accordi ng 10 erfand AlZbcrg... r (2001). T he REP is usefu l because it 5lr('lflgly correlated w ith fo liar chlorophy11 co nte nt and can rsenslnvc indic ator o f vegetatio n stress . Determining the edge position using remote se nsi ng data usua lly requires collection of'hvpe rspcctrnl dat a.
vegetati on indices are useful fo r rnomroring the co ndition and bcalt b o f vegetated pi\ e b . Ho wever, such pe r-pixel an alysi s doc s not provide any informatio n abou t the nature o f surroundi ng pixe ls, inc[udlll g thei r site and association charactcnstic.s, Landsc ape ecology principles haw been dev eloped that mcr casin gj y incorporate remote se nsor data to JS'>t"S.~ the health am i di, ers ity of veg eta tio n and ot her variables withi n entir e l,.'\:osy!>te11ls. Th is has res ulted in the dcvclopmcrn o f numerou s 1'lIId~Coll"Jt' ecology maries or imJicalO~ Ihat arc o f .;.jgmficanl value when anal yzing rangeland. gr ass land. forests, and wetlan d (F roh n. 1998: \IcGariga l et al., 2(06 ). Numerous govern ment agen cies. suc h as the Environmental Protect io n Agency. base much of their en vironme ntal modeli ng and landscape character izat ion on these mctrics and indicators (ErA Landsc ape Eco logy. :.!UOlil. There fore. it is use ful to pro vide a brief review o f their or igin and summa rize se vera l of the more important landscape ecology metr ic varia bles thai can be extracted from rem otely sensed d ata .
'Or
". ,,-
., 'J
lmcar method proposed by Clcvcrs ( 1994 ) ca n be impletoo that make s use o f four narrow bands and is co rn-
ed as follow s: REI> '" 700 + 4 0 [P (led ~Irc) - P (7IKlnm1] . 1-l 17Jlln,n ) P I 71 ~ ) n m i
p ( l>7U,onl )
,
+ Pn~u"r,, )
(1 1-·.\1)
(1 1--12)
P
d
d
wson and Cu rran I I99!l ) and Haranos k i and Rokn ... (2005 ) rizc add uio nal met hods used to determine the rcd _ position. .enusts throug hout the world are studyi ng till: ro le of ial vegetatio n in large-scale g lob al proce sses. Thi s is sary in orde r to unders tand how the Earth funct ion s as s ystem. Veget ati on indices are bein g used to accu rately mlory the global d istri bution o f vcgcrauon type s as wd l
The t... 011 llIlli!" '
394
ciplincs that it embraces Ie.g.. geog raphy. bio logy. eco logy. hydrology ) is that it provides a hierarchica l fram ewo rk for interp reting ecologica l struc ture. funct ion. cha nge. and resiliency at multiple sca les ofinquiry.
Tmditio na! measu res 10 protect the enviro nment. such a ~ preventin g water po llution Of prorccring biodiversity, often focused on specific e ffluent d ischarges or fine-scale hab itat requi reme ms. Th is method has been described as the tinefilter app roach. In con trast. tho: coarse-filter approach to resource conservation states that -b)' managing aggregates (e.g.. communities. ecosystems. landscapes I. the ccmponer us of' these aggregates .... ill he managed as wdl", f1llurgcro n and Jensen. 1993). In other words. the most costeffective stra tegy to mai ntain the resiliency and productivity ofecological sysn..ms is II,) conserve (or reston..) the dih,:~il~ of species. ec osystem processes. and landscape pa tterns that crea te the systems (Jensen and Everett. IlJlJ31. Applying: this coarse- filte r manage me nt met hod requires that landscape pa tte rns be eva luated at mu ltiple spatial and temporal scales rather than sim ply at the trnduional scales of crrcam reach or fOR'St stand.
C11 ,\ PTU~
11
Remot e Sens ing of Vegetation
pattern III/il is a collection of measurement units patch units that haw the property of being the minimum descripto r of a large r spa tial area. The scales otee qucsnous and indic ators suggest two types of landsi:IJ units: watersheds an d lundscapc patlc m types (lPTl('" ham and "'Ilr!on. IQlJ-I). watersheds and l PTs caphR bound four important Iluw processes operating "ithin among landscapes: tlo .... s o f enl'Tg). water, nutnents, biota . Scales '11" wutershedv and l PTs range from apjIll 110 mat cl~ 10 10" umt s in cxtcnt, and fro m Ito lOOba.
Landscape Indicators and Patch MetriCs
Jones et a!. (liN!'!) ~U~l"l-I that tancscepe integril) ca moni tored by carefull~ wa tching the status of the folIo. indicators: land-cover com pO"itioll and patt ern riparian exrem and distribulion ground .... mer
Hierarc hy theory allows landscape ecologists 10 integrate mu ltiple scales of information to determine w hcth cr landscape pauerns arc sufflcicm W 3110 w ecolog ical processes 10 ope rate at the necessary scales. The objective is 10 investigate changes in the distribu tion. domi nance. and connectivity of ecosystem co mpon ents and the effect of these changes on eco log ica l and biological reso urces. For ex am ple. eCl1SYStern fragme ntat ion has been implic ate d in the dec line of biological diversity and eco system suctainabihty at a number (If spat ia l scales (Forman . 1995: Jones ...\ al., [\jl)S). Derermin ing stat us an d trends in the pattern nflundscapc s is cmiculto understanding the overal l con dition 1'1' ecological resources. Landscap e patt ern s thus prov ide 11 set \) 1' indic ators, (e.g .. patte rn shape . dominance . connectivit y, config uration ) that can be used to usse ss eco logical status and trends nt a vur icty o f sca les. A hie rarchic al framew ork also permits two important type s o f co rnpnrisons: 1) to co mpa re co nd itions within and acm s-, lan dscapes. an d 2) to co mpare conditions across diff eren t type s of ecologica l risks . Suc h eco logical risks include the risk of eros ion_ loss of sni l prod ucti\ it)!. loss of hydrologic function. and lo ss o f hiod i\'C~i t)!. Sca lolble units are nCl-ded 10 add ress landscape t'eo logy issues at multiple sca!..:s within a hierarchical fra mework. Exam ples of scalahle units inclu de palcht's. patterns. and land s.capes. A patch IInil is a s.:1 of co ntigU\lUS measurement units (e.g.. pixels ) that ha\e the sa m..- numerical \alue. A
grccnn....ss paucm degree (l ftllorh~ sica ! constraints
erosion porcnual. Monitoring these landscape Ind icators req uires PI"lXi>/. repeatable measurements of terrai n {'tllclles such as indi\'i~ ual forest vtandx. rang eland. wetland. and/or agricultu!1l fields (Table 11-5). It is also importantto ident ify palchl'S1l! pure urban structure such as rc~ i dent ial and cornmerciallars lise. Thes c Illl'asure llU:llls of I.. . rruin patches arc roulinely refe rred ttl as /wI
Ta t
B
395
.JIldsc a pe Ecology Metric s
~ 11 ·5 .
Societal values. ellample indicators, ami candidate landscape «olog) mcuics. Indicator
Socie ta l Value
3iOOin ' H it ) '
\\Itrn. hed
l n l~ ri l ~
Llnd, u pe resilk-nc e
~illul/ce.
Candidate Metric s
wildlife habitat suitability
patch statistics (number. total area. average size. largest size. distance betv..cen, ratio penmeser to area. shape . fractal dimension . square pixel model, etc.] , Iragmcmation. cOllwgi"n . zone fragmer uanon index, patch per-unit-area index. domina nce. adjacency of laml-cover IYJlCS. Shannon diversity, biophysical attribute peuerns
stream biological cr,odltion
di\l:'f'S1l}. square pue! mod el. dom inance. fragmcmarion. zone tragmcntation index. p.uch per-una-area index. adjacency of land-cover types. sl0J'C. elevanon . diffusion rates, percolation threshold. erosion mdex. texture. bi..,ph}SJcai aUrioole patterns. geochemical attributes
forest plant species richness
diversity, dominance. fragmentationzone tragmcnuuion index. patch per-unit-area index. slope, erosion index. texture. patch srarisncs, square pixel model. biophysical attrib ute patterns
landscape ~uslai nab i llt)
patch sM islics. contagion, zone fragmentation index, p"t<:h per-uniturea index. fragmenta tion. texture. domman ce. fractal dimension. """uare pnel model. biophysical attribute patterns
water quality
patch statistics. erosion index. hydrologic modiflcarion . adja cency of land-cover IYJle~. domina nce, contagion. IUllC fragmentation index. patch per unit area index. fractal dimensi on. square pixel model. elevation, slope. biophysica l attribute patterns. geochemical aunbures
vulncrnbibty 10 lloooiul;:
patch Sl
land scape sustainabiluy
patch statistics, dominance , contagion. lone fragmentat ion index, patch per-unit-area index, tragmemarion, fractal dimension, square pixel model. biophysical attribute peucms
D. is the information theoretic inde x thai idc nu-
~ the extent to which the landscape is d omina ted by a si nland-co ver type- The metric. 0 < D < I, is com puted as
D-
1- [2:<-p, ·,np,)]
,
( I I- H )
In (II )
~ O < p~ < I is the proportion o f land-co, er type k , and" the total number o r lan d-cover types presen t in the land-
pe.
"'I
where is the probabili ty that a pixel (Ifco ver type j is adjaccm to type j . T hc f ;-(/<"10 1 dimens ion, F. of parches indicates the exten t o f human re-s ha p ing: o f land sc ape struct ure (O·N ... ill ct al.. 19971. Hu ma ns cr...ate sim ple landscape patterns: nat ure ere;;I t.:S complex patte rns . The fractal dunc usion index is calculated by regressin g the I\)g o fthe patch perimeter aga inst the log o f the pa tch area fo r each pat ch on the landsc ape. The index eq uals tw ice the slope of the regression line. Patch es of four (If fe we r pix els arc excluded because reso lution probte rns distort the ir true sha pe .
lPnlagil:m. C. expresses the probab ility that land cove r is re "cl um ped" than the ran dom ex pec tation . HII' index . 0 C < I. is
" Inp"l] c = 1_[2:2:<-P 2In (/I) ,,
(11--441
O ' Neill cr at. ( 1(97 ) suggesr th.u th is se l o f three indices may ca ptu re fund ame nta l aspects of landscape pattern that infl uence ecological processes. Sign ificant changes in these indi ces for an eco~y~lcrn might indicate that pe rhaps deleterious processes arc at work in th e envi ronment. For example,
(U \ "l ~.H.
39£
•
•
. , -,,-_ b
•
an> l.md cover I ~T"''''
~""""""''!''''''''i'' mndllicd C" nra;:i" n, C moee
clumped
nOIclumped
FIgure 11-27 A hYJ'Olh~'1;cal dq nc lu.lfl o f a thrcc-dimcnsso nal landscape metric feature space . Point <1 represents where a stable, unmodi fied ecosystem might reside in ucnunance. contagion. and fractal dimension te a ture space. Wlk"Tllhe landscape is modified b> man or natu ral forces. il may mo ve 10 point h with mall)' land-cover Iyrc~ being introd uced tdontiucncc chllIlgc l. be less clumped (con tagio n). and ex hil:>it a
more modified fractal dimension. This could be good or bad. Remote sen sing of vegetation is cnucat In tho.' extraction of landscape Pilh:h memes.
cons ider 3 small ecos)slem that exhibits a less mollified frac ta l d ime nsion. is highly du mped. and has relativ ely few land -cov er types wit hin n. [t might appear in a thrce- dunensional landscape metric space allocat ion a in Figure I I-.:n. If t his small ecosystem we re subd ivided with se veral new roads and fragmented. its loc ation migh t mo ve in th reespace to b with many land -co ver types be:ing introd uced (dominance change], be: tess cfurnpc d [contagion], with a me re modi lied fractal di men sion , Thi s co uld be: good or had . In face the relati on ships between the metric values and how they ac tuall y re late to eco logical principles are still being determined. Remote sensing oj vegrtanon K-ifhm these patches is I 'el)' importunr
•
Re m ote Sensing of VegelatiOll
Applying tho: principles o f landscape ecology requirt$ understanding ofthe natura l variability oflandscape and proc<."l
less
lnoJi lk d
11
T he goal is usually til
estimate, on
J reg iona l basis and with kno.... n confidcnx. the curre nt vtatus , trends. and changes III se indicators u fthe importantlandsca pe s:
csnmate w nh know n co nfidence the geo graphic CO\C!J!t and extent ofrhe land sc ape s" pattern s and types : seek a ssoci ation s hl:t.... cen ~e lo:':: l<:d indicators of and anthropo geni c s trcss o rs and indic ators of la~ condi tion : and pro vide statist ical summ aries and periodic the condition of the landsca pes .
asscssm~
Moni toring the vcgcnnion in land scape parches us rcrnotcly se nsed data an d deriv ing acc urate mentes these data is becom ing a very important component of~ ecosystem monitori ng pw gram s. For exa mple. AlTO) Moya cr al. (2005) usc-d remote ..ens ing-tkrived lan~ ecology memes to anal) lO: forest fragmentation" regrow th characteristics ill Costa Rica fro m 1%1) - 2001 Jac kson and Jensen l 2()(15 ) used remote scnsing-lkri\d land scape ecOI'I~Y memes 10 perform reservoir short. envuonmcmulmonitoring in So uth Carolina . II is also imponam to mon itor the hea lth of CCOS}M{'1lI~atlb: reg iona l an d nat ion al kwh to iden tify sign ificant ~ areas rhar may he experiencing u loss of'biodivereuy Oee Ii the most use fu l me thods o f mnintainjug biodiversity that ~ based on the use of remote se nsing derived vegetation dalJ6 Gap Analysis .
Biodi versi ty and Gap An alysi s
t he rap id lo ss o f biol \lg ieal div ersity {biod iversit y] remaiI one Ill" ma nki nd's greatest threats. T he convemiOMi approach to mai nta llling biodivers ity generillly has b«n ttl
Ron
pN \I ,
'b \
'" o r
r I,
c:
• " \
I
397
mote Sen sin g o f Ve getati on Ch ang e
'"
rms
this
<0'
)at-
ccd species b)' en dange red speci es and threat by threat. illiin the Unit ed Stores. the primary mean s o f stemm ing loss is the Endang e red Spec ies Act (E SAI. Some have , izcd the ESA for ...cvcrat reasons, incl ud ing a bac klog unaddressed pennons, fail ure to develop and implement ery plans in a timely fashion. and lack ofedequa te eg to meet objectives. A prim ary ca use o f these probis that the Ac t focuses on individual species. Effort dcd on this. ... pccics-by-spccies approach is inefficient. sivc. and b iased toward charismatic mt'gdfwflllI hallbroad public a ppeal a cute an imal is more likely to prol~ too than a not-so-cute ani ma l I. Last -min ute protecefforts also contribut e to economic conflict becau se fail to pro vide a reasonable planning fram ew ork for ic inte rests (e.~.. be tween bi~l log: is1s and logg ing ies). Wh ile necessary. these effons need to be comnted with mo re proact ive met hods that attempt 10 in speciers and eeu syste ms while the) are sti ll com(Edwardsct al.. 1995; Millington cr al., :!O(3).
u.e.
co. "d
.ge
approach lo r ass<:ssing the current status of biodi ve rsity
scntcd in exist ing mana gement are as. It functions as a pre limin ary step 10 the more deta iled st ud ies need ed to establish ac tua l boundaries for po tential biodiversity management areas. Gap Analysi s, by focusin g on higher levels o f'biol og ical organizations. is likely to he less ex pens ive and mo re hkely III succee d than conservation pro gram s focus ed o n single species or po pulations {Sco n ct a l.. 19(3). On e of the lirst G ap Analy ses focused on enda nge red forest birds in Hawa ii (Sn 'U cr al.. 19 87). When compared w ith a ma p o fthe exist ing rese rves. -c 10 percent of the geographic ranges of endangered fore-st bi rds \\ eft' protected . i.e.. there were signific.a nt gaps in the exist ing biodi vers ily prut ect iun sc heme. Several areas wi th highl y endangered bird species richness have since bee n protected by the Nat ure Co nse rvancy a nd stale and federa l ag enc ies. Succ essful G ap Anal ysis has tak en place in man) locat ions. inclu di ng Haw aii, Ltah. Pue rto Rsco. and California. G ap A na ly.- sis is under way in many ot her states and cou ntries [Sa vitsk y, 1998 ).
Rem ote Sen sing o f Veg et at ion Change
elllevels, not just en dangered s pc-cics. is called Gal' ."'111/of
'. m
'y
e-
. As an evaluano n pr oc ess, it prov ides a systematic ch for dete rmin ing the protection a fford c-d bio logical ,mity in g iven are as . lis fund amentals arc prese nted here use- it is heavily based on the use of remote sensing and graphic infor mat ion ~)st..·ms (G IS) to idcnnfy gaps in iu'rsity prote ction that IllJ) he filled h) the est ablishI (If new preserves or c hang es in land-use practice-s netal..19l}J; b lward s ct al. .1 99 51.
)e
,d
o.
!)'!lical Oap An alys ts inclu des the crea uon and anal ys is of primary G IS layers:
,d •the distribution o f act ua l vegeta tion-cov er types deli neated from sa te llite and a ircr;l!\ remotely se nsed datu mdancillary in Ionmnion:
"n
Ana lyzing a n ind ividua l date o f remote sensor da ta to e xtract me an ingf ul vegetation bioph ys ica l information is o ften or value. 1I,1We\ Cr. to apprecia te the dy namics of the ecosystem. it is necessary to mo nitor the vege ta tion through time and det er m ine what changes in succ c -oion are tak ing: place . Rela tively h igh tempo ral res olution satellite data is o ften of value when conducting suc h successiona l studies. Th e follu wing case stud y docu ments the usl'!oll1l:s, o f S POT remote sens or d.ua and the methods used to monitor wetland c hange in ;I freshwa ter reservoi r.
Remote Sensing Inland Wetland Successional Changes
' land 01'. ncrship :
.r s
and-manag ement status; distribution o f terrestr ial verteb rates a s predicted fro m the distrihution ctvegemnon a nd if! situ ob servatio ns. Analys is provi des an o vervie w o f the d istri bution and of seve ra l co mpone nts of biodiv ers uy, II use-s distribut ion oractual \ egctation type s an d terrestrial vcrte and. whe n av aila ble , invertebrate taxa as indic ators ates j for biodivers uy, Digital ma p po lygon overlay's .G IS an: used 10 ide ntiry indiv idu al speci es. speciers-rich . and cover tylXs that arc unre presented o r under-rep resetv arion
I
Inland wetland s assi mil ate pollutaurs, cont rol floods, and ser ve as breedin g, nu rsery , an d feedi ng g round s lo r fi sh and w ild life . Unfo rtuna te ly. the conterminous Un ited States lost 53 per cent of its we tlands tu agr icu ltura l. resident ia l. and.o r co mme rcial land usc from the 17Xlh to 19ROs. Accu rate and timely in formunon un .... ctla nd dist r ibutio n is essen tial for effect ive protectio n and ma nagement. T his case study docu ment s the use of m ulup le-season a nd mult iple-yea r SPOT sate llite multispectra l data for mon itor ing inla nd wetl and successional changes in Par Pond on the Sava nna h River Site. Sc. ca u.se-d by the d raw-do .... n o f the reservoir 's water leve l from J une 19'11 thro ugh Oc tob er 199-1 (Je nse n ct al.,
398
J'1'1 7) . The ~ lll Lly brings to hear man y ofrhc considerations d iscu ssed ill this ch apter.
C H.\ V I t :K
11 ('~ l' l ~
1'1I" uul"t:: i,'al
,,( Ca ll1li l ~ and WlI lcrlilk, in I'ar Pllnd.~'
Ca ttails arc green with fullcanopy
I
Par Pund Rht'r\t1ir .stud~' Area Par Po nd is a 10 12-ha reservoir orig ina lly crea ted in 195 t! to rece ive reacto r cool ing wate r. but now rece ives no w. through wurcr from 1111: Savannah River. Par Pond has a stable. pred ictabl e cattai l and wmerlily ma rrophyte co mmunity when wate r le vels tl uctua te < I m per yea r. App roximately 30 macrophyte plant spec ies an: found in Par Pond . bUI o nly a lc" dom inate : Cnnmls ( Typha spp. ) aTC persistent emergent mac rophytes thai exist year-rou nd in Par Pond. They begin to " gree n up" in ca rly to mid -April and oft en form a de nse. green canopy by late \by. as doc ume nted in the phen ological calendar sho wn in Figure 1I'::!8. Ca tta ils scn cscc in late Sep tember or early October, remain ing brown thro ughou t the w inter mo nths . Canails are normally found in shallow \.\, mer < I m in J':IHh adjaccrn to the rese rvoir shoreli ne. watcrhhes l .\)'ml >h
R.
Re mo te Sensing of VegetatlOll
r-l"~ Calt,ulsa:\:
1
! C' alt a i l~
f
!
arc
brown
'
Waterfihcs arc
\
green with full canopy \
,
j
bl\l\' n
\
I
;
\, •,
F
M
A
"
Figu re 11-28 Annual phenological cycle of inland "'~lland ~ Llih and wah:rlilks in Par rund 0 11 lh~ Sanlla River Site in South Carolina. Cattails m ~ emergent marsh \ egetalion that green up CIfk than warcrhlies in late :\larch and ...ady Apnl T'i/I begm scncecing in late October and hr dormD over the "inter, Wat... rlU ics disappcar cuml'letcl) bl November each year and reappear in late Apr.L n ulh cattail and waterlily have a full, ,knse ~ througboen the summer months.
SI'Ol HltV images used to doc umentthe . cgo:lao tion succcs..ion ofPar Pond.
Table t 1-6.
Date
S POT Oal a Type
Refenlnce Cotot· Inlrared Aerial Photog raphy
HRV- XS
January J I. 19'12
May 5.1 ')')2
HRV· XS
~l
October 13, 19<)2
lI RV· XS
August 10. 19'12
:\13) 1O.loNJ
HRV- XS
April 23. 1
October 28, IIN3
I:IRV,XS
January 22. 1m
April 2, 1Q'14
HIW-XS
April
October 25, 1<1',1"-
HRV- XS
M arch 14,
19'J ~
2. 1<)')2
t ~,
1'1'14
Remnte Se n\u r- Oata Sun ang le and seas ona l soi l mo isture (Je nse n et at., Seven S POT multispec tra l (XS ) images acqu ired in the spring and fall o f 1992, 1993, a nd 199 4 were analyzed (Tabl e 11-6 ). Nc ar-ann iversary dales were selecte d when ever p ossible to minimize c hanges in reflect ance caused by
I99S ~
Co lor-infrared aeria l phot ography was also available fOf~ expe riment. SPO T image-to- map recuflcauon was based ee the lise o f approximately 50 ground-con trol po ints per d:ltc and nearest-ne ighbor rcs ampling III 11 Un iversal Transverse Mercator projection. Tota l geometric roru-rucan-squae-
,n
te Sensing of veqe tetrcn Change
~d .SC
399
'0 , - - - - - - - ---------c
Irtetal iun x ucce....iun
on Par Pond
•,,
,, , ,, ,
,
. ." _
- • - Old f ielel 1'" ,,, _. ..... Ib. hlwood
Wal ~ r
IHZ'f/?'~ Ikad \ 'q
Old Fid d
Sr ,kcnI,h
Pinc Hanlv.o.>d
11>1 < SoI l
,, I cal-
, • ,,' -., ,
"
:t m ah
en t jrhe r
1l1Cy t m nl
b, Til. .~,
" I"cd
;;pe 11-29
e
• "e
~ "e
,
II
~b5
3 11
~ 1~
Days since
a.
f, ~ 7
(,/~ 3 '<) I
~ ~~
Hll4
1120
Dr:lw-dul'o II
b.
3 ' Pcrspcx-tivc \ ic.... o fthe percentage oflarul cover in Par Pond from March 14. 1l)
(R\ ISE ) was !. 0.5 pixel (:t. 20 m) for each date of gcry. All terrain > l OU ft abov e mst was masked OUI of study area. ::e C lassifica lion a nd C h a n~e Derectlu n
'ift: spec trally unique clusters were extrac ted from each of imager)' usi ng an lmcracuv e Self O'1!ani7ing Data lysis Techniq ue - ISOD:\TA (re fer 10 Jensen. 2lKJ5). clusters were labe led to produce sew n land-cove r maps cvcrull accu racy lor two of the classiflcanon maps reer 2S. llNJ . and A pril 2. 1994 ) was 75,6 percen t and - .9 perce nt. respectively. This level of ,tCCUr:lC)' i.'i abou t I ls expected from simple three-baud 2n x 20 m SPOT I_reclra l data [Je nsen l'l al., 199 5). goal of this study ..... as to document the ecological ge in vegetat ion co ver in the draw-down area, using. Iple J aIl' S of remote se nsor data. This required the usc of rnangc,(kleClion algorithm that provided "from-to" map non, i.e.. a 20 x 20 m pixel of Dead Vegetation in 2changed into a pixel ofSp ikcruch by IQ9:\. Twen ty-one ge detection map s were produced and may be seen in >tn at ai, (1 l)lJ7).
Rou lh
The percentage of lend-cove r in each category on each date fro m .\1arch 14, IW2,Ihwugh October 25, I()l)4, for the Par Pond srudy area arc grap hed in Figure 11 · 293. Th is mfo rmanon documen ts the lo ur year \ cgctation succe ssion trend s on the Par Pond e xposed sho reline, On .\l arch 14. 1991. Dead Vcgctano n occ upied ap pro ximately 35 .4S percent of the study area. The catta il and warcrfily aquatic macrophytes d id net survive the draw-dow n. Atso prese nt were 7.46 percent Rare So il and 8.74 percent ea rly invas ion by Spikerush. As nme p,b'>l'O, the Dead \ 'cgcla ti,)n areas were co lonized by other specie s. By October 25, 19(,14 , no Dead Vegetat ion was prese nt ,
Two maJ' lr types of' succevsional de velopmenttook place on the Dead Vcgel;ltion and Hare Suil d raw-down arcus. FiNI, there .... as a sig nificant inc rease in Spikc rush in 1'192. H)' \lay 5, 1992, Spi k em ~h occupied 20,2X percen t of the slUd~ area. As the so il dried out ill su bseq uent years. Spikerush cov erage declined In about 10.75 po.'rcent by October 25, 199 4 .
Spikeru...h a nd Bare Soil were succeeded primarily by O ld Fid d spl"l.:ics as t'.\p.."l·It'J. and at a Vl' I')' rap id r:ltc". Thl' most
11
400
dramat ic increase was fro m May 10, 1993 to Octobe r 2l( 1993, which sa"" O ld Field land cove r im::rC3SC from almost nothing 10 25.62 perce nt of the study area. Pine/Hardwood seedling cove rage also increased steadi ly from almost no cover in 1992 to 10.25 perce nt by Oct ober 25. IQQ4 . Irthe draw- down areas were unmoles ted to r approx imately 75 years. oollh id.ory climax vegetatio n w ould be prese nt in a ll the draw-do.... n a reas. Using the laud-co ve r statis tics de rived from multiple-date remote sensor data. it was possib le to develop predict ive successiona l moods tor eac h of the land-cov er vegetation types in the dra w-down a rea. For exam ple. Figure 11-29b ..jepic ts the act ual and pred icted pc.-rt"cnt of the scene occupied by Spi ke-rush at different dates since the initiation o f draw-dow n on June: 23. 199 1. The Spikerush success ion was mod eled us ing a fift h-orde r polyno mial \\ here %Spikc rush '" -0.0 12\)x ~
-t
0.-\0 I Hx 4 • •H19H9x·1 + 1 5 .3 H3x ~ .
14.-125x. w ith R ~ = 0.992 . U ~ i n g this equ at ion it was possible to pred ict the pe rcent of Spikc rus h thai wou ld be presen t at U'K'rspecified dates after a se rious reservoir draw- dow n. Similarly, O ld Field and Pine/Hard wood land-c over succ ess ion were modeled using the equa tions
%0 ](1 Ficld« -0.1>4 1hX ~
-t
0.6421 x4 - 3.060-1.\·1
j
5. 1495x2 •
2.32 75.\, and % Pine ,Hard wlXl(j .. O.OO76 2x s - O. 15 4 3 x~ ~ 1.097h J 2 .9 5 39 x ~ -+ 2.4909,. .
-
The: pol ynom ial mood for O ld Field ( R2 = 0.89 ) d id not e xpla in the successi on as well as the Pine,'Hardwood predictive model (I~ 2 = 0.1)4). The fi rst de rivat ive ofrhese mode ls ca n be used til predic t the rate-of-change {gradient) in perce tu o f land co ver on .. speci fic day since draw -down. The ana lysis of the land-c ov er a nd change-detection map s derived from satellit e remot e sensor data q uamu auvely doc u men ted 1) the spatia l dis trib utio n of the ..ucccssiona l cha nges in land co ve r, a nd 1 ) the rare o f successional change in Par Pond ca used by the dr aw-down . Numerous stare an d govemmcm agencies recognize the importance of ulihz ing remote se nsor data for mo nitor ing thei r sensi uve vegetation resources. For ex ample. the first comprehcn s ive inventory of the vegetation at the plant community le\'el of Ihe Everg ladl'S in Florida was co mpleted using a co mbination of ~t ellile i ma ger~y, aeri al phol<,grap hy, G PS. and G IS ll'Chnoltlg ies I Doren et al.. 1999 ).
Remote Sensing of VegetatiOn
Remote Sensing South African Agriculture
Many coun tries usc remote sensing to obtain cnucal physica l information to help protect its citizens from du ring ... ustai ned drough t. For exam ple . the Republ", Suu th A fri ca Department of Water Aff airs & F~ mandated by the Somn African Nouonat woter ..k l (1m ob tain inform ation on the sp atial d istribut ion oral! agr:~'" turc tha t uses water each year. All agricultural water ~ must become "re gistered water lIS I:I1' '' in order tn kgall)1J!i liz c the nauon's ...carce water resources. The DWAf respo nsible for conducti ng the water usc accounting lIld! the w ater Auth orizat io n and Resource Mana gement 5)!tCI ( WAR.\1S) spatial dec isio n support syste m. Remote semiIt is on e of the primary method .. used 10obtain the agri wa te r u...e into rmauo n. A f' AS A. ... ponso rcd snrdy ass~ the DWAF to de cclop remote sensing-assist ed t~'Chniqll.~ obtain the nece ssar y agricultu ral water use intomuri [ Jensen \' 1 al.. 200n ). Si udy :\na Th e siudy was con d ucted in Water Ma na gemem Area ~ Usuru and Mh lathu zc River cat chments (F igure ll ·JCl The area co ntai ns natu ra l vegetation co nsisting uf forest . sc rub-s hrub (bushvehh, non- irr igated dry land fanning. aDd irrigated agr iculture c'lllsi sling primari ly o f sugarcane lid citrus . SI'( jl" remote sensor data a nd ill .\' ;111 ground rcferm:e mformarion wen.. used to train a nd e 1a~s ify the imagL'l)'mw agricuhu ral land-c o vct classes.
Many o f the agricu ltura l fields in the U.n l i ll and Hhl
Re
Ta
nces
11-7.
• .f
Citru s
Forest
Bushveld
I :!(.I
161
0
4
n
744
F~...
13
Bushveld
"
..
)ugatCanc 0
Ubjcct-oncr ncd inmg:.: !>\:~lnent;
Sugar ca ne
Class I
401
,
, 87
,
13
n
Rood
g .1
lI'ater
0
0
Fallol"
7
,
0
,
,
4
0
0
4
4
1J411
.'1 " 2
10 1
93.55
M. 31
1I1'>.14
• 0
n
II lndbreak
.....
'_0 1&1
"
Producer's AccufaC)"
d d
{hl'rllil
0
( OlflT,fi('nt
0
o
Wat er
44
133 5
'14. 4(,
0
m
<,1).8':
0
140
h:! .14
0
'"
55.11.1
0
57
7R.<,1j
0
0
",
<)5.M
W
0
0
4"
7'1.5<,1
0
30
0
44
XIX~
sh.'l7
, , ,
0
0
4
4
, 0
User's Ac cu.. racy
Fall ow
,"
4S
Ba na n a
Row Tota l
Wind.. bre ak
0
,
10
0
0
0
0
0
00
ev
103
'0
5(1
"
so
....
26l':2
7'l h l
-o
"
72.22
n
'1.'.750
IN .-l%
83. 7 ~.
I.S itu (;rnund Reference n a ta
a
muh ispo.:dral ttn x 10 m ) and panchromati c (5 x 5 ml daw
,trrurIlC ~'
li.appll
n
0
S2
0
0
,
0
"
g
25
Ro a d
~(l()..j
D\\AF obt a ined in .Ii/ll grou nd reference info rmation 011 the l!'fI': of agricu lture present in 261Q fields in the stud y area . ~ centroids (I t" many of the fields arc ove rlaid Oil I: I 0,000 irgc·scak ort hop hotography in Fig ure 11-30 b,
The SPOT data were su bjected to an object-oriented image
Color Plate I I·Mt . The overall accuracy was ~N .4 perce nt w ith a Kap pa cccfficicm of agrccn wru of ~3 . 7 (Table 11..7). Th e use r's ,l<;curnc) tin sugarc ane and citrus \\Il'f\'l)4.4 b percern and 'l J.i'Q percent. rc~ rccl i\ cl )i whi le the producer's uccuracics were 93,55 percent and 86.3 I percent. respective ly. This lyp..' of ag ricu ltural land co ver infumuuion is uscd hy the Republic of Su uth .Africa Department of Water A ITairs & Forestry a !> input to the Watcr A urhor izruion an d Reso urce \-la na g,,'mcnt System (Wt\ R\1SI spatia l decis io n support s)sl<:m tcourte, Jensen cr a l.. 20061 .
~tat ion
classification that takes into accoun t both the and spatial information inherent in the SPOT da ta refe r 10 Jen sen. 20115. for information about obj ec r«ltTlh.:d image ~eg m e n l 'l lio n). ~lrJI
Referen ces
s
t.
A. t\ .. tlopul. s . anJ A .II . Slrah k r. 1')L}Il, ··rnrwanl and Rever-ie Modeling ofCanopy I )lrcc·li" n31 Reflectance Us.. Ing a J\ ...ural f\ ..·\" urli. ..· H",.",I.: <;,-11\/"1{ or /:.'", ',n""',,,nf_ S'IAS; ·CT
A hudgJ~jm .
!he objcct-o ricruc d !>egmentat ion classi fica uon us ing both SfQT 2004 m ultisp ec tra l radia nce 110 x 10 m l and pench ro.. ic (5 )( 5 III1data) ield cd the clasvificarion ma p show 11 ill
402
{·I! .... PH.H
11
Rem ote Sen sing of Vegetalion
R.
A
SPOT Data of the Mh lathuze River in So ut h Afr-ica
B
E
a. Part o f Water Management Area #0: Usu tu and Mhlath uvc River catc hmen ts recorded on SPOT 5 red band imagery collected on January 9. 2004.
b. Ground reference points overlaid on onho photography Figure 11-30 al ~ I'O I tlRVIR image l,f an area along the Mhldlhu/ l: River in the Republic .. t ~'lll i h Africa. 0) A portion or the :?b~1 fiddI used IV assess the agr jcuhu ralland CO\ cr classi fication accuracy em: overlaid t il l I :IO.OOl)..scak orthopb otographv IJ~ « al.. 200fll.
•
I 403
eierenees
eyo-Moy u, J. 1'.• Sa uchcz-Avofcifa. (j. A.. Rivard . B.. Calve, J. C. and O. I J, Jan ze n. ~OOS. "Dyna mic s in Landsca pe Struc1m': and Compovirion tor Ch omlega RCgHln. Costa Rica from 1%0 to ::!1I0U:" Agr,..,/lwr
106D -J9. :li. G. V. ami J. u Rok ne. 2UllS. - A l'rac uca ! Approach {or Estimating tho; Red Edge Posiuon of Pla ut Leaf Rcflcctina. - ",,1. J"lIrn,,! nl Hl'molt' 'ii,'mi"g. ~N ,\1:503-521.
Clar k. R. '\I .• King. r . V....\ gc r.l'. and (l A. Scuvzc. 1")'}5. " Iniria l Vegetation Spec ies and Scne~cc ncciS lr.·ss Indic ator Mappm g m the Sa n Luis Valley. CO . Us m~ Imaging Sp cctr omcter Da ta." /,,,,,.·,·dill!!..,. Sununitvitle Foru m; II. 1'0 ' 9 . J. Pcudc tton. a nd D. Van Iyl, II .d,.), Colorado C.eo logk:ll SlJr\'C~ PuhIiCIIlio n I'l l<. n4-1>'.I; hup :/, ~1'<'C 'a b.er. usgs.Bu' . Clark. R. :\.. S wa F~'. (i A .. wise. R.. Livo. K. E.. Hcc fc n. T. \ 1.. Kok aly . R .. and S. J. SUlky, 2Ull.1. USGS VI~il
i. G.. S and (i \k"cy. I'lM( M\1.:aO:o.:o-b-l3. lllg
Wj?e«>n. P. S. a nd \ l . E. Jen'«:'n. ] tN .\ . -,\n Overview o f 1:1.'0-
0<:\1.'1'1. J. ( i. I ~, -Imaglllg ~ll<"lmm('11') in Agricufrure: Plant \"iu lit)' and Yield Indicators." IIIHill. J. and J. \ k gi..-r 11:<6. 1./",aging ,V"-c-m",..-!ry I Ti.,,! 1''' t:""i"",,,,nu'l/ Oh"T\"
k:>giC1lI Principles for ECOS)SII:m \ 1.ma!!.:mcnt.- in Jensen. \1 .
r,.......,'
:md P. Bourgcron tEds.). £,,'''u/.' E"'HY""m /I.·..lth h
,4ppllC'alicJ/l,'. \ lIM.oul .. : U:,l> \
I'orc~l Sef\l ~e.·N -M).
. '" H. and E. Leblanc. 2UIMI. "Comr;lrinll Pr t'di cti,m Power IIlds.tabl lit) ur Broadban d and Ilypo: rspcc tral \ .... geLlti\lll Indin." rc. Estimation of Green L ear Area Ind." .md C31l('f'~' Chl"n.. pbyll Ik n, i, y.- Remo'e .'W.-""",!! of t'-m'I'''''''''''''' 7ft: I ;1>-172. Iller. Ci ,\ .. l'lq I, " rrimar~ and Sc:~\,udal) Err.... cts of the Wate r (omcm on lhc Spect rat 1{000110:0elanee o f Leav es." .~",e"i'·ll" }"urt/<1l ot Bolall l'. 7XI 7 J:'/16 - '/ 24.
(a ner. G. A .. I'N .1. " I{l",p" nso:olo of L.. af S pectral Reflecta nce III Plant SIre"." ' '''' '''it '
un.. . r.
A., (' ihul a. W. (i an d I{ , I.. Milk r, 1<1'11" "Na rrowband Rcflcctun cc huegcry Cu mpa rc:d wuh Thermal Illla!!ery for Ea rlv Detec tion "I' 1' l,lIlt Str t's, ," .10111"11'11 0/ 1'1",,, "".ni"l . ul{l'.1 4 1l :SI :'i - ; 22 ,
Cohen. \\'. B .• l'Wl, "RCSp
es In Three vtcasures of teal' Wa t ~'r EII}!III<:~·r/ll!!. J: R,'m,,'~' S",,-,UI/!.
:-'lrC"".~ "h(lI(J~m",m,'f,.i("
5712 I: 1" 5 21l2.
Collin... W.. 1<1 7 10:. "R e mote ".'us ing nfCrnp Type and \ la turiI~ . - PhtJl
II"''''.!'in: 12u-· 1.11 .
Crist. F. 1'.. I " ,"I~_ MA Tbcm.nic \h pp cr Tas seled C ap Eq uiv ale nt for Retlecran ce F;tClnr Oa l;' : ' R.-lImt~' SCII'HIj! ,,' 1;IIl"/mll m"ll/ , 17:J( Jf - J O/>. l·n s!. E, P. and R, (". Cirone. I'I H4, " Alll' lir
~1 .
and T. A , Black. 1'1'12 , " Den ning Le af ..\ rea lnd.... x for Non-fhu t.eaves." 1'1<1111. ('<,! f ,m" "'-""irnnmellf, 1;:42 1-
(Mn, T.
Ikd ,"
Pho togr'IIl/llh '!ri<' F llglII" "I"mJ; .(-
('ill' ])e-l11y~li
H,'mol.'
5;" II.'i llg.
52 t l ):Xl-l
U~ ,
~'l.J.
M.. Pavhc . Ii. Hm ..... n. L.. L'thlar. L I chl ane.:-' . U . Whil.... II. P.• lI all. R. J.• l'cddk D, R.. Kiug. U. L rro rylllo" . J. A . S" ift. E.. Van d.'r Sandc n. J.. and r. K. '.... Ilil ka. ':W02. " [krivation and Vali dathm nf( ·an ada-wid.' ( 'o ursc-rl'S'Jl ull.lrl Lca f A r...a loon \, ,,p:. U~ing Illgll-rc,olutiul1Salclli le Imagery anti (jrvu nd ' lea.;uremcnls:· Ro",,!.· S"'",i,,~ "/I.»";n",,,,,,'II. ~O: I ft ~ 1R4.
Dan, on . F. \1 , 1' 1'll<. " Tcaclnng the Phyvica l Pnn cipics of Vegl"latu m Cannpy I{dl cela n.·c Us inl! th.· SAIL ,\1n l1 e l: ' }'/W!Og m mm..·tri,' t: lIg lll" " r i ll/! J: H,'11ml<' S"II,' III/!, 6 4( ~ ) : 110 I CJ III 2.
lh ugh lry. ( . s, r.. Wa llhilii. C. L . Kirn. \.1. S.. Hro" " dl" ( 'u1>roo n. E. 'ill<.l J. E. \ k \ l unr cy Ill . :!IlOll, "E~lillla ling Corn LcafCh lorophy ll r nnccnt.... li"n fn>m I c,tf and Ca n" p) Rcllo:<:lall\-,\,: ' R~'_ ' I/I.tt! Semi,,/!. Of t:",·inmmt'lt/. 74:12~2J
~u!a.
\Ii. <.i a nd ( i A. ("J rL er. 19')2. " Idcntifica lion o f a Fa r-
Red Rdlcdann' Rc spunsc 1<> t.."c-Iom.'....'rr},i:.l(' in Slash P inc-. ~ {1r/emal"",,,1 J"ur",,1 .. rR"",ol" S,,".dIlK. ' .11; l:
[)a" S('ln. T. P. and P. J Curran. l'1'I X. -.J\ !\ c w Tec hniqu e' f'lr Inler[llliali ng Ihe Re t]cela J1e.· Rcd I·tigc P.....\lnn:· /1IIt'nlafmn,,1J, ,,,r1/<1/ vi R,'/tICJI.' S.-"WI/!, I ~ I ' I: ~ I B
:! lJ').
C1I W Tt-:H
404
Deering, D. W.. I{
11
Rem o te Se n s ing of Vegetation
Gausmann, II, W.. Allen. W. A . und J{, Ca rd enas , 1969, "R(~ lance o f ('oll,m Leaves and the ir Str uct ure." R.'ml>/r '!/ fm·mm ml'nI. I :110-22. Gi ldson. A. A., Ka ufm an. Y, J ~ Stark , R. .md D. Rundquist.
Didan. K., 2n02• .\fOOIS ~ "JW"'/I"n Ind. ,x Prod"c tion ..flgorllhm.•• \ 10UlS \'~ctal lon Workshup. Missoula. MO. l uly 15-1 8: Tcrre-tria l Biop hysics and Re mote Sensin g .'.IO OIS Team. Tucson : Univ, of Ari Tool!. _-v..n l~g.uml.<'tlw' MOI) I SConfindc\.tllmJ. ~lrcn .
R. F., Rutch...)'. R. ami R. Wckh. I'm , "The h ... rgjades:
" ~o\'e l
Aigmi lhm" for Remot e Esumation of VcgeuEioll flI
non," R.w w l .' s..'I ISIIIK tJ{ £IlII1V"m,'tII. !!0:76 · S7.
( ioe l/, A f . H.• l tN~. ~ I mag m !t Spcclrom.:lry for RcmO»I ing : Vision to Rea lity in IS Years." Frocvedingi, SPI£ na tio na l Societ y f{lf Op lic al Engine... rs. 24 ~0: 12 pp.
t\ PCI"\p«liH' on [he Re qu ire ments and Application s for veg-
e tanon 'lap and Da tab ase Products." ph ()fog r" mmcu "ie Eng l•",('ring ,,11
t>u. Y.• 1 cillcL
P. .\1. and J. Cihlar. ~OO~. " Radiom etric Xcrmalization or \ lullitl' mporal ll igh' TewolUl ion Satellite Images with Qua lity Control for Land Cover Ch ange Detec non," ReR/me S,·n.""K vi Em irw1tl 1<.·"t. H2;123-134.
Edw ards, T. c.. ll omer. (' fL Ba ssett . S. C.. Falcon e r. ..\ .. Ramst y. R. U. and U. W Wight. 19"5. Utah Gap Analys i.• : ,41/ Enr i n m m.' m ,,/ hlj"rm"'i,,n .\ n l.,,,,. Log an: L:lah Cooperative F i ~ h & Wildlife Research Urur. Mot pp.
EPA Landscape r COI'Il;Y. 2(10(,. l.amlscape Er%K). Wash ingIon: En viro nrne neal Proiec rion Agcnc ). hup-Z'w w w.epa.g ov / ncrlcsd 1rland- sc i.dcfau It, hun.
Goward. S. N.. Markham. n .• Dye. D. n , Dulaney. \\. .. Yalll!, I'N I, " ~ omla li ud Difference Vegetation Indel sure mc nts from lhe Adva nced Ve ry High ReS<.' lulion el.:r. ~ Rc''''ol t!' Se't'i" l: ul E",'irwI",..,I/. 35:257 -:!77.
G RSIJ. I tN~ , Phem ./t>J:ical C.,ft·ndan ul Se /t'cNJ C...'. Barbera: Geograp hy Remote Sern.illg Unit. G upta. R, K., ViJ3ylln. I) , and T. S . Prasad . 20u l . ~:-';ew H~~· tral Ycg etanon Char acteriza tion Parameters ." . ~Jt',mc:t'S U! ~ R" .'I<" I>1·h. :!I\(I 1:2 0 1-:!06. Haack . B. and S . Jum pol cr. l <)
Fara bee. M , J.• 1'1'l7. Pho l" .fynl hf!',l i,l , hllp:lfge ncd .t mc.ma ricopa.ed urbio/b ic 1!!I!U IO IJKi ll iolJou l.. PS .hUll I
lI alll:I.., B. and S , Jam pole r. 1INS. "C010u r Composite C~ ",'I ns for A gr icu ltura l A sses sm.. nrs." lntl. Journ al of ReIJII' S,·m IllK. t(,( 9 ) : I ~IHO-1 5 9 ~ .
Fo rm an . R. I .. l'N~ . -S om e Ge ner a l Pr inciples o f Land sca pe
Hardick y, M . A " Klc mas. V, and \1 . Smart. 1 9 ~ 3 . "Tile Infiue1lCf
and Regiunal Ecology," Landscape Ecv!"XI', 10 (31: lJ 3-1 ~2 . Fro hn . R. C . I 'I<)I( H<'I11"' <' Sell-l' ing j i,r [.
Boc a Ra rou: Lew is.
l) <)
of S" il Salinity, Grow th Form • .t ll d Leaf Mo isture on theSf'« tral Radian ce (,f Spartina Altcmif'lo ra Ca no pies," fh a'fIg_·a".. melric !\nKI IW"I"I IiX ,\, Hemo'.' S"m'III!!. ~1J: 7 7-~ 3 .
p.
r rate s, D. M.. .I, J. Keegan. J, C . Schleter and Y. R. We id ne r, 1'J()5, "S pccrrul Properties " I' Plants." Applied Opl in , ~(l l : I1 - 2 0 .
Hahoudan c. D.. Miller, .I, R" Trem bla y, N.. zarco- Tej ada.P j, .l:"~ L Dextrave, 1002. "hncgratcd Narrow- ha nd Vegetation Indim
for Predic tion o f Cr llp Clilowph yll Contcru for Applicatire ~ R,'''''''CS,'n "-,,!! '!l f:nrinmm "m. xI:J I6-
Pre ci sion Agricultu re." ~ 1 ('1 .
Ga tvao . L. S.. Forrna gpic, A . R. and U. A. Tisol , 20 05. " Dbcr im ina t io n of Surface Variel ies in Southeaste rn Bra zil with EO- I H) penon Data." Ht'm ol e Sen'ln/( of [ n vi r
Ga o. R C. I' N n. -N U WI-A Normalized Differe nce Water Index for Re mote S"'ll~ing o f vc gctanon L i,!ui d WOller from Sp ace. R"""".' s. 'm;ng 01 f) ll'i n ",,,,.,'II. 51\:257 - 261''1 .
Huang. C . Wylie , B.. Ynng, L., Horn e r, C . and (i l~ lSlra. :«I;' "'n e rivalioll of a Tass eled Ca p T ransform ation bas.:d on LandlI
7 at-satellite Refl ectance," 1."'- )mll"n
'if R,'"'''''' St-1If14
Huctc. A. R.• l'l l
F
405
~rences
,A. R. and C Justice. I'I
Goddard Space Flight Center. htlp:rm()d:lIl:h.~~ ti:, n3s3.gov/ MOL>I S 'Li\ ~D lIn: gclatio n. ind k .:.., 12'1 p.
A. R ~ Did an. K.. Miura. T.. Rndrigul'l . E. 1'" ( ;30. X. and (, Ferreira. ~OO1a. "UWr\lew of the Radi ometric and B i{'Ph y~ k al h!form:ull:e orue \ IOOlS Veg"l" ti"n lndices." R" m" lt' Srm ;" 1-:
t/£'fI";rnllm('7lf. 113 : 11,15-2 13.
Je nsen. J. R.• Coom bs. C .• Po rte r, O.• Jones. B.. Sc hill, S. a nJ D. While. I'NJoI. " Extraction o f Smo oth Fo rdg rass. I S,,
".
Jensen . J . R.. Hua ng, X. and II . 1::•.\l ack e) , 19'J7, - Rc moic Se nsing ot S ucccssiona l Cllang{'s in WeIland Vegeta tion as Mon itored ()urlllg a Four-Yea r Dra .... ,Ju.... n of a Former Coohng Lakc.- Appllo:J Gt'O~'
. A_ R.. Didan. K, and Y. Yin. 2oo2h, .\fOOlS 1'-g_'It/fi,m I'tri.,"",",p. \1i~sou la. \-1 oTJfa na , Jill)' 15- lll ; Terres tria l Hil'(' hyso.md Rem" le Sensmg nURSI MODIS Team, L'ruvcrerty of Wooa. hu p:lfuL1m.gcophy's.ulah .cd ll!d,(lt,L,.lgg5~7 modi .. '",.I. IiIlmI.
Jen sen. J. R.• Ga rcia-Quijan u. M .. Had l... ~ . II.• tm. J.• Wa ng, L.. Nel. A . L. . Tcrx erra. E. ;m d n A. Da
Juurnul 0/ Relllul" A. R.• ll ua. Ci, Q i, .t.•Cbehboeni J\. and W. l . Van Lccu .... ern. 1'l92, "Normahza li..n of \ t ult idlT<'Cl ioo al Red and jvea r-intrared ldecum:es .... ilh the: SAVI.- R"fJ/
. A. It. and 11.1). Liu. 1'1':/4. "An Errv r ant! S.:n~l tivlly Ana lof the Atnl(lspkri,' ami s..il·(\lrrccl; n~ vanams "f lhe \0" [ fo r the MO DIS-H >S.'· IFf.' " rrwI.>'I<" if>('~ ml ( ;",-,," '1.'11("<' .m Rem,,,., ,s.-" " "j!. 3~141:!I'n-9(J5 ,
s.."UUlK
"mJ GIS, 111 press.
Je nsen. J. R.• Rutc he y, K. , Koc h. ~ I , S , and S. Narumala ni, 1'N5. " Inland We tla nd Cha nge De tectio n in the Evc rg ]..d es Water Conservation Ar ... a 2A L:s;ng a Time Scric.. of Xo rm alized Remorely Sensed Dala : ' 1'lm/oK'amlll,,'r/,· f:" J("'<'I!r illJ( 4<. Remote S.:m 1fIj!. (,II ~ l : I
.m
e.,"'. R., Liu. H Q.. Balchl[Y. K and \V. J. van Leeuwen. 1'1'17,
Jensen, M . L a nd 1', S. Bourg...ron (I-.ds. l. 11,11,1 3. la'h ide F o rt'.'f E. ·VB·}I ..." ""
".-4. Comparison o f Vcgcrauon Indices ( h er a Globa l Se r o f T \ t lmagc~ for
[ OS· MO OlS.- N" """,' SC" .•'''};
"I
Environment,
19440----451. l. E. R.• Roc k, B, :-I. a nd P. S, l\ohcl. 1'111 7, " \lcasur<'mc nt of leaf Relativ e Wa ter L'outcnt hy lntrarcd Refl ecta nce." H...,11101,'
kn sen, M. E. and R. Fvercn. 1'NJ , "An Over view {If Ecosystem Man agement Prurciplcs,' in Jcn~el1, :\1. E., and I', S. Bourg" ro n (G.Is.I. Emhi,k nl1"(·~·1 1-'."0.'.1'.11" 111 (I
S,·11.\ i lljl uf Environment, 22:421 0---435.
kson. R, n., 1'/'< .\ "Sp,-,ct ra l Indices in n. Spact'. " H." II/" Io' S,' " ,illl-! "1l:.'nl'ir(lllJn<'IlI. 1J :40'! 421. son, M. \'v'. and J. R. Jensen, 20ll5, "A n Evalu ation o f n eacre Sensing-de rive d Laml scnpc Ecu luj() Metric s for Reser I'Olr Shere! inc En v ir"n m enta I Monito ring." PI",t"!:"", ,,,,, '/ri,' En~j",'e"!l,~ ,{ H...",<>I.' .\<,11.\ I!l,~. 71C 12 1: I ~ x 7 ~ 1.\'1 7.
n. T. .t.• Chell. n,. Cos h. M.• I.i . 1'.• An derson . M . Wa h hIII.C.. Donaswamy. 1'. an d E. I{. Hunt 2()(j4. "Vegetation water Ce me m Map ping usin g l.ands al Dat" de riv ed No rm.ihzcd Difference Water Ind e:>. for Corn and S(lyheans,~ Nt'''WI,' Smsin.l! nj EIIl';nmm"nI, 1,12 :4 75---4111 .
, J. R..
~OO5 ,
Rtonoft' S~n.
In/rodrt" "ry Digll..1 Inl
Jin. S. ;In(1 S , A S;uk r, 2005. "( 'um p;,ris"n otFirue Serie s 'Insscled Ca r \\ l' lness a nd the ,",ornlltli/ .:d t une r.... ne e \-l" isture InJ,,\ in D" l" ctin g F" resl Dis turbances ." N,'mol" S" /I,I'I1I1-: ,,/ E/l\' /n ll/It/' ·' IJ/, '1.1 :.1 (,4 - 372. Ju ne s. K . B.. Riu c rs. K. I I.. wickjuuu, 1. D , Tanker s ley. R. D., ( ), :-.J eil l. R. V.. Ch; II\'"d. [) .I.• S mirh. E, R, and 1\. C. Neale, I OJ'} !!. feuf,,),! waf " l ".,,'.~., ''''''If '11 /I,.. L·ni,.," SI,l/e,l: .Hid·A I /lllI fit· RI 'jl ;UII , Washin g lon: [1' ''\ . 1IJ.' p.
Kamieli. A.. Keu tuurn, Y. J. Remer, L.
,if Em '/ron -
Kau fman, Y. l . and D. Tanr c. l'ltJ2. "Aunosphcncally Rcs isl ant Vegetalinl1 [nd..., (A RV!) tor EOS_MO DIS:' IfEE TrUIl." " I/
UII
Cie" ."·I"" c" "",1 R"mole S"mi"jl. 30(2): 261-270.
11
406
Kaufman. Y. J.• Karmc h. A. ;nu l l L'I an rc. ~ I M IiJ. "Detection " f UlISI Over Deserts Us inlC S:1\0.:1I110: Oat;, in the S olar ....·;H <: I<'I1gth, : · f f f.}: Tran.., u-/;'", < (;"O"l'lf" I<"t' ,\, R,'",o", S"m mg, 3li:525- 53 1.
Rem ot e Sensing of Vegetaticn
M il/fa, l., Huc tc. ,\ . F.• Yuslm'b. H. and H_N. Holben, ~OOI. Error and s... n~l t i \il y An,L1 ysis of Atm ospheri c R~",isW.l\ . tron Indice s Dcn ved no m Dar k Target-based '\ lmospbenc rccuon.. ·· H..:" " ,I..: .k "' \ltlK ot E,wmmm, til. 71\:18 4- : 98.
Ka uth. R. J a nd" S . Th.Hllas. 1<) 76. - ne Tasse led Ca p :\ G raphi c ncscnpuon uf th e Spect ral-Temporal Develo pmen t of ' \ !lric liliura l ( ' w p s as Seen b} Landsat." PnK .·.·di" -.:_•• "'a ch ine Proc c"'inl; "f Rem "lel) SCll>.eJ [l ata. WeM Lafay cuc: l.abomtnry for the Ap pli catio ns of Ke mo!e "ens ing. -l l _:"I . Kau th. R. J.. Lambcck, r I • Ric ha rdson . W.. Thomas. G. S.•md A. P. Pentl and . I ~7~. "Feature 1-:"11"3,:1 1011 App lied 10 :\ gn c ultural C rups as See n b> La nd sat." / 'nJ<-':<'dillJ!', L \CI E Sym(JOSlum. IIl.usb ''': :"lASA, 7115 7:! I.
\k( i'1T1gal. K a n~l H J ' ta rh . 1'1'1-1. I-RAGSTtf 'fS: SI" JlIdi
A/h,Il ..., I'ttn:'
If"" e,
V<'!"'IOO I .
uma"".cdu landcc,' rcscarchJfra~ulS. faq.'f r a;!Sl.1 l>_ f3q.}D. \l~ers.
\ . I.. 1'170 . " "<>1 1.. WOl ler an d Plant Relation s." R
Dau~h try. L ~ .. C happel l<-. L W.• \ kMunrcy Ill. J. E. and C . l. Wahha11, )9
$"'~" ":I:
anon lA I':\IU:· ,'f1Jf.·.....·,l i" j!., . 6 th S~ mfl<-'!>l Ul1l ..n Ph ), i.:O£) \11:.1" ..urcmerus, and S ignOllun.~ in Remote Sensing, J anua~ 17-1 1. \ 'a l ln '-tTC'. Fra nce, 2'N _~ nf>.
(" ~ c i ll . R.
Kim. \1 .•
Kimes , n S .. 1 Q ll ~ . ~D~'na mICs olDirccnonal Re flec tance Fee.. tor D,stn hullt>n s fo r Vege tauon ("an op ICs.- 4r p/i,·(IOr ' in .
12('1/:13M ·- 1j 71..
Am h"'r
' 1'1 111 S,"""ldl R,·I.·n·"~·~· lu .l >:rI~'"IIUn: and f, " catk-Ill) of Sc i..ne e-s. 15 3-~"7
\V3sh in ~l{ln . ~ al i.'n'll
Y.. lI un" O£l cr. C. T.. k'n c".. K. B.. Riuo:rs. l\. Wick ha m. J. O. S,·h\\ ar/. p . Good man . I , A.. JJd.son. B \II S, Iia illar!:t<."{>n, 1<.1'17. ··M"nll"nng l- nvironmemal atthe Landscape S cale." R/IIS,·/<',,, ,,,,. 4 7t X\:513- 5 19..
I·..rr~ . I,'. R. an d L ~ Lauten schlager.. 1"'''4. - I' llnclumal a fcnc c ...[S pect ra l \ cpcta uon Ind ice s,- /( ,'m o l <"S""'-""ll'~ l ..in ","''''''. 14 1f>{J 11\2 .
Li. X . a nd A . H Strah ler. 1'11\:' . ... ( eomcmc-opnca l \l ode l i n~ of a C"ni rcr I, mc,t ("
l'c lcr, ,, Il.. D. l. and S, \\ . K llllnJll~. I 'Il':<). "A pplicanonsinf c'sl Sd..nee am t Man ugcmcm." in Th,',,'".l' w /(f Al'l' liruliNiI 11,,11("(/ 1 l/...,mJl(' S l'I1\ /IIK. ~ Y:
Jo hn .... iley. -I21O--4 2 ~~ .
Lt. X , and A . It Sua hlc r. 199 2. "Gcomctnc -op ucul bid irection a l
Reflectance nl, ,,Jeling
(j,'o.\ ,.;,'tI ...· I/. C"'1
30 :1;6-291..
Pierce. 1 , L , Runnin g, S , W. and Ci. A, Itiggs. 1(!QO. "Rcrn
Lunetta. It. x.. Fl1iri\\ Ickrcrua. J.. Johnson. D, /1-1.. I.Y'lIl, J. (1, ;lIld
,\' I/.em o ll' S "/I " /I/.~ , .'i h(
-" ): -" 7 II)--.~ X I,
A. .\1 cKcrw w. 1001. "I mp acts of \'q;cluti"ll l)ynami ,''; un lhc' Id" nli fic ati"n "I' Lund-cover Change in :l Biu lllgic.t11 ) C"m plex C" 111 m ul11 ly in No rth L'arolma. u s,\:· I/..-mole Sell, ill.'! l.nvi-
or
' lJIlIIl< ·/i I .
H2 :25H-1 70 .
Price. K. 1'. (;\10. X. :lnd 1- M. Snl cs, 2002. " Opti mal Llodiloll nt Hand ( '''l1lh i n a l i ''T I ~ ;\Illt Vc!!c1at ion tndiccs fur Di,;(rimi nalloo
S ix lj ra~, I'lllo.! T) P<-'. ill Easte rn Kansas." Iml. ;"",·""1,,,- R
S" II.\I"L!.1J :50.' I 5{l·n. Lynn . .I. (1 . Yua n. l r.. Lunetta. K. .... nn d C . 1>. C h an ~e l)c1ee t i~,n
F.1\' i d ~e .
b .perimcnl U..ing Vcgelatio ll
1'l" S. "A l n d ke~: '
l'I", /oK"w/I III ,./,.;,. E ll gilll ,,'r ;1I1; ,{- R,'",o /t ' SN,smg. 0-112 ): (.p-
150 .
\1 il1 ing1<>n.. A , C..
\ ·~" k/ ..l.icntlu.
.X. \ 1 ;mo.! A. \' Rr'l d k y. 100 l .
- Se a l,' 1>cpcnd c ncc in \1 11 lti lc m pn ra l ~I a p p i n g " I' t'flfCSl Fra!!m":l1\al i ~l n in Hu h \ ia: 1I1lI1 Ik at i...n~ fur E.\ plai ni ng. Te mpora l
Tre nds in
I. a nd~c'l pl"
l~ C on ~cT\ al l (ln . ··
Fc"I" IIY an d :\ p p l i ca l i on ~ 10 R iod i ~·c rsi . fSI'HS J""m
IIIO/<' S,,·mi/l)<. 57: ;S"
1'1').
("Ii. J .• Cab.. !..!'...\ I,'rall . M. S . ,mJ G. Dcd icu. I\JlJ5, "Bioph) ( :11 l'aramCI"r I-' ~ l i rn 'l t i o n ~ L! s lllg \ tu ltiJ ircctiona) Speo.:mI. ro.1<"lsu rerne nh. " N,''''0 1,' .'I,'''' m>: o{ f:" vim"",,,,,,. 5-1 :1 1 ~ j R,' nl w y.. R D .. A . LI Ie-,'na and J . R. Jensen. 19'15. - Till: R~ l i l 'n , h l l1 l\c t ~ ec·n '\ O .-\ o\_AVII KK O\I>VI an d EcoregiOll.l Il C lah.·· R"""",t<. S.·"., mll
"r Em 'in ",,,,,"," . 53: I Sl':- 19S..
A
407
ee rences
hardson , A. J, and C. L. V.' it!.tanJ, 1~ 77 , "Distin gurshing regetauo n from Soi l Backgro unJ ln fornunion." R,'m" '" Sr:m ing of t'nw'nmmenl , ~ : 3() 7 -3 1 2 .
Sa ndm cicr. S_. Mull er. c., llosgoo d. II. a nc.!
(i
A ndre oli. 1
"Sensitivity Analysi:; and Qua lit y ,\S SCS' llle nt Ill' Labo ratory BRDf Data." Hr",,, I,, S,' II.U" I! III f .",·;m nml'nI. f>4 (2 ):11f>1'i r.
chardsc n. A. J. and J. 11. Eve ritt . I'N2. " Us ing Spec tra l Veg cutiOll Indices 10 Estimate Rangeland Producnv uy." Gl:(I{'GrlO hI/I.. 1:63- 77. . ers. K . H., R. V, O ' ~ e i11 . C. T. Hunsak er. J. n. Wickh am . n. H. Yankee . S. I', Timnl1n~ , K. II Jun.... ~ anJ B. L Jackson , 1995."" Fac tor A nalysis c f Landwape Patt ern and Structure \ trnes:' /.(Im/oc" ,..' Ecol" g.!', 1 0l11 :2 3 -J ~ .
UII, G . Steven. \-to and f . BaH'!, IQ% . -Opnm ization of Soil-adjusted \'e-geJaIlOll Indices." RI'm<'! " S"n ' ;nK (~f Em'In»!_
Sa\ ils ky. fl . ( i, 1<,1 >\1,. A/trU'/(l lfC r,11 H"llIflf'" S,,"mr:;: ill S Oll/ h Cun,J",u : A 51/(.11' uf Cm p 1J,,"t t}iwliUlI CUfl
t. 55: Q5- 107.
hsan- 1.. Franklin, J . and U. A . Rohen s. 21102. "A C(lmpariwn of ~lethods
for \-ton itorin,g \1u ltitem poral V~lioo Ch an ge Us-
~ Tbcmatjc ~l appo.." lmagery... R"mol" s..'m i,,1' of Em·i,.,,,,-
Schill . S.. Jense n. 1. R.. Ralx'r a nd D. E. Porter,10().l, "Te mpo ra l ~t ooe li n g of tt ld lrt.'eli o nal Ref'lecncn I)isuihuti"n Function ( URO!') in CUi\stal Vegeta tion." GIS,: i<'lIn ' .i R..m,,!c 5.·mi ng, 4 1(2 ): I Is - u s
.,,1. 1\0: 143 ISf>.
1oo!oe_ 1. W., Haas. R. II., SchelL 1. r\. and D. W. rk~·ri n g. 19; 4. "\lonito ring Vegetation Sy stems in the G reat Pl a ins with ERTS: ' Prrn.-et'JmX.' , T hird Earth Resour ces Technolog y Sal(ilile- I Sy mpos ium. G reenbelt: ~ ;\ S A SP-3S1. 30 10- 3017 . lundquist. B. C. 2002. "Thcln llucnc e IIfl'alw py Green V.:gr:ta liun FraCliun 011 Spectral \1casurem,'nt s o....· r )\',1I i\'e Tallgrass Praine." Rl'm,,/(' S('1I.HIlJ: '!! f" n m nml'lII. I'( I : 12'J--1J5 . Ienning, S W., J ustice . C , 0 ., S"l om on ~(ln , Y., Hall . D.• Bar ker.
I" Kaufmann , Y, J., Strahler. A. II., llue tc, A. R. .. \-tllikr. J. P.. vande rbilt . V.. Wan. l. I\L Tci lkt. l'. and D. t'arn~ g gie . I'N4 , -Tcrrcsmal Remote SCI1:;inl:\ Scie nce and Algorithms Plann ed for EOS/~1( IDls," In/I, ,/"'/1'1101 ol H"fIlmt> S.ming , 15(17 }:35 l\7 - J I,:!(> , Sandmeicr, S. R.. 1'l'N , ( ;lI id<'llm ',I' "ml H,'COIIIIII('IIt!lIIitJIl' Ji ll' Iht' Use I!( III.. S,,,,dm<,ia f 'i<-'t! (lul/iulU,"a /i ". Ill.: A'ASA
St",,"i,\ SI',I"" C,'fII' '/'. Washmgt on: ~ j\ SA , 4 7 1". Sandmeier, S. R. and K. l. tuc n. 1'.l'N. " l'icit.! (juI li"mde r Sysrem (F IGOS) lo r Acquiviuon of Hypcrspcctral BRD F Data."
lEt T
Tr"n"'lCl i""..
"If (il'fJ,. ci" Il" t' ,"
Ht'''''' f' '
.'>''/1.';111:,
Sc h lc rf. \.1. and A tzbcrgct. C .. 2(1llI. " Ima g illg Spe ct rometry and Veg<'lal ion Sere ne.... - in 1"",g ilJg Sp<'('/mnWl rr Ba. il' PrmcipIe.'
Jo ng. EUs.• Dordrccht: Klu wcr. 111- 15 5. Sc hlerf, \1 .. A17hel'j,'er. C. and J . Hill. 2UllS. -Remoie Sensin g of Forest Biophysica l Variable s U~ in l.l lt y~l a p Imaging Spec t rom ctcr Da ta." Re lllo l.. Sl'II'illlf oj !:'1Il'Jr
ment of La nd sca pe Met rics for C h'lraclc ri, illg Ripar ia nStream ~ctw " lk s. "I 'I!
SC"II, J. 1\-1.. Jaco birJ. 1. ami J, E. b te~ , 1987. "S pecies Richness: ,\ Geographic Appmae h I" l'wln' ling Fut ure Biolog ic al Diver ' it)": ' H", .'l.-i,'m l' . .l 7:7l\2- 7XH. SCUll. J . M ., Davis, 1'.. Cs.ni. II., Ne ss, R.. Huttcrflcld, R.• Gro ves. C Anderson . II.. Caicco. S., D' Erc hiu. F.. Edward•. R._Llllimau. J . and R. G. Wrigh!. I'N'>. "G all Analysis: A Geographic Approach to prorc cnon o f Biological Diversity," Jl ddh le ,.\f" '/lJgmp h •. 123: 1-4 1.
371 11 : 'n K-~1l (,.
Sandrneier, S., \1tlll er, C .. Hosgood. B. and (i Andre oli. 1<,I <,IXa,
·Physical ~l ee ha llls Rls in lI ypc rspec tra lll RD F Data o f (i rass and Walerert:ss: ' R,·m"I.· S" ".\I"I: of E",·in",,,,.',,I. 61;:222·
m.
T BRS, 20tH , Enh''''<'ed Ji'g,'Mli"" /mk r. Terrestrial Biophycics and g emorc Sen., ing La b. l ;'ll\ . of Arizona, httpv/t brs.ariz ona . edu. pru1~'C\l MOIllS e \ i.php. Tow nshend. J . R.
{ i. a nd l' O . Jus tice, 200 2. "Towar ds O perat jon al \ Ionu oring ufTcrrest ria l Sptcms by Modcr atc -resolu-
{ 'IL\PTER
40B
non Rem ote '..-nsing." /let/WI.,
S"It.~illl!
/' l /-;",·;rm m,elll.
l'l3 :35 1- 3S'I.
Trull. C . I ~ _W . Luf'tbildpl.m and okologische Bcd entors chung. I I. G... [r,li.llnd.' , Be rl in : 141 - :'911.
11
Remote Sensing of Vegetation
WCIO:rs. S.• Boc k, \,.1 ,. Wi ' WII. ~l _ and (i \{o ss llt"f. 100-l. "Mappillg and lndic. uor Approac hes fur the ,\ ~ ......ssmcm oflb bit:e at Different Sca l e~ usi ng Rcm ore Sen~ing: a nd (l IS :\leth
"/,"'''''',<, h7>B ~65.
Wickh am, J. D. and D . J. "Ionon. 1l,ll,l4, " Mapping and Tuck er. C. 1~ 7 1( ",\ COlllparhun of Satelfue S.:-nsur Bands for Yegetanon \ lo nil<,)ring. " !'h lltugra mmd ri", Engin" erillg &. R,-· ",,,,,, S,·mm~ . 44 : I J(, 1O- I .lll(J.
lllg L a mbcllpc Panc ms.-
A~
I.dll'''''''''''' f.·,·.. f,,~y. 'J( 11:7-:3.
u.
Walter -Shea. E. A. and L l. Biehl . 19
Woodcock , C. 1-"., I 'oums. J. B • Jaka hhazy. V. 1>., X., \IIC
Wang. fJ.• Ad lku . " . Tcn bencn . J a nd ,\ ( iranit'T. l f)(15. -Cm tbe R...lano nstup of ~(}\'I with Leaf Area lndc \ in a Deciduous Fore st Sil c." H,"",m," E nv tronment, ')4 :: 4" :'55.
Iha.. Y , Gao . J. ~nd" Ni. 200.~ , "Lse o f ~ onna li:rro D1ffc:rs.1 Built-up Inlk'\ in AU\lluullo;ally \-l appi n ~ Urban ..\ rca, fll)lll IV Imagery." //111 J,mnl<'/ ,,/ R.,,,,,,,e S... n illg, 2-'lJJ:583-59.:
s..."""g.,
12
Remote Sensing of Water
W
3h:r cov ers ap proximately 74 pe rce nt o f t he Eart h's surface. xo.... here els e in the kno .... n unive rse is suc h an abundance of liqu id .....ntcr fo und . Almolot <)7
percent of the Earth's volume of "
31fT
is in the great saline oceans. Only
abou t 0.02 pe rce nt of the Earth's water is found in fres hwater streams. Til ers. la kes. and rcscrv oirs. TIle remaining \\ arcr is contained in underground aquifcrs (O.fl percent]. the Earth 's atmosp here in the forrn of wa ter vapor IIUMl! percen t ], and me in -cap (approxima tely 2.2 percent].
Wate r exi sts in various states o n Earth. inc luding fre sh.... ater, saltwater, '" mer vapo r. rai n. snow. and icce. Meteorologists. oceanographers. hydrolo~iSl:>. some geo graphers, and others devote their lives to mca"uring. mon itoring, and pred icting the spatial distribution. volume. and movement Ilf water as it prog resses through the hydrol ogic cycle. It is poss ible to obt ain ill snu mea surements Il l" va n o uv hydTll logic (" aler) para meten. suc h as precipitation. wate r depth. temperatu re, sa linity. \ clccity. volume, etc .. at \\:'1)-- spe cific loc ations. Fo r e xam ple. the U.S. G...-olog jcal Survey ma intains a de nse net.... o rk o f in W/l river- flow gauges on major strea ms an d rive rs that provides cont inuous r...x o rds of ri\ er stagc (hci gh ll a nd vcloc uy. Major cities and airports collect insitu precipita tion (m in an d sno w I info rrnarion. Depar tmen ts of hea lth and environmenta l control are ut kn mand ated It ) collect water-qualit y samples fro m rive rs. lakes, reser vo irs. a nd estuaries. Thes e poi nt mcasurc m...-ms arc ve ry impo rtant. If enough of the poi nt obse rvations are collected throu ghout a region. il is possi h le 10 interpolate between the point observ ation s an d infer regional ge og raphic patterns. Ijnforumatclythcrc arc usually 1101en ough pointobse rvation s to crea te a st,ltiSlically s jgnificant d istribution ma p (K r oger and La w, :!tH ).'i ). In fact. it is etten diffi cult to obtain reg ional spatial inform ation using ill .\ i lll point o bse rvations fo r a number of the most import ant hydro logic va riab les. includ ing :
water-su rface area (st rea ms, rive rs. po nd". lakes. reservoirs, an d seas). water constituents (o rgan ic
~ nll\' -surface
area.
sntm -w eter equiv alent.
12
4 10
icc-s urfa ce area.
Rem o te Sensing of Water
'I Ol al
lk>wnwell in~
Sun and sky irnadianc e
icc-wa ter equi valent.
Lf
"
rld i~ n «,
Lf' + L,r + LI , + Lb
cloud cover, prccipua uon . and • water vapor.
Therefore. a sigrnficarn amount of research has ta ken p lace 10 develop remote ~nsing methods that can o btai n q uan titative, spatia l mcasurem cms of these important hydrologic
variables [e.g., Gregg and Casey,
~()()~:
Karaska et al..
20f1.4). Th is chapter introduces the fundamental principles associated w ith remote sensing surface water and its constituen ts : clouds. water vapor, prec ipitation, and snow. II cond udes w ilh a nonpoin t source po llut ion .... ater -qu aluy study,
Remote Sensing Surface Water Biophysical Characteristics Figure 12· 1
This sect ion rcvic.... s how remote sc nJO ing ca ll be used 10 invent ory and monitor the spa tial ext er n. o rganic . inorganic co nstituen t", de pth. and tempe rature 11f wa ter in rivers, la kes. reserv oirs. seas. and oc eans. It is import ant to first ob rain an ap prcci auo n for the e nergy-ma no r inte ractions that may impact our abi lity til perform an acc ura te aq uatic remote se ns;ni; im e stigat io n.
Water Surface. Subsu rface Volumetric, and Bottom Radiance
The tota l radia nce. (/ .,) recorded hy the sensor (Inboard the aircra ft o r satellite is a funct ion nf the clc ctromagncuc ene rgy from the fou r s(Jurccs identified ill Figure 12-1 {Hukutu Cl al., 1995 : Lcglcitcr und Rubens. 20(5):
( 1::! -I ) w here
Lp is the pornon of the rad ian ce recorded by a remote sensing mstmrnem resu lting from the do .... nwetlmg sol ar (I:'o;",,) and sky (t:
Water bodies receive madiance from the Sun\f,. and atmosphere If.'.. , ). The totalradiance upvoellq (e\lli ngl from 011 water bod)' 10...ard the n.'1lIOteSCll\llr i~ a funcnon of the radiance from at~ s'·all<;rillll tL,.I.... atcr-surfacc radiance (L,\. face volumctnc radrancel!"I. and radiancefrOIlldli: bouom (/.~) uf the water holly tallcr Bukata lIN; ),
sum·
et'"
L, is the radiance fnuu the dow nwel ling so lar and sl) radiation that reach es the air-wa ter interface (somelimr; culled I IK·.II~'e- \· III:filn' lave r I'T houndary layer), but only penetrates il a millime ter or so and is the n cssl.'lttialll' reflected from the water sur face. T his re flected energy contains valuable spectral information abo ut the n.:ar· sur face charucrcristlcs of t ill: Willer body (F igur e 12· ~ at Unfortunately, if the sola r ze nit h angl e and senso r viewing angle an: almost ide ntic al. then we may gel a pure1r spe cula r re flection from the surface o f the water hody. which provides wry liule useful spectral information (Fig ur... 12-2 11 ). Sud' .mnglim is to be avoided ...hcneve pos s ible . This is why we rare ly collect rem otely sensed data at nadir within one or two hours o floc al no on .
L" is the radiance fhau rhc down welling solar and s~-y radia tion that act ually penetrates the air-water interface, inte racts with the water and organic/inorga nic co nsrituere and then exits the wate r column without encou ntering the honom [call ed wlhfllr!n("(' volumetric radiance). Thl'i radiance prov ides valuable infonnauon abou t the intc:mal bul k c haracteristics o f tho: .... atcr co lumn.
, Remote Sens ing Su rface Water Biop h ysi cal Cha ract eris tic s
a, mad-and.." hue mfr.lI'l:..J pholograph of wmcr
f'9ure 12-2
"".h.. . in FI"n Ja-
b. B1"d.-aoo..wh;le infrared J'l!<"op:tf'h with :runtltmt
or
01 ):\ blac k-arut-w hill.' in frared photograph an area in ['It,rida ." Iltili lli ll~ nat ural veg etation. a !Coif course. and fair ly deep nonturbrd "liter bodies. b) In this example. epccularly reflected ~lIn~hrn II< pre-sent tha i seriously impcd ..... ou r ahi!ily III..xrrac t usdul information, The onl) d'"la of value are the '" md-strca k paucrus \,n th......etc r surfac ... llul pro,itlc ,;
. L~ is that portion o f the reco rded mdianc... resulting from !bedown.... d ling solar and sky radian••n that penetrate..... the arr-w ate r interface. reaches the bo ttom of tile wat er bod)'. is propagate d bac k thro ugh till' wate r column. and then ni ts the wa ter co lumn. l fw c want ttl ob tain infor mation abo;lut the bottom. such 35 when performing bathymet ric tdeprh l ma pping or co ral reef mappi ng, then this radia nce trom the bottom may be of sign iii cant value [ Mumby ct al., J lJlJ7: Pnsquafini c t ul.. 19 1J7 1. Howe ver. rad iance fro m ihe bottom ma kes II \ cl) difficult to proper ly ch arac terize the water column above u. Basic
The goal of 1II0si aquauc remote "cnsing is 10 extract till.' edbncc of interest fro m all the other radiance com ponents being reco rded by the sensor sys te lll l l) t1 \a ran cr al., 2001 1. for example. the scientist inte res ted in iden li fying the and inorganic concrituems in the water column te .g., sspcndcd sediment or chlorophyll II) is mos t conc erned ';lh isolating till: subs urface vo lumet ric radia nce (I., I CI1I11putcd as: Ol"~nic
L,
411
( 11-2)
This usually involves ca reful radio metric currccrion Ill' the remote sensor data to remo ve atmospher ic atten uation (Lf.l,
surface sun-gli nt and other surface reflection IL,). and 0..11tum re flecta nce (1. 10 ) Ie .g., \t ust.u d <:1 al.. 2001 J. Scien tists interested III mOllitorin!,: wa ter dep th (bathym ctl}' ) or bottom cha racrcrisrlc s such as ree f structure arc mos t interested in prec ise measur eme nts of bouom radia nce ILIoI, so they must attemp t to remove atmosphe ric. surface. an d subs urface volume radiance.
Spec /ral Resp onse of Water as a Function of Waveleng th
When conducting a remot e sensing invesngnrion un water bodies. it is first usc fulro understand how /,un' water sclccliH:ty absurb, an d or sca ucrs the Inc ident. dtl\\ nc c tlmg sunligln in the wa ter column , Late r we w ill consider bow the incident light is affected w hen the w,111'r co lum n is IlO! pure. hUI con taut - organic and inorg anic ma terials . Pure water is fre e from orga nic lind inorga nic mauc r, Bukata al. ( l lJ'l5 j sum ma rized t IH.: absorption coe fflcic nr f~ A) , the scancnng cocffic jcm 11(;' ). and the total atten ua tion coc tficrcm ('(AI of pu re water molecules at wavclengjhs from 250 - }l(1I1 nm from a numb er ofstudies (Table 11-1 ). Several irnpurtant relationships arc o bserved when the nbvnrpno n and sca tte ring da ta are gra phed, as s hown in Figure 12-3. t.'t
12
412
Rem ote Sen sing of Water
Rerr
C).I
0.'"
Abscr-ptlon and Sca tt er ing Atten u ation in Pure water
o.oe
0.07
0,06
•
."= 0.05
""
Absorption
o
z ]
•
fJJ~
F
. E
.\
= E-
,E ~
0, 112
~
-e 0,0 I
Scattering
\
ull nl\ jolt'!
hl"1I
\'Iolet
~
dark hlue
-~
o
~\' I hl\'
Ii~ht
""
'.
.,
urun l:1.'
grc cu
"' ~ - - -
' C, '
.
l__
near -
ITOI
infrared
~ ,
...
.
2 4 (12'112~ 1) 1 1~ )12014nl~1"n.lOO420 ~n4M 4W~OO~2()~411~h ns" nl ~n'2n'.ln'h06~1)~~ 172 () 7 4' )7MI7 ~O ~ (II)
w avelen gth ( n m) Figure 12-3
Absorption ~n(1 scatteri ng of light in pure wat er, Mole cular wate r absorption dominates in the ultraviole t « 41 K) 11m) and in the ycllo w through the nca r-inlrurcd portion urthe spectru m (> SilO 11m). A lrnu,t 0111 uf the incidcmnear- an d middle-infral\'d (740 - 2~1 1(f nm) radiant flux cnll'Ti ng:1 pure .... mer body is abso rbed wilh ncgligihlc scaue nng taking place. This is whyiiiail'! is so dark on black-and-white infrared or color-infrared film. Seallcnn.: in the water column IS especially important in thev,. nlet. dark ollie. and light hillt' p ortions Ilf lh~· spectrum (41)(1 -.:"00 nm ]. This i> tilt"reu...m water appears hluc 10 our eyes. These data .... ere derived trom a \ arkt) " r sourccs by Buk,lta el al. (I IN.:"). I he graph IrUl ll'uk-:- the ah"" rrlion attenuation infomalioa In Ihe ultraviolet and m the yt'II11\\ Ihfllugh ncar-infrared regi{)n~ because the .1l!enu.Llion is "'-' gn::lI. Refer to Table 12·1fOl absorpt io n attenua tion infofm 311tlll inthe,c reg ions.
The most not icea ble characteristic is that the /t'/1,H amo u nt of absorpt ion /I11.J scanen ng of incident Iighl in the wate r column (the refore the best transm ission] lal.cl' pla ce in the: b lue: wavelength region fro m appro ximatel y 400 - SOO nm, with
the mi nimum located al a ppro xim atel y 460 - -IROnm. These: wa \ c lcn ~'1h s of violet 10 lig hl blue light penet rate funae than any ot her type of light into Ihe water col umn (C larket 31.• 1991).
413
Rem ote Sensing Surface Water Biophysical Characteristics
Palancar Red nn Cozume l Istan d . Quin la na Roo , .\ It'\ il'n
COJUmel lsIan
4. sroT Band 1 (0.50 - 0.59 Jim ).
Figure 12-4
b. SroT Band :! t0 6 1 - 0.68 JIm).
e. SPOT Udn
Individual band s of SPOT XS d;lla of Co zumel. Mexico. lncrdent green and red radian! nux (ban ds I and 2) penetrate through the water column and are reflected by the sand. bard-bottom, and Palanca r k eef C(l(l\crsdy. much of the green and red ene rgy is absorbed by' terrestrial \ .·gdalioll. causing it 10 appear dark. lt is d,ffieull III identify the land-water interface (boundary! u~mg thC!< vivible bands, Waler ah".)rb~ 81n1ll"t all of the incide nt ncar-mtrared radia m nux, while the te rrestri al vege tation reflects mcs t of Ihe mcidcm ncar-infrared ,..ner~'Y, The res ult is that waler appears alm ost black on the nca r-infrared (band J) data. \\ hilc the upland vt'gt'latilln appears " rigJlI. rhis makes it easy It> i,k nlify the land-water boundary i " SI' UT Image. lnc.].
Incident gree n and yello w light from 520 - 51<:0 nm is ah&'rb.:d w ry well by the water col umn with relatively little scattering taking place, Si m ilarly. sl"ltHe ring o f orange and red wa velen gt h ene rgy (5 fiO 740 run } by Willer molecules beco mes insig nifi cant when co mpared 10 nbso rprion by wate r molec ule s . A l n lD ~t all of the incident ncar- and mi ddle-infru rcd (7 40 - :;000 runl radian t fl ux en ter ing a deep. pure water body is absorbed w ith ncg lig ihle scaneri ng tak mg place ( Figure 12-.\ I.
m iddle-infrared regions. water bodie s appear very dark. even black. because they abso rb almos t all o f the inc ident rad iant flux, espec ially whe n the water is deep and pure with no suspende d sedime nt or organic matter in it (c.g.. Figure 12-2a) , Conversely, land surfaces an: typ ical ly c ompo sed o f vegetation and bare so il lhat refl ect significant amo unts of ncar- and middle-infra red energy. as summarized in prev iou s c hapters. Th is caus es the land surfaces to appear relatively brig ht in nea r- and mid dle-infra red bands uf imagery.
Thus, molecu lar scatte ring Ill' vinlcr an d blue lighl t-c 520 nm) in 3 WOller column and signifl...mt absorption o f g reen. yellow, or ange. and red wa cclc ugt h light (520 - 700 nm ) in lhe same water co lumn . cause purl' wa ter to appea r blue to oor eyes. T he blue color is es pecia lly evide nt in pu re m idocean WOlle r and dee p nomurbid inland .... atcr bod ies.
For examp le. consid er the green (ba nd I ). red (band 2 ). and near- infra red (ba nd J) SPO T It RV XS images o f'a portion of rhc Palancar Rcct'j ust o ffshore rho island o f'C ozumcl. Q uintana R{\(}. Mexico ( Figure 12-4 ). Unde rwater visib ility in this po rtion o f the Ca ribbea n Sea is usua lly 80 - 120 It. Incident green and red wa ve length energy fr om the Sun peneirate throug h the water co lumn and are re flected by bouorn sand, hard-bottom. and COrd i red . No te how the details o f the reef arc more clearly seen in the green (band I ) and red (band 2 ) images than in the nea r-in frare d hand J image ( Figure 12--H.
\ l lJn it o r i n ~
th e Surfa ce t: \ len l or Wal('r Bodi e'
The best wavelength region for d iscnm maring lan d fro m pure .... ater is the ncar-in frare d and rmdd je- in fra red reg ions 11 \\ a\ckngths be t.... cc n 740 2 500 nm . In the near- and
12
414
Re mote Sens ing of Walet
Reo
.\ li ssissip l)i River Delta Table 12·1.
Op tical properties of pure wmcr (de rived from var-
ious sourc es
Or
Hukata ct al.. 1',1'151.
-
Tota l Absorpllon a l i,) (m")
Scattering
bl'1
0(' 1
(m " )
{m"l
P"
2SU - Ultnl'i.l ld
(I,I~ I
(I,4)3~
U.!2tMI
va illl
J.'
"ltra'ID let
O.(j..jO
0.n 15
0.0550
l:u-utm."i<>lCl:
(!.len
oou
n,o,l:!u
(e
350 - ultr'3' k>l"'-
11.0\ 2
O.U082
0.0201
sl i
,-iok!
1l0l 1t1
(u ..~ s
(),OIO ~
~ 10
_ \1"1....
O,IMIS
0 1. 140
O,((1'lO
~u
- "olf1
U l Ml-\
{lOCH!
n oon
0 .002
0 002 7
uooo
hi ",..
(lI Mn
{I
n0 22
O.fl(IS:'
500 - ligh t bll.lC
0.Oll6
0 .0019
IUlU;9
~1n
IUII-I
f UM I ] "
OO I~ h
5-10 - I't!:'<'n
11.01'1
0 .00 14
0. 030-1
Shl l -
I.t:""""
iI,n.w
IUMI12
O.ll-l!l1
580 -
~'dl""
IUl7 4
(LOO II
0.07 5 l
nc. l _
"rd !l~l'
11.20
I HS ~l'I,\
0 11M~1
610 - " rallt'"
41.14
U OOX!
(I.24m:
1'>-1(1 - n' d
/1.27
0.\1(. 172
0.27(17
M O - ", d
0,J l 0
o.I)("IM
O. 31!1(>
I,SII _ rc d
H.,;S
I I .l K H~ h
IU S/ N,
701l - rcd
(l ,f>O
1 ),(~IO S
O.IiIXIS
7-111 - near-Inlran:d
2.2~
U.l " ~J.l
1.1504
76 0 -
ncar.infrared
2. ~ (,
(I.(xms
156W
~( H I
ncn. lI\lran:,J
2,111
(I.(XHlN
2.l ~:2ll.\
Wave len gth (n m)
.;l MI -
Attenuat ion
Th
un
m-
2( \\ w
-Wl _ ~ ~u
darl blue
- darl
on"
-
Wh ile the subsurfa ce info rmation availa ble in th... gree n and red SPOT images (ha lld~ 1 a nd ~ ) is use ful for ma ny reaso ns. it is not of m uch value whcn trying to identify the land-warc r mtc rface. i.c .. the actua l edge orthe 1.. land of Cozumel. h 1rtunatcly. the water abso rbs almost all the incident ncar-infra-
Figure 12-5
PtK\lI>gl. dent radia nt tlu x bad ; into the atmos phere. ( oe. vcrscly, rhc
Il1 llIT
pure water. farther offshore.
nt>sorhinF m0S1of the incident rad iant nux. caU>1~! il 1(, l1pp.:ar da rk. The bou nd ary I Irouu ret"«IIthc sc...hmcnl-In,!l-n " a1<,' r and the nonturhrd ....-alel" quuc e, idl.,] t (courtes y K . l u lla. !'\A:SA Joomoo Spal'l"Cl'ru" r).
red radianl nux (as shown in lig urc 12-·+0:1. cau sing lht SPOT lI RV hand 3 Sl'n,or to record oc ea n water as blacl while the uplaml vcgc tuuon re flects much ofrh... ncar-In trared radium Jlu-c. ca using il to uppcur bnght. The refo re. it isJ ,tra ighl furw a rd rusk 10 delin eate the tend -water imcrface usin g the S POT ncnr-infrured band J image. Care 11 H1 ~ 1 he exe rc ised. however. wh en lhe re arc olJ.!-anic and inorganic co nstituents in the "mer column ( c'p<." ial ~ thl'~l' IlC>Lf the ~ u rf,ll' el beca use these m.ncnuts will cause ncar-infrared surfac e rc tlccnou an d subs ur fa ce volumetric scaueri ng III take p lace, drama tically inc rcaving the amoolll o f ncar-in frared radiaru Ilu\ lcuving thc surface nf the " ;llrr bod y. FI'r e xample. consider thc Spac e Shuttle phl1lOgraph o fthe \ll~SI~s i pp i I{i\ t'r delta in Figure 11 -5. Fhe sU 'Jl""~ded sedim ent in the water co lum n o.:iIUM:) significa nt scanenng and re flect ion of radiu m nux h ick toward the se nsor S}stem, ca ll~ i n g the water III appear almost as hrig ht as the few land fcatun , III thi) bud's- foot delta.
a L
, a I
,
='!mote Sensing Surface Water Bi ophysical Characteristics
Spectraf Resp onse of Water as a Function of Organic rid Inorganic Cons tituents - Monitoring Suspended llinerals (Turbid ity), Chlorophyll, and Dissolved ()ganic Matter
Thw. far we ha\ c main l} con sidered the spec tra l response of xtosr natu ral water bodies , ho wev er. con ta in 3 of organic (e.g.• phytopla nkto n chlorophyll (1) and eorgamc l c.g .• suspended minerals) const ituen ts. Wh en natml waters co ntain n mi xture of these materials. one III' the 10>1 difficult remote sensing problems Is til disentangle it\tr~ 1"1) quantitative infon narion abou t these spec ific con!lituenls from the remotely sensed data (Doxaran et al., . 2; Karaska ct 31.. 200·H, water.
1Intt~
''hen conducting wa ter-quality studies or ll)ing
10 predi ct Iller productivity using remotely ..cnsc d data , we arc usudl) most interested in the ,' /lh.' II// tin.' l'rJ!lmwlr;c rat/iII/let" L, (Figure 1:2- 1). .... hich is the radianc c [rom the down"elling solar and s"y rad iation that act ua lly penetrates till' e-watcr interface , interacts \\ uh the wa ter and organic.ino rfII1 lC constitue nts. and then e xus th e wa ter co lumn toward §(1l -.l.l!" withoul enco unte ring the bouom The subsurface !Q/uml.>trie rad ianc e exiting the .... arcr column tow ard the ensor (I. ,) is a function of the concentration of pu re water ~'). inorgan ic sus pended mi ne rals (5 !'f ) , organic chlorophy II ~ IChI), dissolved organic mater ial (I)(}\f). and the Im,11 snount of absorption and scnncring attenuation thai rakes place in the water column due to each ofthese constitucms.
415
than I u rn in diameter. Thus. sus pended mineral concentralion is usuall y o f no sig nific ance In deep ocean re mote scns lug surdfcs. Th is is important since the contributions from suspen ded rnme rals can onen be ru led out w hen conducting a deep ocean re mot e sensing inves tigatio n. Co nve rse ly. inland and nearshore water bod ies may carry a significan t load o fsuspe nded scd imcru that can dramatically impecttbc spectral rell..x tance cha racteristics o f the wat er bodi es (l\.l iller and l\. k Kee. 10(4). .\1o nilnrillg the type . amoun t. and spatia l dis tribu t ion of sus pcndcd minerals in in land and nearshore water bodies is ve ry important. For exa mple. so il erosion in a watersh ed co nmbmes sediment loads to surface waters, wh ich resu lts in faster filling o f major rivers . reservo irs, farm ponds. tlood-cenrrol impoundmenls. a nd estuaries. Th is can shorten the usctul Iifc o f rese rvoi rs. po nd s. and flood-contro l devices and req uire dredg ing o f rivers and es tua ries . For exa mple . the reduction in storage capaci ty in rese rvoi rs in the United SI:IlI.'S caused by the in fus ion uf suspended sediment res ults in a loss \,f >$ I OO mil lio n annua lly. Sedi me nt also affects wate r quality and i l~ suitabilu y for drinking, recrea tion. a nd industrtal purposes. II serves as a carrier and storage age nt o f pesticides. ab sorbed phosphorus, nitrogen, and organic compounds and ca n he an indicator of pollution. Suspended sedimenr-, can impede the transmission of solar radi ation and red uce pho tosynthesis in submerged aq uatic vegetation a nd rt ear-bottnm phyto plan kton. T he nquar ic vegetation and phytnplan ktuu play a vita l ro le in the food cha in o f the aq uatic ecosystem .
i.1. Lc., (12-3)
krs mstructivc ro look atthe effect that each of these concurDel11~ has on the spectral rcfl cctuncc ch aracteristics o f a
water column.
\Iiner:l ls such as si lico n, 3Juminum, and iron oxidt""S an'
Fonunarely, remot e sensing ca n be used 10 monitor the suspend ..oJ m ineral concentrations in water bod ies . Thi s usually requires obtainm g in situ measurements of suspend..-d min era! concenrrauons and rela ting it 10 the re mot e sensor data to deriv e a quant itati ve relat ionship. It is good pract ice to collect bot h the remote sen sor data a nd the in ,\';111 suspen ded s<:di metl! mea"ure rnents on d"ys that have littlc wind, WindTOughe ned sur l:lce waler cre, lIes specu lar rel k elion s. w hich C:1O he dl.'1t"l.:-rioUS to lX'mOle se ns ing o f suspended sed imenl wnccnlml ion s l i la n and Rundquist. 1995 I.
bJnd in suspe ns ion in most nalural wa ler bodi ..-s. The panid~
r:lnge from lint' cla y pani....1cs (3 - -I!Jm in diameler) . to lilt \5 - 41) ~Im) , til Hne-gra in sand (-II - 130 pm ), and coarse 1f'lln ~and ( 13 1- 250 !Jill), Thl.' sed imen t wl1\es from a \ari· rty of sources including upland ag ric ultural cro pland t'Ttl~on. wellthering o f mountainou s Ic rrain . sh('reli ne eTtls ioll ClIU~ed hy nat ura l "aves or bolll tra nk. and volca nic erup101I (ash ). .\lo SI o flhe suspe nded m ineral M'd iment i... co nmltr31t'd in the inland and nearshore Willer nod i"'" ( Bukala eul.. Il)IJ5). ('kar, d.:ep ocean (relcrrl.'li 10 as Case I water ) f.u- from shore rarel) conla ins suspendtXI miner als gre :uer
The spcc lral retl eetance of su"pcndtXI sed Iment in surface .... aten. is a fum:tio n of both the qua ll1ily an d ch ar:J.e teristi cs (pan ic le ~izl.', abso rplion) of The ma leria l in the waTer. Sus· pcm h.'d s\,d inw llt co nce ntral ill n is lllea sured ill sifll us ing eilher a secehi tJj.,k l'r a nt'phcl t'll\ etrie turb idit)" un it (N TU) detedor. Th c seCt-hi d isk ( Figure 12-0 ) is a c ircu lar plale that i ~ lo.....ered in\ll the ..... ater unt il it eannot he ""'en. T his secch i deplh is ill\C'rscl ) eorrel at~d with the amount ofsuspendC'd m;uerial in Ihe w" ler. l1lc greater the amounl of suspended
( 'II,\I' IE K
4 16
12
Rem ote Sensing of Water
Spt'cl r nr a d iOIll\"1 1'1'"
T
16S cm
Figure 12-6
A sccchi disk is used ro measure suspende-d sedirncnt In "";Iter bodies b) l l"'• ..:rmg II uuo rhc water co lumn and dctemu mng tho;' dCf'lh al which II disappo:M!>. Tbc .I.:c ur:to:y of the measurement is it Iunclion "f the v"ual acuny " I' th..." ,,1> serve"1". '" hicb can ' dry d rama tica lly.
Figure 12 -7
A "!'L-':lruradi"rncIL"( may be used 10 mcasuremllll <['l"("lrdl reflectance characteri stics of pure \\1ICI' dOJ water \lo llh l an('us sus pen ded >
1'1'-171.
material. the less the sccch i de pth. i.c.. it II ill d isappear [ W ill view rr-lntivcly quickly. lhis met hod relics on human visual perception . which is no l con-aam among scic ruisrs. The more rigo rous nephelometer detect or pa"scs light through it sam ple ofwater oh tamcd at vuriouv depths to . . lctc rr ninc its transmission characteristics that are refuted III suspended m ateri al ill the water, Research has documented (he gene ral impac t of increased suspe nd ed mine ral COIK' ClI (H1till ll in wate r bod ies in the visi ble and ncar-infra red portion of the spe ctrum. For cxnmplc. co ns ider the expe riment conducted by l.odhi et a l. (l l)\)7). which dete rmined th... spect ra l reflectance characteristics of lWO Nebraska so il type s (d ay ey and si lly) ut \,aTlOUS suspended sediment concentrariouv III water. Figu re 12-7 depicts till' e xpc rim cnta l d es ign .... here a spectro radiomerer was used 10 collect spec tral re fl ectanc e data fro m a he ighl of 165 ..:tIl dir ...ctly above a cont rolle d wate r sur face . T he spectral rn ca surcm cms were made in 15 2 dis c rete spectra l ha nds between Jill, and 1.11~ nm. T ill' spectreradiometer \HIS calibrated with a gray card ( 18 percen t rencctc ncct that lIas cross -refe renced to u BaSO~ calibrauon panel. Rc tlcctan ce. I'll" \13'. calc ula ted as a simple ral i" us ing the c...uaucn I Markham and Barker. 1986 1:
/. , -xl.. I.,
(1 2-11
wlt{·r..-[., is rho rad iance measured from the ....-arcr surface.I, is the radiance fro m the Ib S()~ panel, and k is a calibratice factor for tile lJaSO.1 pane l (refer ro Ch apter 15),
Fip lrcs 12-l\a. 1I depic t the spectral refle ctance o f cleat 113\('( and wa ter \\ ith varying suspended sedi ment couccmrarioa o f clayey nnd si lty so il. Sp ect ra l refl ectance o f the clear water drops continuous ly a fter about :'i !\(J nm due to ahsorption in the water COI UlIlll. as previously desc ribed (refer ttl Figure 12-."\ ). As the suspen ded sed iment conc entr ation is increased. re flectanc e increases at a ll wavele ngths for both clayey and s illy solls. T he c layey soi l (Figure 12-lla) h.1J mo re organic nuncr and w as darker in co lo r. ....hich resulted in app rox imately 10 percent lo w er vo lume re flectance at all wave leng lhs than tho: liglu-culored s illy soi l (F igure 1 2- gb~ Reflecta nce inc reased in the 5S0 6 1}(1nm region and in the near-infra red regi on as more m inera ls .... e re suspended III the \.I ater buJies. T11/1,~. fill' [Jl'llli. retlectonce .I[urn toward longtY wavctongths ill the visible ft'gi"" as more suspended .wdi· m(''''~ lIrt' U,/(/I'd. " lo re green. red. and ncar-infra red l1KIiJ1l l1 u.\ is reflec ted from the water body and recorded by tbc remote sensi ng ~ystl' m ... \ wate r body with suspended st\fi.
Re<
417
emote Sensing Surface Water Biophysical Characteristics
, "
clear water
1., T------~
u ...
41)0
~VI
500
5:;(}
IiOO 650 100 .... ,, ,,,length IJlm l
i~
~10
ll~
I.OOOmlPl
t
""
me m in it will generally appear brigh te r in ima g.cry than a nea rby wat erbod y without any suspended sediment. Correlation cocfficicms lr) were co mpu ted ttl descr ibe the relationship between suspt:ndcd sedimcm concent ration a nd !be re flecta nce at eac h o f the :!5:! spccuul sam p ling po ints. For the cl ayey so il. the values ranged fro m n.2X- tJ.97. and
for the silly soil. the runge was n.7x - ().II X. For borh soils the \ alu~~ of r .> I).'XI oc c urred in the ncur-inf'rurcd region betw een 7J.l and XXO om, .Is expected (I Ian and Rundqu ist, l'N 4). Th ese resu lts
su gg~'st t hal :
418
(' lI A I' 1tR
12
Remot e Sensing of Water
Re n
c;lrl
Diat um
ther
as chlo n ' p lasl ma te ria l
wh hm
set ,0<
•
_ - - cell wall
de.
inl
eh
,rr re ca
Figure 12-9
Oil A micrograph " rhlu~' rCn L'CI"d lig ht fwm,) phnIOS)lI\n.:sizi nl! d ia\tlm r ) A micwgrarh .. r hluc n: n ec'l...- dIight froma ~ algae .:<.'1 1( Jflr ""'f"r/,l\ .p_l_ 1~ chloropla-" l mat crra tm tho,> rente ShO.'"S up in da rk II e,; beca u.... the chlorop hyll a pigmell .jh",.,.h much (,f ' l1<: mci..k ll1 blue light d uring phorosyn tbesis,
" ic
d. T
a the \ isible wa\ c-lcngth ran ge of ; :\11 - (,911 nm may provide
infon nat ion on the sur face \\ .ucrs: and
~11Jt·
ofsuspclldcJ sedi ments (will in
the ncar- infrar ed wa velength range o f ? 1" - IlM) nm ma y hi: a use ful \\. ;lld,·nglh ran ge for determining the lIIIIO/III' orsu..pendcd minerals in surface warers where suspended minerals arc the prcdomiuam consmucm.
These rd atilln,I'up' milY nnt be universally applic able. Scienusrs attempting tu remotely sens e susp ...-ndcd sediment concent rations should im estigatc the spectral absorption and '\c;lt1l'ring cha racte ristics o f the water and soils in thei r geographic area of Intere st.
the visible reg ion (e.g.. (,flS nm). They sugges ted thaI ... stutl) attem pting to mouuor suspended sediment usifl! remote se nsing sho uld he ba ..cd on a thor ough kllOwlcdgcaf the panicle grai n si/ e and composiuon hc ing examined Miller and \k Kee (~OIl4l found a robu st linear rclation.-mp ( R~ = 1I .!\~1 between MO DIS b and I (o2() - ('7(J nm)l5()x
250 m data and ill »n u tota l suspended sediment measunmcnt s in the (j u ll' of ," lex ico. C h lll ru p h~ 1I
Plankton is the generic term used to describe all the Ij\ing and :Illirn;t)) present in a water body lhat ca nno t resis t the current (unlike fish). Plankton may be subt)rgal1islll .~ I plant
For example. Dux aran ct
divi ded further into algal p lant organisms (phyt/lflll1llklOn~ animal \lrg all i.llls (;;/lopl.lllkllllll. bac teria (/}(/c1Cri(Jp!lInl. /m l), nnd 1o"" cr r I:1111 fo rms such as a lgal fungi , I 'h.r!op!anl. /011 are sing k-ecllc d plums smaller than the size of a pinhead. Micrograph-, uf the blue rad iant energy rellet:tcJ from a dknom and a single cell or gree n algae arc shown in Figun: 12-l)a.h, In both inst anl'es, the chlorophyll a pigmen b ill the plants absorb most of the incident blue light cnuving IhL' photosynthetic portion of cuch to appear dark
Similarly, Binding et al. ,20IlS) foun d thaI the successfu l USl' (If Nl R wavdt:ngths for meas uring ,uspl'nJed sedime nt was d<:p<:ndcm un tho: filet that in highly turbid v.ah:rs then.- is su fticicnl scattering to m l'rcome the strtl ng ahsorpt ion by v.;Iter at these wa \dength:. . In less turbid w
stances that contain carbon. Phytoplankton sink to the OCcall
Ph) toplan knm , like plants on 1;IllJ. arc composed of subor wate r-bod y tloor when they d ie. Zooplan kton migr:lte K\ th.: ~ urfaee al nigh t tu Icell lln 1ivo: phytoplan kto n and tkn sinl to great er dept hs du ring the da y. When :zooplankton die. the~ a lso silll to the hottom. carT)' ing Ihe ir ca rbon \\ ith lhem. Tho: carbon in the dead phy topl anktoll alld zoo planlton is S()(ln C(lvcred ll) othl'r sclliments. Also . phytop lankton usc
•
IT
C
r
4 19
emote Sensi ng S u rface Water Bioph ys ic a l Cha racteristics
n dioxi de and produce ".\)gcn during the photosvnic process. In th iv way. rhc water bodies a nd OCI:',tO S act a fjlrh""l i"I.. 1I place that dil-il"l-c~ of g toba l carbon, kh orhcrw isc '::111 accumulate in lhe unuosphcrc :I~ cardioxide. Other gtoba l sinks include land \cgel,ll ion and I. However. the carbon III Ihel-l.' sinks frellllcntl) IS cd III the atmosphe re a~ carbon dioxi de hy burning or mposuion. teo o ne knows cxactly how muc h carbon the and water bodies and ocean accumulate. Alo suc h. the actcrisucs of phy ropla uk ton and Illuplankion an: \ cry IIlJ'OfUnl 10 o ur knowledge of the glohal ",11*,,)0 cyclc a-, 11 esems a s i~ni l1cant carbon 101IIk tor inereJ.M:d levels of D dioxide in the atmosphere (Bu kal a o:t al.. 191);).
4
Ih ,nl'r la nl·.· " r C1t'ar and ,\ Iga.'-I;u lt'n " ah'r
, -' >
~
">
25
" ,
~
>
'"=0
:E'"
( "lear \\:ller
+
U
05 AI phylllplankhJn
III .... urcr btllhe!>
cem.nn the photnsyntho:t-
Il~ active p igment o:h1,'rof'h~ II a 110\\ ever. chlorophyl l r ,
m even c ma~ also he rT'l."S<.'1l1 and at \ arious depths. are 1.... 1' othe r ph)'tup lanklUlI pllt'II",~nthcloi/ ing ~b: nIlVlt·//oi.l.l' and I'lryn>hilim . Bukara ,'1 al. (l iN;) ~ I:'\l. however, that chlororh~ II " ma) he considered a !J:a. mable ..urruglll,· fur rhc organic C\lmpOIICJlI of op tically mmp1c:l. natura l \\o atcn•. Fortunately, because diffe rent IHloI:S ph~ lop la nkton have differen t concemranon.. of chtoro~11. thl:'~ appear a!o di fferent
colors III scnsi uv C remere senThus. recording the color o f a ll urea of the ocean or (lhcr water body allows u-, It> esumatcthe a moun t and genealtypc ufphytoplan ktun in umr urea and Id b u.. abou t the leaIth and chemistry of the water body. Co mpari ng images uken ut different times Iells us nbour changes rhar occur .' \ ..r arne and thc pr'lCt.'~s":l-
'DtIOWl'hyll t,rplillll OI' h1IIC lighlht.'IWl,'';-11 ~ 1l11 and SOli JIm: chl orophyll II ab->tlrpliol\ 1'1' red appw xlmalely n 75 nm I ( j ild o;l'n. I 'N;! ):
• ,Irung
lighl
at
• rcncdancc llIi1ximum :lrllund 550 nm (g r.·en pc'lk I l:,IUs,"d br n:laril'l.'1r lower ahsorplio n of green Iighl hy algae iGildsoll. I IN;!);
II 4
25
>
~
;;
~
•
'"
•,,
soe
~" .\ Iga t"-I:ld e n \ \ at.. r with \ ari"l1 \ SIl..pe nded S.:d iment C "nr l'nlrllli{tll'
'"
soc IJ\~ 1
" 10
~
; /
500
b.
(,I~ t
70(1
SOO
lJ(J(J
Wave length 111 m)
"':l-
Figure 12-10 :'I) 1"'rn 'T11 rcllcctnncc ,,( clear aml ~l lg "e·lll d c l\ tcr t>"".:d on 1/1 ., i lll spcct romdiomc rvr measure11l~1l1.
hI
I'e r~·,· n l r<'ll~·,I;\ nc ....
" I'
h \ ,lri,'us ....1'nc"lllr.lli"ns of ' usl....ndo:d ,cdim cnt
\I' it
rllnging l'nlill 0
5nn I11g/l hl1.:r lIan.
1 1J~ 7 ).
pwminclll rcllcc lanct: pcak armllld 1',<)0 - 700 11m ClllI""U and a mi nimu m "u mbincd d 1l.."cl uf pigmclll and wato:r ahsl'rpti,'II. T he height I' f lh l!' [1<." lk aOO\l: \h,' haseline (;IhSl}rptio n ITfl ugh ) ea ll he u..... J 10 ,Iccu raldy m.... llloUro: ch lorllph)'ll a moun l ( RUlldllU i~ICI al.. 11)1)5). h~ an intn ,Klioll I ll' alga l-cdl scallcr ing
HlI..i<:all), 01.. ,'hl"rt'ph)1I ,'o llcO:lllr,ll lUIl i no.:rO:;ll>O:~ tn Ih..: \\alo:r cu lum n. lho: r.... is a sig niticall1lkn~·ase tlllh,· rdal i\ c
420
C" II-\P" l t :lt
amou nt o f energy reflected In the blue and red .... evctcn grhs. bUI an increase in green wa vele ngth refl ectance. When both suspended min era l sedime nt and chlorophyll an.' pres...nt in till: wa ter body at the same lime . a dramatically d ilTerent spect ra l response is produ ced, f o r exa m ple, Figure 12- 1tlb demo nstrates w hal ha ppe ns 10 the spectral response
of water as red lI...m sediment concemranore, from 0 - sou mg.'l an: added tu water tha i nllliains alg ae (chlorophy ll
rrom 5~7 nm (green light l al 0 mg. l to 5% om
(o range) at SOO mg I.
Rundqu ist ct a l. (1 1J96 1 and IIl1 n and Rundq uis t (1 91)7 ) obt ai ned accurate estimates o f alga! c h l ll ruph~' 11 pig ment
amount in surface water using a simr k ncar-infrared 0 0:; nm ) 1 red (CJ70 run ) rat io when the conccmration ofchlorophyll .... as rela tively low. Com pc ung the first dc rivu uvc uf re flec tance aroun d h'Xl nm produced the best results when a lga l ch lorophyll co nce ntration WOi~ re lat ively high. Chln rop hy ll in Ocea n \ Val er : 11 is assumed that a remo te es tima te of near-surface chloroph yll concentration consnlute-S a rem ote esurnatc of ncar-surface biomass tor prima l) producnvityj fo r dee p oce-an (em: I) wa ter .... her e there is liulc danger o f suspended minera l sediment comatuinarion. Nume rous studies have documented a rela tionship hctw cell sel ected spect ral hands and ocean chlorophy ll co nce-ntrati on (Chf) using the- equation Ie.g, Gordo n et at. IIIX3 ):
( I:!-5; whe re LO'I) and LfA: ) are the up.... ell ing radiancl.'s al selec te-d wa \ekng lhs rccu rded by Ihe remote sensing sysh.'m and ,\' and y are empirica lly de rin'J constant" Bukata ct :II. ( 1995 1 poi nt Illit tha i this approach docs Il ll! tah' intn acc uunl lhe absorptiun and M.:atl cring chanu.: teri~ lie' 0 1" lhe inorganic an d 0lli an ic CI'lh tituc nl, lIf lhe stud) ilrea The only reason it is <,ueces...lul is that 1ll the m id-Ix' ean , l'hlllWphy ll pi gme nt~ ilre lhe princi pa l co lo rant Of C b e- I "atef"O. Salel lite remOh.' M.'flsing syslems used to measure ocean eol ur are summari,t...-d in Table 12-2 . Tho:- l'PCral l. mal a lgnnt hms used 10 e:\t ract phYlop lilnkton ab undance info mlatioll fro m severa l o f thes e satel lite remote s('nsinl,! sy"tems are summarized in Tah k 12-] . lI 11p...fully. the upna liol1
12
Re mote Sensing 0 1 Water
IO RRI\ 1.-\GE, lnc. ) to bu ild o n wha t " J ~ teamed U~ iDgtb: ( 'oastal Zo ne Color Scanner. Sea WiFS has additional b.mlI ill 4 12 n111 (In ident ify yellow substanc es tilrough t he lr ~hl wa\ dcnglh absor ption). at -190 mn (to increase ~ l' ll ~ i li vityll chlorophyll concenrration j. and in the 7(,5 and ~ (> 5 nm na· infra red no assi~ l in remo ving atmospheric anenu auom Hecause of the role of phyto pln nkron in the global em cycle. SeaWiFS data arc usc,d to a~ses.... the ocean's role the global carbo n cycle and to ex amine ocean ic (J..1vrs atfect g loba l climate cha nge ( Pink ert on et at.. 2005). <:;a. Wif S data an: used to ide nnfy the mag nitude and \ anabllily of the an nua l cycle of primary prod uc tion by marine pbJ. topta nkron aml tu determine the distr ibution ond timing 01 ~ pri n !! bloollls. The obscrvauon-, help sc kn lis!s u nd~l'li!Jnd the dYl1 illllie s Ill" oc ean a nd coastal c urren ts. the physks ol m ixing. ami Ihe re lationship.. betwee n oc ean phys ics and large-scale paucm-, (I f prod ucuvuy. Sea\\ 'if-S research mcorporat...... atmospheric correc tion mt improved ill}!:orithms applied 1\1 ocean imagery, The ltll.ll. impo rtan t SeaWiFS operational a lgorith ms. involve ue ee ofband- 4-1 .'- -I'-IlI. or 5 1U nm div ided by the hand at 555nm (I"ahk ~-3J (F'll kll\\'s ki et al., IYt,lX: Pinke rton t't al.. 2005 For exam ple . consider seve ra l ex amples o f the oceana llpplicat illll' Il l' Sc-a WiFS datn in Color Plate 12- 1. The tiT>l image is a gllllxd map o f chlorophyll a der ived from a compo snc of imag es obtained from Septe mber ]. 199 7. throog!; December ~ I. 1\)\)7 (Color PI:tIl' I 2-l a). Th e next imageisl true-color composite ofa portion o f'thc ea stern Unncd StaI<5 at a spat ia l res..lution of 1.13 x 1. 13 km (Color Plate 12-lhl 1 he true-color image i.. a color cornpos ue of'ba nds 670. 55' and -II:! nm (RG BI and hlllhli ghts veg etation as>tlCwtll .... ;th land morpho logy. Wh ile area... ilre elllud s and dense a<,"fOsl,l s, ('ol,'r Plate 12-l c ]lres~'nt s the chlorophyll o COlIl"Clllr:ltilllh on September JO. 1'197. Rl.'d collie'S reveal high l'lllwl' l1 lrat ions 0 1" chloroph yll. yd lows and gTl'cns inditalr ink rnlt'd iate co ncentr at io ns o f l' hlorophy ll. and blues and purples d, 'CUl11ellllllw chloro phy ll eo ncc- ntra tiolls . rang ('I a l. (:21)(1.') found g'-.od agr~mcnt wi th SEAWiFS dala and ill .•illl ch lllTOphy II 2()f) m ) w as 27.7% with R: '" 0 .71. eompilred tv .U % R ~ I S log l' rTOr and I{ ~ '" O.6Ih ear the cua"b .
R
T
42 1
mote Se nsing Su rface Wat er Biophysical Ch ara cteristics
12-2.
Satellite rcrmuc scnsillb ~}Sl<, rn~ U~L-d to measure ocean euler (courtesy of Intem;llinnal Ocean Colour Coordinating Group. hllp:llwww.l<)Ccg.0TW'><:ns
Sen so r
I
Ag e nc y
Satel lite
Sp atia l Res olut io n 1m )
Number o f bands
,
Spect ra l c overage (nm)
rzrs
NASA \ USA )
Nimhus--7 IUSA )
I Oi24 '7S-Q6l22,1l6
1115
ecrs
?\ASll (Japan )
xoros (bp;tn l
es- t 71'%-0710 1V7
ADEOS (Japan)
0&·1 7rw,..n7101,V7
'000
",
411:!· IZ500
CNES (Frnlltt)
"'"
DI.R W c rman}')
IRS P3 (India)
Launch 03/21 91>
suo
-Wli-I600
NASA\USA)
OrbView-Z
Launch 0810\/97
1100
OCI
"' IT (Japan)
ROCSA r - 1(Talw ;ml
Launch 01'W
l<2 ~
OC\1
ISKO tl ndia)
IRS-N (India)
Launch 05126iY<}
3"
" , ,
~IODlS-To:rT
NASA tUSA)
r.,rTU (USA)
launch I2IUi'Q<)
1 5fl1~ 001 1 000
OS\U
KA Rl (Korea)
KOM PSAT\ Korea)
l aunch 12f10i y<}
1!50
\tERIS
E...SA 1Europe!
ES V ISA f · 1 [Europe !
b unch 03/0 1'()2
) 00 1100
\IODIS-Aqlw
:"lASA tUSA)
tlqllo(USA)
La unch 05104-'02
oronts
CI's S·\ \China)
xhen l ..hou-3 IC hina)
eOCTS
C\'\5A IChi na)
Ibi Yang- 1 (Chin a)
ell
('\,\5,\ (China)
llai Yang- 1 (Chi na)
0;
15iO~_WI~5 i03
250
(;U
NASDA (Japan)
AI>EOS-ll (Japan)
11,'14/0Z-I 0125/03
250/10tlfl
CNES (Fruncc ]
A1>EOS-1l (Jupan)
12, 14!O~ · 10,25103
6000
""""·1 ~IOS
)eaWiFS
Pt,lder-.2
The primary insrrurncm for ass,,; ~s in g (}CC,Ul product ivity on Ihe EOS Terra spucccruf is M ODIS. MOD IS bands X - Ill, r!nging from 405 - '(1, 77 nm at 101 11.1x 1(1)0 m spatia l resoluuon. arc particularly well suited 10 the collection o f" infbrmaion on oc ean co lor, phytoplankton concentration. and hogeochcmistry ( ~ I O IJ IS, 200(,). Ti.'n·u I'I l () DIS produ ct numhcr l\10D .2 I , parameter numbe rs 26 and 27 (C hlor_a_2 md a_3, respectively] can be USl ' U to extrac t Chlorophyll a eeccrnration informal io n from Case I and Case .2 water ising the algorith ms fo und in Table 12-3 (O' Reilly cr al.. ~)()(); Card er ct nl.. 2002 : Darccki and Stramski. 2(114). A IMp of the chlorop hyll 'I dist ributiun ulong the so uthern Lnncd State s on Nov.. . t uber 23, 200 3, derived using the MODIS Ch]('r_3_2 a fgonthm is shown in C o lor Plate 12-2.
lnfon una rely, 0..'\ en these algor ithms semcnmcs have diffi erlry ex tracting c hlorop hyll " inform mion from o ptica llycomple-c water such as the Baltic Sea {lIarecki and Strarnski.
l
Operat ing Oate s
8
Jf>
4.l3·12500
433·910
«e.sas 433-IZ500 401·885 405_1 43s5
•
«o-soc
Z50f.'iOO/\OOO
,."
4 12·10."0 405- 1431!.'i
113 lSf02-O'lll .'i112
400
J4
403- 12500
Launch 05/ \ 5102
1100
10
402- 12500
,.
421l..Kl/ CI
, ,
375-12500 ~4 .1 _9 1O
20(4 ). Maruorcna and Siegel (20ns ) presen ted a W:lY to merge satelluc OC<:11I1 color da ta streams From MO DIS "no Se" Wi!'S to improve global daily coverage infor mation. C h lo ro p h}'11 in ('n:ls l ;l l ll nd In lnnll " 'ntl'!": For inland and nca r-coa sta l wate r hudics , i t is ofte n difficult to discntuug fc
the Information about the phytoplankton pigrncnrs in the rem ote sensor data fro m the c uecrs of sus pended ino rganic materials or dissolvcJ org anic maucr (DOM ). T h is norm ally requires the lI SC nf sop histicat ed atmospheric correc tio n technique, appl ied to the re mote sensor data te.g.. Ram sey et al., 19921 and a complex multi ple-co mponent extrac tion
methodology t c.g., Bukata cI nl.. 1')1)5 ). For example. Karaska et al. (20114) docume nted the usc of Airborn e Visible.l nfrared Imaging Spectro meter (AV IRIS ) hypcrspcctra l da ta to map chlorophyll
12
422
Table 12 · 3 .
Rem ote Sen s ing of Watar
S...leered opcrauona l hand-rollina lgorithms for remote se ns ing ph)10pl,m kltln abundance . Algorithm
sens or and A lg orithm
OCTSc s..'aOAS 4 .3 C hi _DC"'"
C"
(O.S SOOl>' M'l7RI .[0
"
References O 'Rci ll}'':1 al. I
h
ere
Pinkerton d at...
R Sea V.W:o. UC: ~ v4 Sca OAS 4 .3 c h l_......2
r
R l490I] R - lu!! w Rr- 555 L
S..:aWiFS 0 ('4,4
n(
)
"hcr.:,, = [O.J J'I. -1 .J_~t>.H.1I7" ..0. I J~ . •(1.011 1
O"Rcillyo:taL .
Sl.-aIlAs-J.3
c
chl _oc4 chlo r_ 3
R "" llI '
"
fIIa.r I R, (+*3). R (4901. R (510I J]
.
'
~lU [
' S
R (<;55) .
"
o =- IO.J66.•J.007. 1.930. G.o·N. -1.Sl! 1 O-Rdll}.1 al.,~{((r
....IOOIS D ,-\.\C-V4 C hlo r _1I_2
.... Iorel and Anloik 2000;
(based on Sc'aWiFS oc, algon thm wnh modified band s)
"as '" L __,+I _ '_) und r J , /.(551 ) .
=-
Darecki and S:,'1lIlIski.100·t Pinkerton et 31.. 2Q(\\
L(448 ) L( 55 1)
where ' '1. ·1..J.U.l J ....10 1)15 UA /\ C· V4 ch hl r_ \ 10 Ul S
\tOlll S Il\:\('- V4 { -hlu r _Il_J (fo r ('a"" I und (',I": 2 wlllcrsl
[0'
C" '"
c
C1~f".
",,[_ L=(..,'",, ,, )]-IAO -: ""
D Jrc'd;.i and SU1lIlI-
"
,, - [H.2IN.
ski. 2004 : Carder <:1 ,11.. ~()(l:
-x.z, 1.2J
~klrcl
MERIS-C
l oon
[ R" I'-")]
R '" !t)£111 Rrs(SOO )
itT.. <: L then ~ ,=4.B and a .. [0,1. J 15, -1.1.; 44. 1.21': 1.. -2.747. 2.S65. -1.2(l4J. if 1 ~ C.. 5 10. then >..u=.4')O and II = [O.311Nl, ·2.020. 2.572 •• 7.15". III IS. -0,S95J.
if Ca > 10. rhcn 1,,)>=5 10 and a =- 10.390. -3. litH, J.I MI. -20.33. 63.2 I. ·11 J.'l].
N .\S n \ l' rnCI'""r C hi"
c:" R
:JX~
L" n( 550)
ESA "' rm' \'~ ,ur c'nu
liLl O(' . H .iLl
I'/
Pinkerton el al.,
,
""
(/~
I0"
+
"'10[
I OI "" - " , H ~ " , R · ~ ,, , f/
,
)
where
lII m l /".. ~ ( -1 'B ) , L..,,( -160 j. L ~ ,, (S2 0) 1 ]
1... ~ ( 5 -1 5 )
(05 12. -3.(.5. 4 ,45:. -2..175. -ll,167J
31\(1Antoine.
, te se nsing Surface Water Biop hysical Characteristics
ssotved Orl:an ic Ma lt'rial light pe netrates into the wate r co lumn a certa in photic
, h uhe verti cal distanc e fro m III.: \.\ atc r surface 10 the I t subsurface irradmn ce le\ el} , Phytoplankto n w ithin phone depth o f tile \.\ ater co lum n con sumo: numerus lind vert them into organic maucr " ill pho tosynthesis. Thisis jed p rim m ')'1',.".Ju("li(", . Zooplan kton cat the phyto plan k-
and create organic matter. Hactenoplankron decompose m.s organic mutte r. All thi s conv ers ion introd uces Ji.HO/I'l,d Of!:mlic malleI" ( DO I\l) into oceanic, nea rshore. and inland Iller bod ies . In ce rtain instan ce s. uicrv ma y be su fflcicm dssolv cd organ ic maucr in the wat er 10 reduce the pcn ctra lion of light in the wat er column (Buk.1l3 et al., 1 ~ 5 ).
The decomposi t ion of phytoplankto n cell s yields ca rbo n ecxidc. ino rga nic nitro gen. sulfu r. a nd phosph oru s co m;JOOnd~. The more product ive the phy topl ank ton, the greater tile release o f dis solved organic matt e r. ln add ition, humic J~b,'/aJIC{,S ma y he produced . Th ese often ha ve a yellow rppearance and represent an important colorant agent in the laler co lumn, .... hich rnay need 10 be taken into con sider Ilion. These d issolved humic substa nces are called vetto..... ~lonce or Ge/h.\ /olJe and ca n I ) impact the absorption and lQtlering of light in the .... arcr column. a nd .::! , change the color o f the wat er. There arc so urces of d issol ved organic matte r other than pIly1 op lan kton . For exa mple , the bro wnish-y ellow color 01" 1M water in ma ny rive rs in the nonhcm United Stares is due LO the high conccmra uons of tannin fro m the eastern hem Jod ( I ,f uga c(IIICld(·1/.~ i.~ I and va riou s other spec ies o f trees IlId plant- gro .... n in bog s in these areas [ Hoffer, 1971\ ). Ibese tann ins can cre ate pro blems .....he n remote se ns ing eland wate r bodies.
Water Penetration and Bathymetry
423
ope d a special wutcr pcnctnuion film in the 1970s thai was sensitive to the wavele ngth interva l OA4 - 0,54 urn anc r tiltranon. Tlus infor mation was also used when sped(ving the blec-scns iuv c band (OA 5 - 0.5 2 pm) r>1I the Landsat T hema lic M a p~r se nsor sys te m. ....hich is o nen ca lled the water pc netranon band . If the .... atc r column is exceptionally clear, it is pos sible to see subsurface features to a depth of 10 - 30 m by :'\.' n ~ing in these .... a\ ele ngihs. Bathym etric mapping in the 1l.4 ~ - () , 5~ u rn port ion o f the spectrum requi res thatthe wate r be almost free Irom org anic and inorganic ccnstuucnrs such as c hlorophy ll and suspended sediments thai ....ould cause sca tter ing and/or absorpnon to ta ke pla ce and obsc ure thc bonom topography. 1I0 \\ <:\er, as dem on strated in the Cc zumel. Mexico, example l Figure: 12-4 J. even th e green a nd red wavelength re gion arc o f vafue tor water penetration when the water is clear. But what happens whe n wa ter is not clear? Perhaps the blueg ree n portion o f the spectrum may not he the mos t ide al region to usc if the water co nta ins s uspended sedi ment. Lcglcitcr ct ill. (2004) do cumented the effe cts o f cha nnel water de pth o n remote se ns ing refl ecta nce (Figure I.:!· II). They found that at wa velengths <560 nm. remote se nsing refl ectance from the bo n om substrate increased as de pth increased from 5 to XO ern. Conversely. as de pth increas ed . the remote sensi ng measu red refl ec tance in the red and part icularly the ncar-infrared spec tral regions decreased du e to the slWllg ab sorption by pure wate r as previously d iscu ssed . A crossover ponu of equa l re flectan ce for all dep ths separated scanerin g and absorpnon-dommarcd reg ime s [ Le gleiter c t al .• 2IJlM), Based o n these results, Leglcit cr ct al . 121)(M ) found that thc natural log o f the simp le rat io of t....u ban ds o f hypcrspcctral dahl center ed on 560 nm and 690 nm correla ted well w ith stream wate r de pth (wd):
... d = In[/. (5 60 )] . Bathymet ric ma pp ing can be pe rfo rme d using passive optical tc.g., aeria l photograp hy} or act iv'e re:motc scnsing ~ys lClllS. MO'it g..'O~ph iea l1y e:\tcn~ i v e and aeo:urate bathymetric o:harting is perfomK-tl us ing act ive SO :'liA R t\\hich rellcets S('u nd wa \C~ o tr the Otl!tom ) and L1DA R (which rd kl·ts laser light o lTl ho: botto m ). Balh)-nw lr ic :\lappinJ: SeI1VillJ:
I :~ i n ~
P:", i\{' Optica l It e mnte
The opt imu m optical wavel en gt hs to ornai n t>a thymet ric (depth) informatllm arc from app rox imately 0.4-1 to 0 .54 ),Ull based on Figur e 1.:!-3. In fact, Koda k. Inc.. seicll1 ists dev·c!·
/. ( 6 QO)
( 12-61
ac ross a broad rang e o f strea m conditions ( R 2 = 0.79). Th is techniq ue oUlperformed th e line ar lrans lClnn me thod used in h l ~!clrical ro.:nWle sensing b
424
n l \l"
t: rr... d .• " r\\ al l'r n cprf u n lh e "tt'mul e St'n,i ng R... Ifv... tan...... of a x rr eam ( "hannd
enu O.O I ~
"k
0 III
- _. 5 till J c plh --- 2U em _••.'/1 em ····· 50 cm 65 ~U crn
'Ill
~:H
,
Remot e S e n s ing of WOller
sendi ng acoustic puls es via it tran sducer. The ,lcoUSlic llu!sl:l arc reflected h) the sea Floor and the reflected echoes n rcccivcd by the transd ucer. I'he elapsed time belli-em ou tgo ing pulse and the retu rn echo can be used to accUI1td determin e depth , There a rc t h ree main IYflL'S of SO"lAR'i!" terns { ~ ()A A e s c, 2UOf, j : xinglc beam
o
12
S() ~ .-\ R:
~ O.OlJll
o
~
~
mul tiple beam SO ~A R:
o.e.. 0 ,00'
.,-jJ.i:: ->~.,.
'"
O,OO:?
5 em
Pcnph yt.... ... INr.au SaI,""'n1 c.--..nl,. .....
W,IId >f'C"'l 5
,no'.
side-scan SO;.JA K.
'-. ~o .
' m, L \"."
Smg h '-hf!l1m S(}',,"--fR-~ usc a transducer th at em its a s.i~
sound p ulse into the \\ are r co lumn at s pecific intel'\'als'll a narrcw acoustic footprint (F ig ure I :!·I::!). Th e ~OUnd"'i~':
reflects o fft he seafloor (or fish !) a nd the return is capwml R gur e 12-1' t he ... nec ts ot warcr d,,..lh on remote se'flsi ng retlec1aIl<:<: from a ~lf("am channel. This particular a ream ch annel bonom substrate .... as covered with Peripb)1011 'a curnph:\ lIIalri, of alga... ami heterotrophic microbes attached 10 submerged mat erial in almost all a'l ual1c l."\:,,,,y~kms) which has a ,uung absorpl ion f,'i\IU!'t' at (>7 5 r un. The stre am ....arer contained ap proJHmaldy 2 mgll llf suspclH.kd scdrrncm. 1'\, .1<,:th at as,h,.. dep eh o (lh,' wat er inc reased truro 5 10 llO e m. the red and ncar-infrared re flectance fm m the Y" Il~" column dcnc;l'...d. Conversely. as the deplh uf the W ~ ler increased. Ihc greater the reflecta nce from w avc fcug ths -c ;(,.0 nm. A reflectance crossover occ urred at epproximatcly .'\hOnm ILcglcite r cl a I., :!OO-\ : reprinted with pcnnission fmm EI"",'i<:rl ,
Wh c n cond uc ting bathym . . lric surveys using photog rallllllclric techniqu es. it im pon :llll to l:lke il1!o :lCCO U11l th e t:1Ct th:ll lhe light from Ihe Sun is hen t fro m lIs trul: Cll ur~c in holli lhe atmosp h....re and in the wa ler ....Ohllllll. ....ausing balh ym .... tri.... (: 1 in format ion in the im:lg('I)' 10 /l ll ' h(' in ilS pro per pl:lnimetr ic (x ,l 'l po silion. Th..:refo re, ll1e ind.... x · (l t~ rcfnl cl i o n pr....\i ous ly disc uss....d in Cllilplcr 2 mllsl be l;lken imo ....onsid.... ration whenever ren1\)te sensi ng n1l'thod s arc used to pe rfo ml bathym .-trk ma pp ing .
Balhlm('trk I\lappl n::: Using . \ Cll\ (' SO:'llA R TIle a.... ronym SO ~ A R ( SOund, NA vigation and Rang ing ) is a n Am..:rica n ll' nn tirst lIsed in World War II. The Brit is h cal l SO NA K, AS O le s (A nti-Suh ma rine lklL"t:tion 1m eSligalitm (olll minee ). SO ~ A R tCl'hlltll(lgy may b<: us..:d to collect measurem ents o f the scal1oor. When ac tive SO ;.JAR is used 10 l11ea sun: the d islall....e to th.... tll.lllllm, it is lnll" n as I'clw ,\ fJI l11d i ll};. Ec hu S\lunde f1i, arc uSt.'d to measure wa tL'r deplh by
hy the transduc e r t~O :\ I\ esc ::!006}. Smgk-a SO~ :\ R data arc collec ted along transectlines and t~ p~ ca nnot provide co nnn uous coverag e n f'thc seafloor. The: put resolu tion (,I' the da ta a rc determined b) the JCOJSJiI.' foot print SiLC. s;lIupling inter. al, sam pling speed, and diIta nce between transects . Single-beam se nsors may colko f>alhyml·try dina (lr he calibrated til idL'ntify seafloor habllA fish. or subsurface sedimen ts. Many of the systerm .-r dL'signed tn he l'asily transported a nd used in small boats thlI can access shallow areas. Recreatio nal fisherman use rdauvcly inex pensive single beam SONAR sys tems.
Htdfl/,le' '' ,'dm SO.YA H\· pmvide users with twn kinds of data: bathy mctric (depth I and .. ucoustic backscatter" (Gard· ncr. ::!on::! ). T hey can he used in extremely deep water (up10 11,0( 1(' Ill ). ' I ' h e~e sen st' rs rmit multiple sound pul~ (b.. . ams l that cov cr lar ge overlapping swa ths of the scallooL .:-nanli ng cnn ti nunus CnVl'f:lgc nf the sca llnnr, The backscat· ler sig nals 1.'(111 be IIsell for ha hilllt o r fc,llure mapp ing. Mu ltIp le heam ;!c('Iuslic Sl'\lS(lfS arc Iyp icall y mo unted onthe ship's hu ll. Th e ,onar s<:It,], a t:lll o t"sound energy to\\ aldtht s....a tloor. tlK'n re....ord, thl: re tlected suu nd th rough a set of naITO\\ rece iw rs a imed al d il1"ercnl an gle s ( rigtl~ 12-12l. 1t call delec l feillures as sma ll ;I S o ne meter a.... HJss and ]OCJlt lhe m 10 wilh in u ne m.... t.... r o f the ir true geographic location ( NO AA Olli e~ ('I f Coa:'lt Sliney. 2(1)0 ). Fnr example, 1M K\lIlgsbcrg EM ..002 multipk b<:am echo so unde r has I n"min al frcl.j uc n.... y l,f 300 t.. 11:.- wilh an angular eo\ m gr he lllw the ship 0 1 ~ 2 00~ and up 10 50l( ac oust ic soundings jl\:r p ll1 g as narro w ;I ~ I J e);:ree (Kong sb<: ~ , 2005 J. Aehie\· an k S\\ ath " iJlh (lli a nat OU!lOIll is nnm lJ Jly up to I0 ti~ thc water dl'plh_ T he sp.1c ing hclween sound ings as well as lhe ilcoustic 1lltltp rinlS l"an ~ sel nea rly co nstant over the
te Sensing Surfac e Water B iophy s ica l Characteristic s
425
Side-scan SO'.jAR.,
SO ~ ,\ R
H ath~ m t'tr~
S .n,l~ am
SCl"M R
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• '9Jre 12-12 Single- and mutuple-bcam SnS .,\R s. A Singlebeam SO;";A R Imnloa'l \ <'1" ...."tId~ out a singh: puis.<: ot acousnc ,,,,'und ) ,'n,'fS) usually dir,-ctl) beneath the boar. The acoesuc enefl!.Y trefcrr curo as a p mg l is rclkct.-d oITthe ""Ullin (or any intervening (ll>jecl - uch as II ~hl ...1 u f fish l lind IS reco ....kJ by the tran sceive r, It is then I'"ssi t-k 1<> de tcrmme lhl.' de pth t{llal}!<"1~ ha....'u I.. the pubc lu return to the surfac... an d a knowledge ufth e speed of "",,00 In wa ter \t Ulll pk -w m ~( ) "l ARs transrmt n};lIlY beams per ae{lu"tk ping Ie.g , > 5001as narrow as I degrl:\"amle:lnk(l,·rlr:tel..nf~xllell) \\hen lhey encounte r the bou.eu torother features in the wate r.
sanh in order to pnwid c a unifo r m and h igh detection and lllJpping pc rforrnanc c . An acoustic im"b'c o f thc sea bed fkor can a lso hc produ ced fnnuthc da ta (Kon gsbc rg. 2(H15 ). Color Plate 12-3a dcpict-, thc shaded reli ef bathymetry of lake Tah oe . C;ll iforni a·N c vada. It W
to as tow - fish ). Th ey arc use d pr imarily for searching for a nd detecting objects o n the sea floor, nOI for bathymetric mappin g. The to .... -fish SO:'>lA R points multiple bea ms ar ang tes and covers large overlapping swaths. ena bling cont inuous coverage of Ihe: seafloor. The rmn smin cd energy is funned into the shape o f a filii thai s.... ec ps the sca noor from direc tly un der the towflsh ro cn ncr side. Like ot hcr SOf\A RS. a side scan transmits sound ~ nergy and a nalyzes the return signa l [echu ) renectcd oil' the sea floo r or other objects. The st rengt h nfthc retu rn l....ho is continuously reco rded creating a ' picture' o f the ocean bonom where objects t hai pro trude from th... bottom crea te a Jar\.. image [strong return) and shadows from these objects arc light area s (little or no rerum ). Wh ile the shape: uf the seafloor and objects on it ca n be well depic ted , most s id...-scan systems do nor pro, ide depth informatiun . However, the y can be deplo yed in w at ers up 10 I I.tJ()() l11... tcrs deep and pro vide data wit h a resolu tion of a Ie" centimeters.
Bathymet ric information can he accurately extracted usin g UIJ..\ R ( L,g ht Detection An d Rangi ngl remote se nsi ng (re fer to Chapter 10 fllf iufonuauon on terrestrial U DA R app licatio ns) , Gucm cr ct al. ( 2f1nO) provid ed a detailed h istory of airborn e U DA R bath ymetric ma pp ing . T he Scanning Hydro graphic O perationa l Air borne Lidar Survey (SHOALS ) system is the most adva nced airborne U DA R bathymetric nl
( 'I IAnt:R
426
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Si multancoue tran smi~~ ion of _
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Rem ote Se nsin g 01 Water
ta l pmi litJn acc urate 10 J m and a vert ical position aeeum to 15 em. SI IOA LS is man aged by the Joi nt Airbome Lss Bathym etry Techn ical Cen ter of Expertise bused out ofQr US Army Eng ineer District in Mobile . A labama . An eumpic o f SI IOALS ba thymet ric info rmation is shtl" n in ( iii Plate 12-3a wh ere il .... as used 10 co llect 0 to 15 m bathYIl'l!ric data of Lake Tahoe.
metry Airbo m c UDA R bath ymet ry overcomes the limitation> acoustic ISO 'lAR ) sensors in so me key areas :
Xcar-mfrared
surface return
I
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,
Airborne LID.-\R
';
ncar-intirated 110M nm) , rn1 green (SJZ nm) .~ J'ul~ loward wa ter bod} '
-
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12
-
II pe rform s especially wel l in sha llow wa ter where ro. mig ht run aground.
WaleT
,~ Green ,,-bonom return
-
-
Bol ,om
Figure 12· 13 Airt>omc lIf)AR hal h) 'rnl.'t r)' sen ds tw o lase r pu lses [ncar-infrared and l?fe..;l\ I IUWMd the .. aler at cxa...' t-
Iy the same instant . The nca r-infrared pulse is refleeted from the water surface toward the U DAR rKCI VCI. TIle green pulse penetra tes into the water co lum n. lf the wah:r is clear enough ant! the dep th is nottoo great, a pt.rtion of the gr
near-infra red surface return and the green bottom return and (he speed of Iight in a ir and water (Guenther t' t a l.. 20(0 ), Terrestrial L10A R s)'stt:ms send out > )(}O,OO{) pulses per second ty pically with a 10 nanosecond pu lse length. U [)A R bathymetry systems operate ;\1 a much slower rate. c.g ., I,GOO pu lses [i.e.. sound ings ) per seco nd with a 250 nano second pulse lengt h. The longer pu lse length is necessary because a short laser pu lse would be scaucrcd in the water column (O ptcc h. .:!O()tl).
The SIIOALS system ca n surve y up to 32 km 2 in one hour, at an a ltitude of .:!OO 10 -100 rn a bove sea level (A SL ) with speeds up to I I S kno ts. Th e S ilO..... LS sys tem. depe nd ing. on ahitude and speed. i" capable o f co llec ting depth S(Jundings on a -I m l:! rid . Using a kinematic global posit ioning s)"item, SHOALS references eal'h depth mea.,;un:mt: nl to a horizo n-
It allows surveys of hazardou s coastal areas Ie.g., •• high "urf) 10 be conducted in com parative safety . It is mobile, allowi ng rap id res pon se in emel]m.'
situanons, Large are as can lJC' economic adv antages.
inventoried quickly
pro\-~
U DAR an d SON AR harhyrncrric mapping co mplirn
bathymcmc map ping in shallow water em ironmcm wherea s sing le rm d muluple team SO'lAR are useful fer bathymetric mapp ing in ime nucdiate a nd deep watcr.
Water Surface Temperature
We know from Chapter II (T herma l Infra red Remote Sen.. ing) thai we may ob tain the temperature of inland ....'ater bcdics and sea-s urface tcmpc ruturc (SS T) during daylight hOOT> and nt night using thermal in frared remote sens ing ted!· niqucs. Unlike land surfucc s. howe ver, water bodies Iransfer energ y primarily throu gh ...onvcction. Therefore, any helt enc'r gy introduced into the system may he transferred hUlldrcds ormeters 111\0 the wa ter body. T his mix ing is rcspons. blc for the relat ively un i form surface temperature of a ",am hod y both day and nig ht. Thu s, water bodies generally hal'( hig h thermal inertia. mean ing that there may only be a few deg rees diffe rence bet.... cen the daytime and nighttime wa ter-surfa ce temperature . T his resu lts in water bodes uppc ariu g rela tive ly cooler than the land during da ) Iighl hours
F
427
eaote Sens ing S urface Wat er Biophysical Cha racteristics
Sea-sur face Temperature Maps Derived from NO AA AVII I{R nata
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12·14 S...a-surface temperature t<;ST) maps derive d from a threc-day co mposite 01 ' OAA A\"HRR therm al infra red dal3 cent cred on \'I,lTd, -I. I'J'N. Elich pi... .:1 .... ;0' alloc at..xl the highc,1 scrtace rcmp...· r..turc lhal occurred Ju ri n~ lh..: three J a) s. a ) This ternperature "':II' has Ixx-n adjusted In highlig hl the coo l water adj acent 10 the fkorg la and Snulh Carolina coastline. b t Th is map has been adj u, l"d Itl highlighl the circulation pauc rns 4'''''CI4k'tf wllh the .... an n «tl shorc ( julf Srrcum. A color com posite of rhccc imag", lh ;lt pro. ides addiTion:.1 infor mation is found in Color r l ;l k ' 12·4:. I":"U("-S) ~OAA I
measurem ents becaus e the (0.:11I011: sen sor rad unu remjeraturc measurement ( r "h l ) is approximately equal 10 the l\I~ kinetic ternpcrtuurc II j,,,l, assllm ing the ct fccts of the m elting uunusphcrc arc accounted tor. [I is important III encmbcr, how eve r, uiut it is only a surface mcavurcruent. If ibere is a signilie;Il11e hmlgt.' ill temperature just a lew me ters !l:low the surface (i.c.. a thcnuocliuc l, il ma y Il o t he de tected i!' the therm al infrared detectors. Ire
~' O of the mos t importam rhcnna l in fra red remote sen sing ssuumcnrs used III measure sen-surfac e tempe rature arc nd on the ;.,lOA,\ Adva nced very High Resolution Radi~e(er (AVI IRR I and the :'\I()AA GClIl>latilll1ary Operational Iavironmcnta! Satellite (G() FS I. Their spa tial. spec tral. a nd enporn l characte ristics arc sumrnnrivcd in th e pte r 7, Datil ium these sensors i ~ in the pu blic domain. ava ilable at a reaenable price , and are used ht.':lVil) to ob tain sea -surface eopemturc l S S n rncav uremen rs ove r la rge oc eanic surbees usu ally at a spatia l reso lution of > I x I km . For exam~. SST m ea sure me nts o lT the so utheastern CI>.lS t of the lniloo Slates ot>t3 i n ~'d o n :\la rch -I, 1 ~, hy thc SO:\ ,-\ AVHRR arc ShO\lll in Figure I::!·I -I and in Color I·[att.' I ~--In.
The SS T imat!cs depictthe co ol wate r adjacent 10 the Gcorg ia and South Caro lina sho reli ne ca used hy the influx ofcool wate r from me major nv crs . A lso note the location of th e warm Gul f'Sucam \~ indin~ its WII ) northw ard from the lip o f Florida a!l'llg the Eastern Seaboard. Tang er al. (2003b) c xanuncd lU M ):\ !\ ,\ Vll f{ f{ therma l infrared images to monitor the tempera ture chnractcrisrics of the thermal plume 'lss,'c i;ll,'d \\1111 (hi lw's first nuclear powe r station {Dayn H
A g tobal sea-s ur face tempe ratu re (SST I map is sho wn in Color Plate 11-4b. It \\ :IS created using day, n ight f\OAA - 14 thermal dam collected fro m xfurch '1- 13, 14'1
428
up .... ann surfac e water in (he .... es tern Pac ific. 'i(l thai the sea su rface is about 0.5 m higher ncar Indones ia than ncar Ecuador. SOUlh America. The sea-surface te mperature is a lso abou t ll"C highe r in th... west. Cooler tempcrauues exist off Sou th Am e rica due III un upwel ling of cold wate r from dee pe r levels. T his cold water is nutrient-rich, sup port ing high levels of primary prod ucti vity. di verse marine ccos ysIl' J11 S. a nd major lishc ri...s. Rain fal l is found in rising ;Ji T ove r the warmest water. and the east ern Pacifi c is relati vely dry . Every t w 0 to seven Yl'an, the trade ....'tIU.!S relax in the ce ntral and western Pacific Ocea n When this occ urs. the ocean currents an d w inds off'the .... es tern coast o f South America shift. brin~ in!! warm watcr east wa rd, di splacing the nutrie nt-rich cold w utcr that normally wells up fro m dee p in the ocean . Th i.. invasion of wann .... ater d isrupts thlo mari ne food chain and the economics of coastal communities. Fisherm en named the phenomeno n EI Nmo (the Christ Child ) because it oc curred du ring the C hristmas s...aeon . Thus. EI Ni no is characterize d by unusuall y ....arru oc ean tem peratures. especia lly in the eas tern eq uatorial Pacific Ocea n. La Nina is churuc tcrlzed hy unusually cool ocean hcmpc rutures in the equatoria l Pacifi c Ocean . Tree ring ana lys is has doc umented that these southe rn osc illat ions are not new. hut ha ve been occurring syst...ma rically for more than a hundred ) C;J P.; (NOAA. 1999).
EI 'vino can be seen in measure ments of the sea-surface temperat ure . For ex ample. Color Pla te l:!· 5 depicts three different sea-s urface temperatu re conditions for selected Decembers : a La Nina in ItJH loi. a nonnal mon th in [9
C11:\PTF:R
Remote Sens ing of Water
of \ ery small reservoirs. lakes. ponds. ctc.. then infrare d sensors Jlo wn on suborbita l mrcraft Im)< ~ req uired . An exam ple of using an a ircra ft-mou nted thalli infrared r nuhispectral sca nner to map the rcmpcranre wate r in the Sava nnah River is fou nd in C hapter 8 IThaml lntrarcd Remote Se ns i n~). P re c ip it a t io n
Precipitation may be measured operationa lly on a locaI« regional bas is usin~ ground-based (terres tr ial) active mi.:nlW3\(' remote sensing . For e xample, the re a re more tIw1151 Ne>;t tiencrauon Radar (~EX RAD) W SR, /iJoi D s~.-TtII (.!"'Crating: in the United Stares tr-;OAA ROC. ~OO5 ~ lk ~E XRAD antenna is enclosed in a rado mc ( Figure 12-15al and e mil!' a bu rs.t o t'microw ave energ)' 0.. " 11.1 em}. If_ ...ne rgy strikes an ohjec t (raind ro p. snowflake. hailstooc. bug. bird. etc .). the energy is scatte red. A sma ll fraClioo et The scattered e nerg y may he directed back toward ibe radJr antenna. Co mputers analyze the strength o f the rctumcl pu lse nncasurcd in decibels, d I3Z ). the t ime it roo k to tT'ilvd til the object a nd back. and The dopp ler phase shift ofth: pulse. T his proc...ss of cmuting a pulsed microwave s i~ lisll' ning for an y returned s igna l, then emitting the neu sig· nat, tak es place very fast. up to a pproxi mately 1300 1lIDtl each seco nd. The maximum ran ge o f th... radar is approllm;Jtc ly ~50 mill'S. ~EX RA D functions in t w II modes: ctear air mode andprrd l'i/llfjo/f mode. In Clear Air mod e il produces an upd:uct ima ge every 10 or I I minu tes. In Prec ipitancn mnde il ~ duces an update d image e very 6 minutes. In both mode, wha l is important to loo k ...t is the level of rl'lk e ti\ity metsure d in dHI.. The slronge r the retu rn. The highl'f the dBl .1II C1car Ai r 1l1OLk, the sca h: gucs as lOll as -2 8, which is \lhy~ is [lossihle to occas iol1ally detect dust or pollen in lhe air, 10 Precip it,u illl1 mode, lhc sc all' goes as hig h as 75, whichindic-ales Sl'verc weather . The rclk c tivity info rma tion is used111 ma ke preei pilation ma ps . Fo r (".'(amp le. a map of precipilltil)n in S,)uth Caro lina on July 30_ ~IKI5 . at tJ:IKI p.m. produo:cd fwm l\:EX RA D WSR· S8D Prec ipiu tio n modc &u li show n in Figure 12-1 5h .
Weath...r Sen icc Forecast Olliecs use th: WSR -S8D s)'stems to provide re...l-lime infonJlto tinn (lII lhe location o f dangero us \\eather and the amounTof precipitutiun. In Ihe UniT...d 51;lles. T hc Wc;lthcr e haMcl use s NEX RAD in!\'mKltio n to pro\ 'idl' n ·... I· time local and reg ;lllw i weather filrccasts. Sim ilar systems function in Eu rope (I3agd la et :l1.. 20(5 ), J"ationa l
When h igh spiltial resol ul ion sea-sur fil...e tcm pc ralurc dala is needed, it may he possible to usc Landsat T hem at ic r.lapper (T M I data. For cX
12
~r:XRA D
Precipitatlo n
429
.' EXU." I> 'te r rcstr ta r Remo te
St> n~ i n ~
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NE.XRAD pn:dpil.l.lion milp OfSoulh Carolina ,>NalllC:',J OI l 'I ( ~) r Ill. un Jul~' 3H, 20ll S.
-gum 12-15 01) .\ :!s n , d iamete r \:C\ t g"''flcl'illiun Radar ('EXRA Oj .... "atho;r raJar anlenna i~ hUU'i<:tl in side a protective 30 ft. diameter spherica l radome suuaied un a IflO It . tower. In precipitation mode. the volume scan of the radar i ~ co mpn sed of 11 lu ll 3(,00 sweeps at nine uni'luc d C\i11;OO angk... tbctweeeu 0.5" and 19.5o i1oo\e the 100; 011 huril lm). ' I,XR..\O data is updated e\'L"t)' 6 numnes when lhe radar is in precipitation mode. h I Retlectivity pre..·irntatl"o map "'uUlh r'arohna Mlai nl.'d from the :'>lEXRAD in Co lumbia. SC. ob tained on J ul ~ JO. ~OOS. "ilh II>.: :"l I:.XR..\ O \\ SR-lum III precipitation mode. The reflectivity data .... en.. pnll:e~Sl'(t 10 hlghlil;'! ht prec spitanon associated \\ llh a "'-"\ ere thunde....torm rll~,ing from wc~t 10cast. Intense thundcrstonn precipitation is highlighlL"d in .... hit\.'.
or
ntonu nutcly, the maj ority of the world's land sur faces do "I enjoy such coverage h) weather radars or t' \ en rain
'Pu!;!.t' networks. an d will no! for the foresee able future. ueteorological sat ellites arc the o nly systems capable of );Ijuirin!;!. rainfall data over \ a~ 1 dismnccs. Fortunately, it is JlOII poss ible III moni tor selec ted continents on a contin uous jesis and to do so for a sl11:l11 fraction Ilf tllecllst ofa sur facebased observing network or eqllival.: nl spat ial density ISmilh et al. . 2004 ). Unli.1J1U1111tdy. ins tead of direct ly mea1IJring rain fall usin g a ra in gauge. remot e s~'lls i ng methods mu,t rely on using indirect remotely sen sed data o n cloud eflcctunce. cloud-top tempe rature, and/or the presence of fozen prccipuation nlott to est imate the surface rain rate.
Visible - Infrared Technique s
The earliest prccipnarion esumarion methods were based on die assum pt ion that the hrig htncss o f refl ected sunlight in the vsible and near-inf rared port ion o f the- spectrum fro m doudsmigh t gi ve an indication of'their thickness and thu s of tbcir likeli hoo d of bearing ra m. Un fortunately. nOI allbnght douds produce- prec ipitation . Sirmla rty, the te mperature of fie lop of douds was USl.-U to es timate prc-cipuauon. G cncr-
ally. the colde r the cloud top, the grea ter the likelihood of precipuauon, Unforuuuucly, not all cold cl oud top s prod uce
prccipiunion. Neverthe less, some very use ful precipitation csuuuuion k' l'h ni'll tl'S were de\ c lnp'..d based on visible and in fra red d.ua, inc lcding I ) twice-dutly esuuuues o f ou tgo ing Iongwavc rudiution from polar-orbiting infrared senso rs onbonrd A\' I IRR to cs urnatc monthly rainfall. and 2 ) n ( ,O IS f'reclpil;llinll Inde x (( i l' l) bused on an an
Ac tive and Passive Mic rowave Techniques
A major milestone in satellite p recipitation -rar e estimatio n wa s the <.1<.'\ efop mc nt o f mic rowave remot e se nsi ng ins trumc ms that respo nd in a more physically dil¥cr way 10 the presence o f prccipuarion-size wat er and'or icc panicles
430
ell
Tropk...1 Rain fall
" l e;lsun'III ~'nl
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12
IlII a:': l'r~
Remote Sensing of Water
tin "larch 9.1998
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Fig ure 12-16 ( )rhll'II .l a[,H;('lk~li"n Ctl\<:TOI!'C Il~ Ihe r [<'pl,il l Ram!,,11 ~ lc:\Sll[Cl1h:llt \ llssi "n l 'l R \1\\) M,,:ro W3\ C Imager ('I Mljon ~1Jld 'I. 1' 1'J ~ . :-Jll! icc lhal Ihe 35 0 Ilililk " f inc! in.u jon obtaius L,; '" " I ,'llIW :'gC "I' til", tropical and subtropical po nj " ns of lh ~ Eartl ..\ 11 intense frolltat sy stem is uvcr southern Hundn. A b o pl.:aw refer hI Color Pial," I ~-ha (WlIl tcS) ]\ASA
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r,
s
c .... ithin the clouds. althoug h rema ining inscnsi ti\c III 1101!" precipitating clouds. Th e first Special Sensor \f icnlW3\ <: Irnagcr( SS ~1. 1 1 \\11'0 launc hed in IlJx7 and included a highIrcq uency channel at l:'5.5 GI ll. Basil-a ll) . prccipnauon-sizc ice partic k " and 1.:lrge ra mdrops ~ig:nific;lnlly red uce the t"nlls~i\ ily ofthe cloud and thus depress it~ t-righlnl'l'lO remperat ure H~ below a no minal background Ic:\ ct. This allows a rainfa ll es timate III he co mputed. T his se nso r could d isnngursh ra infall over land w ith reaso nable co n", i",ICrll') at 15 x 15 kill spatial resolution (A ll a~ c t al.. 20051. T he SS \l!1 has provided wo rldwide prccipit.uion estimates since Il)X7, ~ illt!1c
mos t important ev ent in rainfall es timation (cspcfor tropical and subtropical reg ions 1 was the launch of the Tro pic al Rainf all Mca -unn g "lis~ i,," (T R\ I""l 0 11 Novembe r ~7. 199 7, h) ~AS :\ and the National Space Developmen t Agency (1\AS D:\l of Japa n tTR M\1 , 2IM "'I, I bc satellue is in a ';50 kr n orbu ar an mchn.uion o f 35 ' . T R\ l.\ ! carries five instrumen ts onboard: till" Precipitation Rada r (I'Rt, the TR \ I~ 1 :\lic rowave Imager (T\l II, Visih le Infrared Scanner ( \ ' IRS), Light ning Imag ing Sensor ( LISt and the Clouds and Earth's Radia nt Energy System Th e
cia t l~
{<.'FRES I.
The T R M\1 Mi.;rowu \e Imager lT~II ) is ,I passive rni..:mwnw ~c n snT dc signl'd to r rnvid c 'lu ant ita live rai ntitli inliJr· Illat io n nn th". illle gratl'd c" llIl11 n p r".~' ipi til ti l111 e\l nt ~ l1ll1\' CT a
4~7
mi ll' (il\O knu swath, 11 is re~t suited for rainfall estimates over oc eans wh..,n.' data are needed most for clirw model verification. It lIlCasUR"S the inh: nsi ty ofraJiatiOl li\ ..- frequencies: 10 ,7 t '; 5 km spatial rcso hnion I, 19.-', ~t.3 37, and x:".:" <1Hz I; km -paual resolurionj. II has dual pcUiza tion at fou r of the frell \l~ ne ies , The 10,7 G il l fn."t:!lJCl);\' pro \ ides a mo re linear response for high rain fall rates ca. mon III tropic al r'lInl;111. .-\ composite tmage Ill' alllh: TI{ "' I ~f .\ l ieruwa \c lrnagcr orh ua l pa ths on Murch 9, 1m, arc presented in Figure 12-16 and Cotor Pknc 12-6<1, \ ett the intens e Iinc oftlumderstorrns nH'T southern Florida, The TI~I\IM Prccipitmion Rada r II' R), the 1i""1 in space. 111.." l'li re" the thrcc-duncre.iona l ra infall distribution o'er l\t'lh laml and oceans. It de fi nes tilt' layer dept h o f the precipuauon and provide s informat ion about the rain fall actual~
reaehmg the surface. .... hich i ~ used 10 dcrcrrn me the 121Clll heat o f the atmosphe re IT R \. I ~ 1. 20061. Passiv e microwee scusors ha l c diftku h) mea-c uring ra in ever land areas ldilcussed rn Lhaprer 'l }, .... berea- the scann ing radar npefal~ at I r.s Gl lll l l ll l provides accu rate prccipitanon data 01'0' land at a spatia l reso lution of 4.3 km at nadi r and a S\l
1
•
43 1
JemSOIS a nd C lo ud s
lJa et al. (2005) found tha t the T R ~ I M Prec ipitatio n r estimates we re good agree me nt with g round-based preci pitation meas urements , Alias er al. (2(05 ) found precipitation esti mates from T R \I ~ 1 Preci pitat ion Radar the Special Sensor M icro w ave Imager (SS \1 ' I) proexcellent rai nfa ll tn forrna non for use in hurricane ysis and forec asting. TR\t\1 Visi ble Infrared Scanner (VI I{S) pro v ides high tion in forma tion o n cloud cove rage. type. and cl oudtemperatures. It is a five cha nnel cross-track scanning mercr opcra ung at O.f•.\ , Lb. 3.75. lO.lUl. and 12 u rn. It ins ~. I km da ta at nadi r .... ith a s w ath wi dth of approxiy 720 km . II: TRM~1
Lightning. Ima gin g Sensor f l iS) inventories the incidence ofl ig htning using an optical remote sensi ng em opt"rating at 0 .777 um uh a spa lial resofu uon 01'5 x lm at nadir and a 590 km s at h \\ id rh. The Clouds and h's Rad ia nt Energy System (CE RES) is a visihlc a nd se nsor designed especially III measu re emiucd a nd lectcd rad iative energy fro m the sur face of th c Ea rth. a nd the atm osphere and its consutucms te.g.• clouds. aero$1. It is a hroadhand sca nning radiomete r w ith a total cl spec tral ra nge of 0 .3 50 m m. ~I M 's
uni que combmauon of senso r wa velength.... coverand resole ing capab ilit ies wuh its lo w-altitude. non-sync hronous orbi t provide mont hly precip itation urns to a 50U x 500 kill grid (T R/l. I\ 1. 2(l()6). Unfon uely. a, can be se en in Figure 12- 16 . si nce the T R!\I/l.1 mis was mea nt to co ver tro pical latitudes. its 35 degree tude lim it e m braces lill ie Il f Europe a nd nume ro us othe r !I1POrtalll land areas in the Ncrthc m 1Icnusphcrc (Ga bcllu ct .20(5).
an advanced , large apertu re. multic hanne l passi ve mi cro wave ra in radio meter referred as the GP\ 1 .\1 icrowave Im ager 'G :\II). This e tfort is prim ar ily a tuncuon of the Earth Observat ion Summit (EO S, held in July . 2t1( U . in Washin gto n . ur .. whe re more than thirty na tions mer to addr ess glo ba l cnviron mc ntal ami economic challenges. As a rc.... uh o ft he EOS Summit. an ad hoc Group on Earth O h......rvanons .... as established to prepare a tell-year im plemen tation p lan for a coord inated, sustained Earth O bser vation System . The G lobal Prcc ipita ncn ~ lca~u rellle ni m i~si()n .... ill hopefull y he launched in 2009 20 W . Tbc G M !"s sp atial rcsc !unon .... ill exc ec-d thai of lln~' current or p lanned micro ave radi ometer, incl udi ng the nc.... Conica l-sca nning Mi cro ave Imager-Sound er \C ,\ li S , radiometer being developed for the :-.10.......... Pilla r Orbiter En \ u omn enta l Satellite S~slem (:,\POESS) (Smith et al, 200l).
Aerosol s and Clouds
:-JASA Ea rth Science Enterprise scientists state that more info rmat ion is needed on the fo llow ing variables if we are to be able 10 model ami u nde rstan d the force, modifyi ng the Earth ' s global climate S~'st L'l11 ( Ka hn, 199Q): the amount and ty pe o f atmospheric partieiL's (llerosols). incl ud ing those fo rmed by 1I011ure OI11d by huma n ac tiviti cs: the amount. type. and height (.r elo lnk a nd the distribution of lun d-s urfuc c co ve r. including ve geta tio n cano py structure.
hrem utlonn l (;l uhall'n' l'iIJil ut illn M cnsurcmcnr ((;1'1\1 ) Pm ~ r~ 1l1
lin d
Aero sols
!' Ii ~~ i ll n
lm rovcd microwuvc-d crived rainfall datu will likel y ecomc availa ble in thc fu ture. In particu lar, the proposed ~matiUl1
' 3
L
pr..'Cipitat illn
radar
A eroso l part icles may be soli d or liqu id and rang e in size fro m 0.0 I u r n to ... cv crel tens o f micrometers. Cigarette sm oke particle s a rc in the mi dd le of this size range; typical clo ud d rops are 10 or more mic rometers in diam eter. Aerosols lend tl) coni the surface bel l)w tho: rn ht:eau se most ;Ief()sols rellect Sunlight b;lCl lo spac t: reduc ing th... am uu nt o f solar rad iatIOn that ca n hi.: :th...orhcd by th.... surl:1Ce be low I Ka hn. IIN\) I. The lll11gnitude o f th is ... rreel depe nds o n the size and cornpositi
432
10 inc reasc-, in the amoun t of atlTK.hph<:ric ca rbon dioxide. Perha ps more smog is good! Others d isa gree . A ltho ugh rem ote sensing aerosol ret rieval science has bee n taking p lace for mor e than t.... cn ty years. um il recently I h l'1"C was no method of obtaining inform ation on ncrosol amount and d istri bution (called optica l dept h ) and pan icle propertie s (Bojinski l ' t al.. 200~ ) . Th e EOS Terra Mu lti-angle Ima ging Spcctr o k adio mcrcr ( ~ lIS R\ col lects such information using four spectral hands (blue. gree n. red. and near-infrare d ) and nine." look angles (refer to C ha pter 7 for a J<:IJ,i k J dcs criptio n]. Fo ur o f the linea r-array sensors look forwar d at an ob lique angle (~ f, .I <>. 45./, ". I'll". and 70.5 ". respec tively). one loo ks directly do.... n (nadir). and four look aft at the same oblique angles. This provides multiple looks 3t exactly thc same pan of the atmosphere [and the surface o f the Ea rth I. allowing quantitative m formarion 10 be derived abou t aerosol location an d content ( Dine r ct al.. :m O; ). Aerosol characterisncs o fthe enure Earth may he ob tained eve ry nine days Tang ct al. (:!OO5 ) reponed on the ex traction oi'ecrosol m for marion using Terra a nd Aqlla r<.t OD IS data. Boji ns ki et al. j2 004 l provides II history Ill' aerosol map pm g and a ne w aerosol retrie va l algorithm using hypcrspcc tra l dau.
Clouds
Ctouds playa major ro le in cont rolling the Eanh's climate. xtorc than any oth er component of the climate syst em, douds affect the Ilow of energy within the Earth's atmosphere. A cloud may warm or coo l the Earth . depending upon its thickn ess an d height above the surface. Lllw. thick clouds retlccr incom ing solar rad iat io n hack In space. which ea uSl"S c\Mlli ng. High clouds lra p omg,)ing infm red radiation and prod uce grecnho\lsl' ' Hu m ing. Oeo.: ause c1(' ud lype. hei ghl, moislu re CO!ll.:'nl. and locat ion nrc s(\ var iahle . Ihl' ir I:l1"ect o n glo ha l c1iIllallJ is \ cry dini cult Wllh:lISlln:. So me bdieve that Ihl.' lal'gl.'sl ullccrt ainty in climatc prcd icl io n mod el s is how 10 chnrac l~'ri;{e and par amelc rin ' the radi at ive and physical propert i e~ of cluuds.
The lin-I metel-'rological satelliles (lnly measured \-isibk cnergy n:fketcd from clouds (0.-1 - O.7IJm) CiOES ....nSOf<; provide data in hn lh the visihle and lhl.TITlal infrared po rtion of lhe spl."Ctrum. as summarized in Ch apler 7. In Ihe da)-li!;hl hou rs, visi ble imagcry prov ides detailed vicws oflh~' c1nud patterns Ihat clo~c1y mall'h our visual senses. i,e.. d ouds usu:llly appear brigh l \\ hite l:tnd a nd wa leI' appear darker on Ik illlnge,. C o nsi d~'r lypica l v isihlc imago:s of h('lh tIll' \n ' slI:rrl and eaSlern Un iled Slill...s o bta ined hy (iOES-l-:ast and
C11W1TR
12
Remot e Sen s ing 01Water
liOl~-Wesllln
Apr il 17. 1'1"~ (Figure 12-1 7a.b).I\<* large low -pressure frontal system upproachmg Wash _ slate from the Bny o fAl:hka . T here is also a significanr pressure system located along the Eastern Seahoanllllll throughout the southeast. GOES was first laun ched (11\ Oc» ber Ih, 1'-175. Since that rime many new GO ES salelhlll have been par ked (I I 35,790 kill in go.:ust;lli(.rhlry orbit~ obnnn visible and infrurcd imagery. They nrc used 10 mM· lor fronta l systems. inte nse thunde rstorm activity a~so.:isce with tornadoes. a nd hurrica nes. FUWpl' has a system similar 10 GO I-'S. called METEOi~ \ lET I.OS:\T 4 is a geostationary me teoro logical sal located 31 O' of latitude and long itude. It contin ob<.('f\cS the vv hole I'arth disk. The images gathered to. IE1TOS AT in three channcls-c-visiblc to.4 1.14 thermal in fra red ( 105 1:!5 IJ.m)and w mer vapor(5.1 - umj-c-nrc transmuted .:\ery )0 min . T ho: METF.os,\T irnagcs avai lable in hig h resolu tion mode have 5000)(500' pixels lo r the visible channel and 2500 X 251)() pads fOlmt infrared anti water vapor cha nnels rAmeur cl al., 2tlO4l. "'l ost remote sc nsi11g systems ,1pCral ing in Ihe visible [l(1niali of the spectrum can only collect data d uring the da}time. How ever. a lig hH .ens it ivc instrument onboard the DefelL'l: Mcl l'tlwlog ical Satellite Program (D MS P) ca n obtain visible imaj!l's
Im a ~ ('ry
The nlllsi l.'OmlnUIl lhernlal infrnn.-d band used in mcleorolugkal investigations is 10 - 12.5 jJm. The atmo~pht-re1S rd,lt i,cl) lran,:.pa renl III thiS .... avC' k ngl h <.'Tlergy UP\\tIlill! fwrn lhe Earth's su rfao.:c and dOI.lJs. ,\IS Il. thennal iofnrd imag"s o.:an be oht:Jined al n ighl. so we can have a conunuOl!S 24-h r n:c l,rd nf c loud Pilltcill s Ihat incl ud<.'s importa nt lllt'k(lrolngio.: a l c,enls lakin!! plao.:c al nigh l.
,
Aero !
sols and Clouds
•"
433
GOES-Wes t and
CO ES-Ea~t
Images
d
Figure 12 ·1 7
a. GO ES-West visible.
b. GOES-East visible .
e. GOE S- West thermal infrared.
d. GO ES·Ea~t thermal infrared.
c. GO ES-West wate r vapor.
f. GOES· East water vapor.
E".Hll P Ic~ IIf GOlS-L!"t and
GO[S- Wesl irnal,:cs o f'thc Unncd States and p ortions of' Ccmra t America ootam c..1on Ap ril 17.
I Ql/N ( L·.ltlr1 ~y ..... OAA)
,
( ' H A P n :1{
434
Col d
t
.::.)nh-..:tiV':'~'~':O:"d:':,,:~~;::) m iddle -lev el clouds or m idd le-leve l conv ectivc clouds
10\\ cumuli form clouds
land
Warm
.
.....- - -- - - - -Bri~gh t
Om
Vh ibk
Rem o te Sensing of Wa ter
red ba nds.joc atcs it in the diagra m. and idcmiflcs thcnabtt: o f the clou d under investigation.
lOps of la rge
semi-transparent high ck.uu!>
12
Figu re 12· 18 II is po~sillie 10 determ ine cloud type based on multispectral measurements in the visj blc and thermal infrared portion o f the electromagnet ic spectrum (a ficrOo:sboisctal..1911 2).
In satell ite meteorology. infrared images arc normally inverted. i.c. tl lC gtcarc r the radiance of a pixel, the darke r the pi xel. Th is way. clo uds. whic h are usually co lder tha n th e surface o r the Earth. appe ar while . an d the wann er grou nd or ocean surfaces appear darker than cloud s, as in visible image s. T hermal infrared GOES-west an d loD ES-east images o f tile Uni ted Stales ,HI: show n in Figure 12· 17c.d. II is easier 10 ilklltify the edge of frontal systems us ing the therm al in frared imag ery. Also , the [and-w ater boundaries arc more distin ct . It has been known for so me t ime that it is possible to extract information on the type of clouds and thei r he ight using multispcctra l re mote sens ing. One ofthe earliest relation ship s is demo nstrated in Fig ure 12- I K where visible and infrared data can be used to differentiate be twe en the sea. land, cumulifcrm clo uds. se mitransparent h igh clouds. and co nvec tive clouds ( like th understorrns t. Tall co nvec tive cu mulo nimbus clou ds arc co ld und bright. The sea and lan d surface are warm an d dark ( Dcsbois cr al.. 19lC). Th e analyst extrac ts the pixel value in the v isib le and therm al infra -
N umerous scientists have aucmptcd h) detect the presence cloud s usi ng a the rmal infra red clou d tem perature thresMl value. The goal is to identify low-temperature pixels till co rrespo nd to medium- or high-alt itude clo uds. The Il\3!I prohlem is usua lly the s~'Citkation o f the exact lernpeTlllr. thr esho ld v alue. For e xam ple, Franca and C racknell (1995 deve loped the different cloud-detection algori thms btiej o n visible and infra red spectra l in form ation us ing \OU A\' ~IRR daytime data for tropical areas. Fcidas ct al. (2 developed a clou d classificati on scheme .... here thick op3lpiiI convecti ve douds correspond III classes .... ith the kMtf brig.htne~~ temperatures (Th) in both the thermal infurel [below 223 K) and water vapor band ( bel ow 223 K). Frida and Carralis (20115) buill upon thic wo rk and devetoped a au tomatic a lgorith m for uackin g convecnv c cloud cells.Te Sur",alb-" Diff':,.,:ncl' Snow tndex (NDSI) d iscu ssed in tit: Snow section of Ihis chapter can also he used to identIi\ clo uds U~ illg se nsors thai con ta in a \ isible and mid-infrared ba nd Ic.g .. Land sat TM ba nds 2 and 5) ( Hall ct al.. 1995 Choi and Bmdschadler, 20(1·11. Cl oud- height informat ion ext racted from the rma l infmtd data ca n be use d to gene rate pse udo ihree-dirnenscrsl ob lique images o f major storm events. For example. tile :\VII RR visible and in frared images in Fig ure 12· 1cab capture Hu rricane Andre w moving toward Louisiana in 1'»2.1n these cxurnplcs. the v isib le (band I; 0.58 - 0.68 ~ m ) aM ncar- infra red images (hand 2; 0.725 - I. 10 Ilm) arc draped ov er the cloud -he ight information de rived from themW infrared data (band 5; 11.5 - 12.5 1l 111)_ The TRM1\1 Visible Infra red Scann er ( VIRS) launched in [997 provi des infur murion o n c loud ty pe and cloud -top tl'1ll' pcraturcs using a five channe l cros s-track sc anning radiometer. The terra 1\1 IS H. se nso r co llects Infor mation in only the vis ible an d ncur-ln frarcd portions u f the spcc uum. while the Terra Clou ds and Eart h's Radi an t Ene rgy Sys tem (CER ES) sensor co llects data from Just one look angle. hut across !he entire sola r spec trum. C ER ES meas ures both sola r-reflected and gart h-em itted radi ation from the top of the ntmosphere to the surface. It a lso dcremunes cloud properties i ndudlll~ amount. heig ht. thick ness. an d particle size. Thus , the \'IRS. MISR , and CE RES instn nncnts co mplement o ne anotherin the collection o f clou d info rmation. MO DIS obta ins cloudtop info rmatio n frum bauds 33 - 36 in the thermal infrared regi on from 13.1 loiS - 14 .3K5 urn .
,
w.
~ate r
435
Vapor
AV IIRR I mager)' ur Hu r ri cane A ndrew un A ugust 25. 1992
,.
a , Visihle band 1 (O.5R - O.6R j.1ml.
b. Ncar- infrared hand 2 (o.ns . I. III um).
Fgure 12· 19 :11A\ 'HRR " lsi!'> le band I (0-:")0( - O.b!!J.1m ) IlTI3gCf)' oll-lurricant' Andrew bearing do.. n on I .("'ll ~iana obtained on A U~'11st ~ 5. 1'I"I:!. Oil ~n: 2 0 UT. I hl.. epparcr u height of the pcl'l;fll.."'I:li\'c r"'rnk rllljo: is il1\cr.ocly f'TupUrtl\,n,,1II' 1m: cloud te mperatures obsesv cd in baud 5 ( 115 1:!.5 j.lm). OI I\\"HRR band:! 10. T!5 - I. III j.1 m ) ncar-mfrarcd data (courtesy ofF lIa'-lcr. K Palaniappan. M . MiUl~'ln and II. I'lcr.:.:. :'>I..\ SA (j"ddard Space ~ li ~h l Cemcrr
Water Vap or
\\aler vapor is esse nnalfo r precipn auon. 1\'ut on ly i ~ wa te r vapor the most important gre enhouse gas in the at mosphere (Chylek er al.. ::!O(J()4 1. but thi s varia ble also plays a key role ft1l' the undcrste nd mg and predic tion o f mo~t important weather pro eess c,s Imm convection. to the fo rrnauon of cloud. and precipitation . 10 the formation of severe storms IWul fmey\.'r ct al., 2()()5). 11 is possible 10 map wa ter vapo r b}' sens ing in water-vapor ubsorpuon han ds. Several wavelengths can he used. hUI on e o fthe most common is centered around 6 .7 u rn . I\ILTEOSr\T I , launched in I ll7!'i by the Eu ropean Sp ace Agency, was the first gcostutiormry satellite to obtai n images of mid - III upp er-troposphere w ate r vapor in the 6.7 J.1m regi on in ukluicuto visible a nd 10 - 12 Jim infrared images. ~ IET EOSAT 4 collects wutcr vapor information inthe spectra l region fro m 5.1 - 7. 1 um (Amour et al.. 2iIl 14).
GOES sensors routine ly provide w.ucr-vapor images obtained in the 1:>.71J11\ region . A t this wavelength. most o f the- radiation sensed by the surcltitc comes from the atmospheric laye r betwee n 300 and (,I)(} kill. i.c .• from the m iddle layers 0 1" th e tro pos phere. h gures 12-1 7e .f de pict watervapor images of the western ami eastern Uni ted States. Note the tremendous amoun t (If water vapor in th.., a pproa ch ing storm in the western Un ited Sla tes and the departing storm in the eas tern U ni ted Stares. A bo note the lad: of ...aicr vapor on this particular date around Hawaii a nd in the lower pur-
t io n or the (iulf {If \1.:\;co ncar Coz umc l, vtcxfco . The wea ther was very co mfortable on th is dayin these area s. Th e rela tive humidity is likely to he higher in brightareas than in dar k areas on a water-vapor image . Bright and d ark areas may also indicatc rising an d sink ing motions. respectively.
It is ab o possible to e.\lm.:l water \upo r information in the ncar-infrared portion of tile spectrum whic h has seve ral fenrurcs that ma ke It anmctive for remote water \'aror retr ieva l. It I;. a reg io n where the so lar rad iation is still q uite strong: and the re nrc spectral bands wit hin the nca r-infrared whe re int er fer ence from other armnsnhcric gases is we ak. wuhin the wav elength spau from ,lbol1t X9(J to (NO 11111 the re arc th ree maj or wurcr vap or uhsorptiun hand s: a strong absorption han d centered ncar l)42 nm a nd wea ker absorption hand, centered around l)(jll and ')77 um IChyle k ct a I.. ::!OO-t). \-IODI S has several bands that arc sensitive to atmospher ic water \'apn r in these rl'gin ns, includ ing hand 17 (890 - 920 nm j, I ~ (9.'1 - 94 1 unu. and 19 \ 9 15 965 nmj. In the future . the European Span' Agency ll1i.1) launch the Water Vapo ur l. idar Ex pcnmcm in Span' ( WA I. ES I using a di ffere miul abs orption Lida r twulfmc ycr ct
Snow
Snow runo ff can be both beneficial an d d isastrous. Spring: runoff is the lili..blood tor most ag ricu ltura l activ ities in
,
12
( 'H M ' n :N.
436
semiarid cl imate s and pro... ides muc h of the po table drinking wa ter (in ad d ition In gro undwa ter ]. Unfortunately, a rremendous bu ildup n f snl'.... or an unt imely thaw can cause sev ere flooding and c on ~c4UCn l l ) II.I~s of life and prope rty Therefore. mc rcorologisrs. hydrologists. an d g lac iologists \\ork to identi fy l ] the geographic extent of the snowpack O il a "1:.1son al basis. and ~ l il!> water equivalent.
Rem ote Se ns ing of Water
ThO" retries
Rt,nt'chl lin ' Ill' e lllud .. anti Snu" SIl
Water
_._.,._-......
Deper
snow .... ater transl mapp
\'.'
regio
2005 \SA 1 discr and ,
Snow in the Visible Spectrum
When clo uds arc no t prese nt in a , i" lble and/or near-infrared image. il is a relati vel y st raightforw ard tas k to identify the: spatial dismbunon of snow becausc' it is generally much brig hte r than the \ egetauon....)il, or water nearby that is not cov ered wi th snow. A ls-o. one of the major diagnost ic clu es that can he used 10 d istingu ish het" cell c louds and sno ....' is 10 obt ain numemuv unages of the terrain in a relali\ d y short time period using AVIIRR or GOES data. Clouds mov e snow does not .
Snow
1
men
•
~ "a
°1J.!'"'r°-i";-, r r nn, -T, r r r;rl'-rT-l"1 U.4
U,7
I II
15
2_0
15
Wave length, lIm
or
Figure 12-20 R...Ilectance o:I"lJd~ and ~n,," In the ...aH~I. internl 0.4 1<1 :!.5 11m (alicr AvC1)' and Bmia.
'"' extr. gen.
exre p4 n
m'l
Snow in fhe Middle-Infrared and M icrowave Regions
Hc wcvcr. if one can only' obt ain a si ngle image of the terrain and it contains both clouds and snow, the n it is possible 10 utilize the middle-infrared portion of the spec trum to d iffer en tiate oct .... een snow and clo ud cover. Th e reaso n is made dea r in Figu re 12-2 0. Th roughout the visible a nd ncar -in frared portions of the spe ctrum. d o uds and sn ow reflect appro ximately equa l amounts of radiant l1u.'< .ln the middleinfra red po rtio n (If the spect rum tcspcc ially 1.5 - 2.5 pm) clouds continue 10 reflect It subslanlial a mo unt o f en ergy, whi le sno w rc tl ccurucc d rop s 10 near J:eruil lal1 ct al., J()95; Choi and Hindschndlc r. 20( 4 ). T his relationship was first documented by Sky lab sensors operat ing in the region 1,55 - 1,75 um. In this ba nd, clo uds ha ve a ver y high reflectance and appear w hile in the imagery. whi le the sno.... has a very low re flect ance lind appear s black . Th us, the Land sat T hema tic Mapper hand 5 ( 1.55 1.75 Illll) and the SPO T 4 senso r with its middle-infrared band ca n be used to discrirninn re be twee n clou ds and snml co ver, T he de crease in re fl ectance of snow from SO - 90 percent at wuvclc ngths < 1 u rn to < 10 perce nt at approximately um i ~ ex traordinary when compared with the re flec tance cha racte ristics of other Earth su rfac e mater ia ls. Based on these relatio nships. lIa ll et ;)1. ( IQ(5) de veloped the /' /11/(1,(1/ Tvt Normafi:etl f)/j!<'n.'nce SI/OM I", I/lx ( t\ DS I, h.IWll n n ba nd 2 and band 5 dala:
t.s
Land sat H I :-a>SI
( [.\12
T~ t5)
( H f ~ ' T M5)
(1 2-7)
A thn:s ho ld appli ed 10 the NIlSI image is used to separ.ll~ cloud pixels from non-cloud {snow 1 pi_\c1!>. The automate cloud cover assess ment a lgo rithm (ACTA ) developed ~ Irish ( .:!:II/10 ) used 0 .7 as the th re..hold value (C hoi and Bindschadler. .20041. However, the optimu m threshold can val) from one 1'\ DSI-derin'tl image 10 anot her,
MO lllS data na ve been used 10 prod uce global MtO.... -c OI I:f map prod ucts s ince Septe mber 13, 2000 at 500 x 500 m resohnron (Dozier and Painter, .2fMI4 ). The automated MODIS sno w-map ping algorithm uses at- satell ite rcflectances in MODI S band s 4 (0.545 0.565 p m ) and (, ( 1.62S - 1.1>52 u rn} I II calc ula te the l/o n lS Norlll l/ {i:t'd IJ(lkl't'l1ce Sm)), Index ( i la ll 1.'1 ul., .2002 : Saknuonson and A ppel. 2( 04):
Su SO l
tiv 10< do
p<
10
til
d. I,
re c:
o r-. fODI S NDSI • ( r-.10 lJ IS 4 - "-10D IS 6 ) . ( "-10 n lS ~ + \ lO[)JS 6)
(12.8\
II
"c A pixel in a non -dense ly forested reg ion w ill be mapped as snow ifl ho.: \-IOmS N I)S I ' s e 0.4 and re flectance in "-IDOlS han d 1 is ::: l l~ ·; " How eve r, if thc MOD IS band 4 refl ectance is < 10° .., then the pixel will nor be mapped as sno w 1.'\1.'0 if the lither criteria ar e met [ Hal l ct ul., 20(2 ), This prevents pixels co nta ining very dark targets such as black spruce forests fro m bein g map ped as snow. Sa l(lm
Qua lity Modeling
aicrowave region of the spectrum offer, promise for 'ing importaru 500.... information (Foster et .11.. 2(MI5). ding upo n the .... avele ngth, estimates of the depth, .... atcr equivalent. and the amoum/prescnce of liqu id in the snow pack arc possible. In addition, clou ds are sparent to ma ny of the mic rowave frequencie s so tha t ing of the snow are a and pro perties is possible even in re s " here clouds arc co mmo n and at nigh t (Foste r et al.. 5). AircrllH and SP;lCCShun lc Synthetic Aperture Radur RI measure ments hav e show" that SA R can he used to minatc betwe en snow :111d glaciers and between WL' I dr) xnu.... (Shi et al.. 1'N..f). Derk sen cl at. (20U5) docuhow data from the passive microwave Special Senuicro....ave-Imager (55 \ 1/1) .... ...ore use d 10 successfully snow .... ater equivalent unormauon over Canada, In I. optical remote sensing used 10 map snow areal (S:\E) has milch higher spatial resolut ion when com.... ith micro.... ave remote M'nsing w hich ca n be used to sno w water eq uivalent (SWEl [Zhou et .11.. ::!OO5). Water Quality Modeling
and county agenci es arc req uired to red uce point e discharges to sur face wa ters. Po int sources arc rela ~ ea~y 10 control and regulate because of their kno.... n n. A phenomenon more common and mon.. difficult to is 1/''''poIIII source pol/llti"" I ~PS). t<\ ps is defined as ion originaling fro m urban runoff. construction, hydromodificauon. sil viculturc, mining. agncuhurc. urigareturn 110 w s. solid-waste disposal. atmospheric snion. stream ban k erosion. a nd sewage disposal. ·Is o f " PS include dccr":'lscd recreatio na l wate r usc; ..nion of wa ter sto rage capacity in st rea ms. lakes and uaries: clogging of drainage ditches and irrigation ca na ls; rcssivc en richment and scdhn cnt auon of surface \\.-atL'rs ,on trihutl' tn Ihe loss o f fis h. shcllthh and w ild life hahand a reduct ion in the aest hct ic qua litics o f thc ;u..j u:tti\· ironment (C(,rbill. 1990). itiollill i/l sim me asurt'mt'nl tech niquL"S ha l e had a limdTn't on identifying and mt1dcling no npui nl '>C.'uree po lScic11li~t... !la\ e found tha t an Illt...g . ratlon of ill Jim an d e "<:nsing data eolk-ction .... ith GIS modding t<.'Chcan provide some \ef) u!i.cful .... ate r-ljua lily infonnaIn fact. remote ~nsing dal a col h:ction comhmed wilh - mudding (,ITen; 3 mea ns of ide11lifying and ranking Ws pOlcnt ial in su rl"a":L' wat ers with o utput that is relat ively ) for the general pu hlic to understa nd. Se hu hl ( I'IXXI vidcs e >.ample s nflw w ren wtc! y sc ns.;d biophysic al \ari-
43 7
ables such as slope. S<.lils and land-cover cbaractcrisucs can be used as il1pul to hydrolog ica l models.
An Integrated Remote Sensing and GIS Water·Ouality Model
T his brief ca se stud y evaluates water-qua lity deg rad ation and iurpucts from urba n runoff with in the Withers Swash water shed in Myrt le Beach . Sc. Wither s Swash is an urha nized wate rshed (.~ ..f% impervious ) that coven; app m xi mntely -i.2 mi ~ and includes ind ustria l. resident ia l. commercial, ugricukural, recreational. and undevel oped land uses. Th e .... atersbed i ~ d ivided into IWO ""uhbasins (Figure 12·2Ial. \\ hich drain into a tidal pool designed to capt ure sediment before emptying imo the Arlnntic Ocean. A study was conducted using remotely' ..enced data 10 deriv e land -cov er information which was then integrated .... uh other spatial information such as hyd roll' gy. topography, and soil da ta , into a (i IS database. The data .... ere then analyzed using the A:~rh'/I!t/lr"II\'oIlPoiIlJ Source (t\ GN I'S I pollution mud d to g ...ncr.nc wate r-quality predic tinns ( USDA . I99X; Sc hill and Jen sen . 1'1'11'), The ,.\(j ~ I' S wa ter-qu ality mode l USL'S e ight d irecnonaltlow attributes determined hy tlllltigra phy and channel charac te risti.:!> to route storm .... arcr th roughou t the wa tershe d to a si ngle outlet cell i Cronshcy and Theurer, 199 8 ). A pp roximate ly one third of the mod el input parameters are derived from tupugraphy (figure L!-l l b ). These parameters include tcrra in sl"pe. the Universal Soil Loss Equation (liSLE) slope leng lh. and ~ Inpe shape . Soil annbute, incl ud ing erod ability (US U : K I;v.: tor) and te xture. were ver ified through field sa mpling and sicvc t csts ( Figure 12-2 1c). Lan d-co ver informar ion .... :IS deri ved fro m 1:11l,(ltll)-sca k ector-infrared aerial ph\llogm phy anti from r\ AS A' s Air borne Terrestrial Appli \·atiolls Sl'I1S0r (l\T t./vS ) J )( 3 m multispectral data (Figure 12-2 Id j. From lht'se land -co \'er alt nhuh:s. the SCS curve num ber (ass igncd by sui l hy dru l\,gic g.rtIU p) . Mann ing rou ghness coeflicient. US LE C (croppi ng ) and !' (pract ice) fal' tnrs. so il L-(llldition nlllstant. a nJ ch<.'m ieal \l.\ygen dema nd ICOD I .... <.'r<.' de rived based on loo kup tabk s in Young ct a i, (l9tI-t). Belo re e\L'\:ulin g Ihe mOOcl. all sPJ.lial dala wcre ass ignt.-d 10 a 30 )( 30 m cell (0.2 )( 0.2 ac re) lo r eac h o f the: 1....0 subb;lsins. A single stoml e\ ent ....as si mulal t'd us ing Ihe tiJl lu.... ing paral11<:lers; stonn enef!:)' inlens ily (r ractor ) o f 1)5.39. sturm du ral ion of2..f hours. tllt;ll slOn n ra infa ll eq ual to 2 .t1 R in.. am i ra inta lt nitrogen COlll'cntnl tillns of O. Sll pp m. An l'x a111pk u l" two lIlodd output pur3mL·ters incluJ.: COl1eel1tratl' d Pl':lk !low in nJ p<.'r -,;c\·.,nd (cfs) (Fi gure 12-2 1c) und
438
C H.. \ "T ~:H
12
Remote Sens ing 01 Water
Rete
tct a' resu
Xon pclnt So urce Pollu tion Mo tlcl in:,::
usc,
, nd ua r h'" oth ~p
L' RJ
c Pea k now (chI
o • •
o o. o n ~ o u ~ .n l ~ () 1 ~ -02~
\U5 -o :\(1
r ('e ll emSIon I (U II>
per ""'1'1: )
d. Land cover den,ell fronl remcic SC I1,'<,(lr 0:111;1
Fig u re 12 -21 :"ollpoilll source pull uliull mod eling using Illc Agri cu ltural ~"nPtli ll! Sou rce (AGNPS l pclluuon water-q uality nlOl.kl :tpplifl! In two ~lI h.lla~i ns. at H)d rolog) ot'the Withl."l1' Sw ash waters h..-d in M) n le Beach. SC \1 oo t'ling was OOSl"d on 30 >< ., 0 mctUI and a !.IlX in. ra il' ill 1 -4 huurs. bl Topography was Jcri n~J photogra mmctrjcully and U5'"U 10 cvrrac t slope inform ation. cjSoil d.na " con: ,;.;,mrletl in the field. dl Land cover charack"Oslicl> were derived from I O
A
439
Ilferenc es
111 cell erosion in tons per ac re IFigu re 12-2 10. Mod el
::lulls have been compared with ill J im measurements and
ltd 10 locat e areas of increased sediment and nutr ient loss ill to ind icate the spatial extent o f nutrie nt and sediment
Choi, II . a nd R. Hindschadlcr, 20U4, "Cloud Detec tion in La nd sal Imag ery of le e Sheers usi ng Shad"" Millc hingl cchniq uc and A utomatic No rmalized Diffe renc e Sno w Inde x Thre shold Value," R<'nw l<" S..".i"K o/f."m'''''mm",,', ~ I :237 ~2"2
espon. depo sit ion and accumulat ion. Th is in fo rmat ion been used 10 spa tially alloca te vegetated bu ffer stri ~ and ~I manag ement pra ctices (ll\1Ps). Kin g ct al (200 5) eon on the use o f re mo te sens mg land -usc input s from ..dsar T i\! data a nd surface ro ughness inp uts from !ADARSAT 10 the ST REA M run off and erosion model.
ter
Dar ec ki, M. and u. Strams ki. 20ll4, " An Eva luation o f MOD IS an d Sea WirS Bi, '-u plica l Algorithms in lhe Balli c Sea: ' R<,·
Refere nces
"''''f' S"mi,,); ofEnvironmem. 11'1:326
l.. Amcur, S .. Ad anc. A., Sau\ ageot. II . and K. Ba m. :004. "Clou d Cl aSSI fica tion using the Textural Features of \leleosal lrnagcs," In/I of H"n/olt' S" "''''I!, 111".
."w,.,,,,f
~5(2 1
3 50.
Dcs bcis. M .. G. Sc ac and G. Szcjwacb. l ~ g2, "A utoma tic Class ilicalion of Clo uds on \1 ET f ()S AT Satellite Image ry : Ap plicali"n~ to Hig h-le ve1 Clouds." J"..rn« / o/Al'pfi,'J Jft'lt:oro {,,XI'. 1 1:4 0 1--4 [ 2.
):449 [--450 3.
ulas. R., Hou . A. Y, lind O . Kea le, 200 5. " App lica tion o f Sell' Winds Scancromctcr and Tt.II -SS \t , I Ra in Rate' to Hu rri cane \ lIa lysis and Forecasting," IS I'RS Journal oj Phm0i!mmme,& RI'm"f.. Se"'InI(.. 5'1:233-243. lIef)', T. F:. a nd G. L.. Berlin , 1')<)2, f'und"mcllT" / f of Remor.. ~1.I' mR "lUI Alrl'lmlO tmerpretouon. ~ Y: M acmillan.
dillG, C, E.. Bowcts.D. ( L and E, U Mitchelson-Jacob, 211U5, "Estimating Suspended Sed iment Foncentrauon s from Ocean Colour Measurem ents in \tode ra le ly Tu rb id Wa l ~'r s: Th o: Impact of Yariahle Pan ic le suite ring Pro perties," Remote Sent. lIIg
Chy le" . P.. Clodi us. W. B " Bender. S. C.. Atki ns. W. H. a nd L. K. Ha lick . 200.1, Sensl li\'i t) o r v e er In frared Total wa ter Vapour h u ma te 10 Cahbranc n Errors." 1'111. Jo ur.. ,,1uf R.''''''le Se,,~ i,,).( . 2 :S~ 2 J ):445 7 4 470.
of Ennronmeltf. 94 :37 3- 3K3.
jinski. S.. Schlapfer. 0 .. Schaepman. M.. Keller, J. and K. Itlen, lUO" , "Aerosol Mappin g o ver La nd with Ima ging Spec lIUS~'UP)' usin g S pccua l A 1I1 ()~' urrc 1<11 inll," In/ f. J"",."" I of R,', ",,,I,' S,'n,'lng, 25(22 ):5025- 5047,
Din e r. 1>. J.. Ma rtonc hik, J. V.. Killin, R. A .. Pinty, B.. Gobron. ~ .. Nels on, D. L. and H. N. Iloloe n. 100 5. "Using Ang ula r an d Spectral Sha pe Si milarity Const raint s to Improve M lS I{ Ae ro,;.01and Surface l{elT ie\ a ls O ver La nd." Rem" ' 1: '~'~""K of f;". I'iron",,,,,,,. 94: I 55 · J 71 .
Derk se n. C. Walke r, A. and G. Boodison, 2005. "Ev aluation or Pa ssiv e Mic row evc Snow Water Eq uiv al ent Re tr ieva ls Across th... Bo real For est/T undra Traa sinon ,,1' West...rn Canada.' He"'''1'' SI"l.I'il'!! " I Envmnnnem, '16 :3 I 5-32 7.
Dre-ier. J and T. II Pa inter. 1(1(14. " Mu his pect ra l and Hy p...r-
s pec tral Re mol e S...nsinl!l of Alpine Sno" Pro perties.R"" I<''' J Earth Pt... " .·wry· Science, 32:465-494
A"""a I
Dox aran, D" fru idd o od. J. \ 1.. La vender, S . and P. Cas tai ng . Wat ~'rs : Application "il h SPOT Dat a to Quanli fy Sus pended Particulate Mal te r Concerurauons." R,'",IIIe -'""".'·'111:ofE" ,,;'w /II/,·nl. 8 [: 14 9 16 1.
2UC12. "Spect ral Siglla lurc of Highly Turhid
Bukala. R. P.• J. II . Jerome. K. Y. Kond ratye v and D. V. Pozdn}'ako\', 19Q5. Optlc,,1 Propernev lI"d Re mMe S,'nti"g of InlaNlo",/(',,"-, flll ""'en ,l'Y: eRe. 362 p_ srdcr. K, L.. Ch en , f . R., Lee, Z., Ha wes. S . K. an d J. P. C anmilam. 21102. MOn{S Ucean Scil:lI('e r..am .~/~ "n l " m TI,,·t)n:li(ul/Ju" i,,' D oc /m ll 'lII, C" .\',· 2 C/d",vl'hyll
ruder. J. v.. Ma)'er. L. A and J. E. II . Clarke, 2000. - \ttlrph ol_ llg) and Proc es ses III La ke Tahoe (Ca lifo mia- l'evada l.- G"'
Fa l~o"' s ki . I·.
G., \1 . J. Ik hre nfelt!. W. E. Esaias, W. Bal ch. J. W. Cam pbell, R. L. Iverson. D . A . Kiefer, A. \ I"rel and J . A . vC>dcr. ItN i'! , !;'llle lllle I'''mory Pm ,h'c/ i"ily o.'M und .-/ IKortl hm D" "l' I" p",ell/ : A .\",-,.."CI: 1'1<111 for J fissi otl /0 1'{u""r Earth, Greeubch: :-..l ASf\ Gvd dMd Spac e n igh! Ce nter. 42 :36 p.
Feid as . H.. Cartalis , C , and A . I'. C rack nell. 2UUU. " Usc of METE O $AT Image r) to Defi ne Cl ouds Linked with Flood s in Greece." I ml JOl/rnu f 01 RemM e' .'leming. 2 1:104 7-1072.
Fcidas, II. and C. C..na fis. 2005, - Applicat ion of an Auto mated Cl oud · lracki ng .·\ Igf'rithm on Sa te Hile Ima ger)' fo r Tracki ng
440
and Monitor ing Small Mesoscale Convecrivc Cloud Systo,:m s:' JIIt/. )uI/mill fit R...,m" , S,·m;"g . 26( J(): 1f, 77 -169~ . Foste r. J. L.. Sun. c., we tker. J. I'.• Kelty. R.. Chung. A.. Doug, J. and II. Powcll.1005. "Quamifying the Uncertainly in Passh e Microwave: Snow Wal...r Equivalent (Ihservauons." Nt!mUIt' S.'mUlJo: uf l ;nl'lnmm,' IIf. 'J4 : I lt7- 20J. Fran ca. n R , and A . P. Cracknell . I'W5. ~A Simple Cloud Masking A pproach USing NOAA ,·\ \I II RK Da yumc Da ta fur Tropica l Are as," /n/I ;'mrt"" "I R.,,,,,,, ,, S<'II_.;ng. 16\9 );1697-
1705. Fra nca. G fl . a nd W S, C'arva lho.1()()4. "Sea Su rface Tcmpoerarcre GOl-.S-K hllmal10rl Approach for the Brazilian C'oaSI.Inti. JOllr fWl vI Rn tl"Il' ~·m/llJ!. 25( 17}:34)'J-)450.
Gabella. \1 .. Michaelides. S. and G Pero na. 1005. " Prchmma ry Ccmpansou uf 1 R\1\l ,U1J grcund-bcscd Precipitation Radars for A Euro pean TC'~I Sue," b, tl j ' '''rlI
Ga rdner. J,. 2002 . "Using Multibea m Sonar 10 \1:1r \I PSs: Tool o f the Future fu r I'lanning a nd Manage m... nt .~ M",'m <, Pm/<'(I-
cd An:" .• -"'PH. 4121: 1- 2.
C H . \ "T E~
12
Re m o te Sens ing of Waler
lIa ll. O. K..• Ri l?~ s. t:..i. A , S..lomonso n. DiGirolamo.:-i. tao: K. J. Hay r. aou. - MODI S Sno w-cove r Produc ts." R S(''''m~ <>1 /:'Il' ;mllm l',r/, 10: .1 : IXI- I<,14,
K in~
$,
., m
Ib n. 1... I'N7" "S pectral Refl ecta nce w ilh Varyin!! S u~ Sedime nt Concemrauons In Cl... ar and Alg ae-Laden \~al
N,·",,,,,,
,
Kor
l4
L.
-rne
lI.m , I.. and 1>. C. Ru ndquist. 191,111. Imp act of a \\iII
(ji te lsnn. ,\_ A .. 1'1'12. "The P"al ,.....ar 700 nm o n Rad iance Spectra of Algae and water : R cl al ion ~h i ps of its \l a ~n il u de and Position with Chloro phyll Cn nct"nlra lion, lml. j""mlll of lkm"' ,, ,~',·m i,rx. 13:3.1t>7-3.\ 73.
Insh. R., 200 0. "Landsat-? Automatic ("Iuud Cover AS6cs;,mm Algo rithm s tor Mulrispcctrnl. Hypcrs pectral. and Uhras~· trallmauc ry," SPIf.". 4114 ~ :.l4X -.3 ~ 5 .
Gordon. II. n., [) K. rlarl. 1. v,... Bro wn, O. a . Rr
Is1:\lO, A .. Gao . J.• Ahm ;.d. W.; Neil. D. and I'. He ll. 2(10~ , "A ("uml'"site DOl' App wach hi Excluding Ih,tlnm Reflectance in Map ping w ater Para me te rs o f Shal low Coastal ZU!lC' from '1:\1 Imagery. n Remll'" S"/lsii/g " f !':m 'lml1llh'/II, <)~ :4n-51.
22:2 0- .\/"
Gregg. W. W, uud N. W. Casey, 2004, "O I(l h~IJ a nd Regional Eva lua tion of the Sl'aWiFS Ch lorop hyll Data Set." H('m "l" Scmill):. vf /:'m'II"oIIIII,'''', '!.3 :4().3-l7'J.
,len,en. J . R., Kjcr fvc, B. K., Ra mse') Ill. E. W., Magill, K, Fo. r>.1cd ciros,C. and J E. Sneed. J, E. I'lX'l. "Remote SensinpJld lvu rnc rical Mod e lling of Suspended Sl'dunenl in Laguna ~ Tc rminos. Cumpc chc . i\l e, ic o .~ R,'"",/<· S"".dng ufEm;ron· mem. 2X:.\ 3--44 .
Guen ther . (j. C.. Cunnin gha m , A. G . La koc que. I' . E. and D. J. Reid. 2000. "Meetingthe Accu racy Cha lleng e in Airborne L1 [HR Bathymetry." "'.'ARSEI. "l'n w"",lill g.1 '~l,h,' LJDAR IJi,rk, h"p.l )re....fcn . Junc 10-1 7, 1: 1- 2 7,
Kah n. R ., Iqq,!. G.-na ,,! 11I/"II,IIl<"l"' '' t il .HISH. Pasadena, t\AS.-\ JP1.. hllp :/lw ww -mi sr.jp l.na sa .g o\ imi inlr o,hlml.
us u. n K.• Riggs. C; A. and V, V. Sal"ml,nso n. I'N5 . -nevet. opme nt o f Method s for ~ a r p ing (jlohal Snow Cover u ~i n g Modcra re Reso lution Imag ing Spect rometer Oala:' H.-",u l l! .li,.·m ing of E""; ",,,,,,...,,. 54 : 127·· 14(1
Re fe
Ka r.iska. M. /\., Hu gueni n. R. L.. Beac ham . J. L.. Wang, \1., Jen sen , J R. and R. S. l.a urm a nn, :!:1l0 .j. nAVINIS Measureme ms ,,' Chlu rophyll, Suspen ded \-tlllerai s. Di~,,,h'cd Organic Carbon. and Turbidity in lhe Ne use River. ~C.W Ph",... g,."mm,'/rll ' EIJgm ,·.'r;nl: & R"""",' S,'milrg. 711f I) :125-133.
l
44 1
"elerence s
King, c., Lecomte. v., Bissonnais. Y. L.. Gag hda di. :-I., Secchc rc, V. and 0 Ccr dan, .2005. "R e mote -sens ing Da ta 35 an .'\ ltc m 3tiH' lnl"ut for the ST RF A M Runoff \1odel: ' Cat(' -
110. (>.2 :1.25- 135.
Morel. A, a nd D. Antoine. 1000, I'j~">t'l11 ",da R.'/ri" ",, 1 ill ew.. I " ' lfer.•• ~ IER IS Algor ith m Tbeoreucal Basi ~ Documem A I HIl 2 . "'. p. 25. hllp:1 en vivat.esa.intrmstrumcrus/meris. pd f atbd _1 _(N . pd f.
tOllgsbcq; , l OllS. F. .\11:11 \I" ltjhe'lm Ec ho SOl"',}"", Ho rte n. 'lOf>l.ay: "'"n gs her~ , l ne . , hllp ;II\\ \\\\ ,l.nugs b
M umby, P. J.• E. P. Green. A. J. Edwa rds lind C. D. Cl ar k. 1<)9 7, "C.. tal Reef Habua t-m..ppmg : Hu w Much De tail ca n Remo te Se nsing Pro vide?" \tarim>HinluK.... 1311: 1<).' -202.
{roger, S. and R. J law, 1(11)5. "Sens ing lhe Sea ," Tn'n, /.' 81OIcchnoflJ/{l. 13 15 1;2 5tl-2 50.
\1 l1~ t.ard. J . F.• Staid, \ 1. 1. a nd \\i. J. Fri pp, ~OOI. " A sc mianalyt-
j"
tncn. \'.• Frordefond . 1. \ 1.. l.a het F. and P. Casta ing. 1/102, ""'>POT Sha llo \\ w erer Ua lh) metr) o f A \h>tlcrald y Turb id Tidal Inlet Ba se d o u ricld Mcasu rcme nrs," R,·mOl.' .~·mjng
vr
ical Approac h to the Cahbranon of AVIRIS Data to Reflecta nce Ov er wa ter :\ prl icalion in a Terllpcr ate Est uary," H.:mut~' S
"r £""/"''' ''' <:111, 75 :33S - 34Q.
£",.i" ",m,· tI/, 1I 1; 1.\0- 14 1\ , legleuer. C. 1. diU.! D. A . Roberts . 1005 . - Effec ts of Chan nel \lorpholog) and Sensor :-. ratial It.;,s o hu i,.n on Ima ge-derive d Depth Esum ares." R"""" .: s.·mlllg (If Environment. '>1 5 ;2) 1147,
NOA,' csc, 1/ll)(>. SinK'" H,'"", Smwr. Ch arleston: 1'0AA Coastal Sef\h;-cs Cc nlt'r, www.csc .noaa.g ov 'crs rs_appp~ sensors. single _lxa m. hlm. :'ol O 4, .~ ()m <:c of ( ">ii.;t Survc y. 20111>. S/d...Scan untl .\Iltfltb.!um
lq k iter, C. J. g o bcrts. D. A.. Ma rcu e, \\' A and M . A. Fonsrad, 1004. - Passi ve Optica l Remote Sen sin g o f River Chan nel \t ()rpho lllg) and in-s trea m Habitat: Ph ys ical Ba sis and Feast~ihly," R.'m ole Sens ing of Em 'm "'''' ,''' ' , '>1 ) :4<) ) -51 0.
SOVA R_ Wa.-, llL ngton: :-IOAA Omce of CO~1 Sune)". bllp :1f cbart ma kcr ne d. noaa.g o v' u s n 'wrec ks, hrm l. ;..lOAA ROC. 10115. ~ EX RAD WS R-!':Rn. Was hington : J'\OAA Radar Oper atio ns. hn p:li \\ ww.roc noaa.gov.
Lod hi. \1. A ., IJ. C . Rund q uist. I.. Han and M ,:-' . J uzila . 1'1"'7. "The Potcnnal f
J C. Harker, I'1St> . "Landsat MSS an d 1 M
O pl.-..: h, ::'0 06. S!fO.U.S- / (J()() , Toronto : Opt..eh. Inc .• Hll p:1 \\ ww.o ptech.o n.ca. O'Reilly, J. E., Maritorcnu . S. , Mitche ll. G., S i..gcl. 1),."1 . • Ca rd er , K. L . Garve r, S. A.. ("I a t . Ill'l l'< . "() ee" n Colou r Alg orilhms for ScaWiFS:' .Immwl '~I (,",' 0I'h,\',I'i<"l11 Research, 10 3(C II ):249 37-2 -1 '153 ,
aud 2 1 co -a utho rs, 2\1110. "Ocean C olo r Cblorophyl l Alg urithm s for Se:t Wi rs, OC2 , anti OC4: Ver s io n 4 ." in
t ) ' Rerlly . .I, E.
Post-Cahbrarion Dyn am ic Ranges, Exua tmo sphc ric Rc Fl e elance and nt S,Llc ]lile Temp erature." f. w H/s'" r,' "!llIi,:ul ,Il,'"t,.,,
S HiHooker and E. R. F i rc ~t
l:3 - K.
( 'uli nr" t ilJlI lim/ Vo l idllt iOIl A 11<111,....". Part 3. J'\A SA Tech nical Memora ndum. 20nO·2 06lN 1. G re enbelt: c s rc. II :<)-1 7,
n."-
Miller. R. L. and Mcx cc . 2004, " Using \ IOO IS Tt'rm 150 m Imagery to ~lap L'oncentrnncns o f Tota l Su sp e nded Matte r In Coa sta l wasc rs." H,'", ol" S " f1SIII.I{ "I EIII'irullm" llf. 'J): 2:59-
260.
Pasqualini. V.. C- l' ergelil-f',Iart ine . C . Fe rnand ez and G Pcrgcnt. I
m" /.. S"I/,in!!, 1!l(5) :1107- 1177. Milche ll. H. G. , ~ fJ(H. 0 /" ",-,1 /IIIU/.:' " IC I./) Slu" JurJ ..fl);!urillm ls 10,I-lI. CORO U ,,,,,I };4 911/ : Cu /ihmfi,,,, " ".J 1;,/id,lIio'l . htlp:llsha raku. en rc. nasda.go.jp ( j U / m l.'c tl 2(11l ll( 1_0 5.pd f.
'.tODlS. 20M, .\fOV IS II" ",.' rag... Gr eenbelt: J'\ASA Goddard Space Fhght Ceme r, htt p:/o mo,tis.gslc. nasa. go vi.
Pinkerton, \1 . H.. Richardson. K. \1 .• Boyd, I', W.. Gall . M.P., Zc!d ls. J. L.. 0 11\ cr. \1 U. and R. J. M urphy . 2005, " Intcrcomp" risun o f Ocea n Colour (b nd-ratiu A lgor ith ms fo r Ch loroph ~ ll Co ncc ntration in the S uhtrop ica l Front East of New Zealan d : ' H.,,,,,,1l' S"", jn.l{ o f E"vmmm,mf. 'J7:)8!----402 .
Cll w n :n
442
Rams e y. E. \V.• J. R. Jcns... n, II. E. Mack ey and J. Gladden. 1 ~<,l2. " Re mo te Se ns ing o f Wate r Q uali ty in Act ive 10 Inactive Coo ling Water Re se rvoirs,' {111/. J""rnn/ of Remote Sen.om g. t3( IXI:3465--34IlX.
Re ynu lds. R. W. and T. \1 . Smllh. l'N4. "Im prov ed G lo ba l se asurface: Temperature An alyses Using Opurnc m lntc rpola lion, ~ J ,mrn<11 vi e li",,,,e, 7 :')l 9 'J-Ilt.
-ne
Rundq uis t, D , c.. J. t . Schatlcs and J. S. Pc-a lo e. 19'15. Response o f Volume Refl ec tance Man ipulat ed AIg.. ! Co nccn aauons A bove Bri gh t and Dar k Bottom s a t Varicuv Dep th s in an Expcnmc ntal Pool," C<',....<1r1
'0
12
Rem ote Sen s ing of Water
Measurements Ilf lhe ThermalPlume from the Daya Bal.~ d ea r r o wer Stanon. C hina ." Rt'/Iwte S",,~ in.g of En"iron 1I~ : 5()n-5 1 5 .
Tan g. J., Xue. Y., Yu, T. and Y. Gu a u. 200 5. MA crosoI Optd Th ick ness Dctcrrmnauon h~' Exploinng the Synl'rgy ofn i RA and A lJ Uc\ MO(}lS: ' H"molt:: s..n.~mx oj E,r_in!/!_ Q~ : J ::i -3 3 .J .
Th oma s. !\ .. Byrn e, D. a nd R. We athe rbe e. 2(102. ··Coa.w SQ Surfac.: Temp...raru rc Var iabi lil) from Land sat Infrared DaD.' HeM"/" .w m mg of tom ·itT/nmi'nI. l\ I :1n 2-272.
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Ru ndquist , () C . l. Il an . J. I". Sc ha llcs a nd J. S. Peak e, 1'1%. " Re mo te \ka surc rncnl of ,\ 1 ~ .11 Chlorophyll in Surface walen : The Case for the nrst Dc rivanv c of Refl ec tan ce Nca r MIO nm ," PholO~'am m,,/'i(" EnK", et',mK & ReRJ(,te Sen .unK_ 61(21: 19 5- 100 .
TR \t \ t. ::00ti, I 'i<·ul Rui"ft,fl Jk<-l-.ufl.·Mt'm Mis' ion (TRW If"",e P"g e, (jrt"e'n..,... li: (i S~C . hll,, : ll l nnm . g~fc .nasa , ~ov,
L 5.-\C E, 2006. SHO ALS, \l o hile : U. S . ,\ nn) Co rps ofElgine ers , htt p://shn.ak sam .usace.anny.m il defa uh.htm. US D:\. 1
Sch ill. S. R. and
J. Jensen. I'N l... ~ M odeli ng 10 Predict St onn~'a
ter Runo ff i n Withe rs S wash Mvrtl c Beac h. Sc." /'ro..·eedmKj. Urban and RegionalIn formation Sy stems. Char jone: 83 - 93.
l jS ( iS . 2U(ln. I'o r i/ it" ,'ieo -f/fH>r Mt1Jll1l" g Image.f .
Sch ultz. G. A.• 1':11111. "R em ote Sensing in Hydrology." Journal
,if / ( I'd",I" KY'
l oo:1 3lJ · 2 6 ~.
1 'J'I~ ... Snu ....' \1app ing ill Al pine Rc gions with Synt hetic Ape rt ur... Radar ," IEE E Transactions ,m (i('m , ,..", e (m d H('mote ,""mlll.l':. 32{ 11.
Shi. J.• J. Dozie r and H. Ron.
p,..
1m" H""eI (l j'rwm .' III. \-lorri s: USDA Agricultural R~ search Se n ice]. h www.flc .nrcs .u!>da.jo:llVi!.luv.q ag nps.hun. W;l~hing1oXl:
U.S .
wc«. G. R, and C. E. Wigg ins. 1000,
"Airborne Lida r BllIbllll-
ctry inrhc Management of Florida's Coastal ZOnc.·•Illfegr(ll(ol efll /"/ Lo u... AUl umn :nl) - 72.
S mith. E. A . and III others, 2 00~ . "Intcruancnal G lobal Mea s ure mcnt (0 1'\-1) Prog ram an d Mis sio n: An O verview." in V. Lcvizzani and 1'. J. Turk . bh.• Me'I,lI/rilli< l' rccipuouonfrom Sp(/n ': F.URAINS·j T and 110(' Filum' , London : Kluwcr, ~ 3 p.• hl1p:J/gpm .gsfc.llasa.gov /g pm _overv icw.prlf
Wulfmcycr, V., Bau er. II.. Girolamo. P. D. and C. Serio, 200:. "Compa ri son of A ctiv e and Pass ive Wa ter Vapor Remolt Se- nsin l;l frlllil Space : An Analysis Based o n the Simulal~ l'crformuucc of I/\SI and Space Borne Diffe rential l.bsor)'" linn l.l DAR ." " .'moll' Sl'I1" 'ill~ nj f.'ll l'i r m mr.'nI. <,1S :11 1-2 30,
Suplee. C.. 19'1'l. "El Nino nnd La Nina : Nature's Vicious Cycle." NIJliml
YUIJnl;l . R. A .. C . /\ . O nsl ad. D. D. Busch. and \1/, P. Andersen,
Tang, D.• Kawamura, 11.. l.ee , M. and T. V. Dicn, 10 03, "S easuna! and Spatia l Il islri hlltio n o f Chlorop hyll , I Co ncentra tio ns and Wate r Co ndnic ns in the Liulf uf Tonkin, Sou th China S ca ." R,'lI w /e Seming "/ Environment, llS : ~ 7 5---4113 . Tang. IL Keete r, D. R.. \\/'IlJI,t. Z .. Lien . J. a nd II . Kawamura. 200J b. " ,\ VIl RR Satellite Remole Sensing a nd Shipboard
Iu'J4 . "1!/"ic lllw m l ,v",r· l'o i m SIIU R '., /'o/llllioll lft!
Eva luatiun o f Re motel y Sensed S no w-cov er Products "i lh Constraints from Streamfl ow and Sr-,;O T EL M easur ements," Hem,,/(, S<,mm~ II) f.·II\'im lml<'lIf. ')4 : 2 1 ~ -2J I.
13
Remote Sensing the Urban Landscape
U
rban landscapes are composed of a diverse assemblage of materials (concre te. asphalt, metal. plas tic, shingles. glass. water. grass, shrubbery, trees. and soil) arranged by humans in complex W3)' S to huild hous ing . tran sponntion systems. utilities, commerc ial and industrial facili ties. and recreationa l landscapes (e.g.• Small. 2 ~). The goal o f this cons uuctic n is hopefully to improve the quality o f life. In many instances. urbanaanon is lak ing place at a drarnanc rate te.g .• A U~'h et al.. 2(04). often without planned development {referred to as urban sprawl) (Clapham. ~OO3 : Wilson l' \ al., 20033). A significam number of bus inessmen and .... omen. pub lic organiza tio ns . and sclc n11Sls constannv require up-to-date in formation about the city and suburban infras tructure (Carlson. 200 3; Herold e r al., 1003, 20041. For example. detailed urban information is required hy : city. county. and regional councils (If governrn ents tha t a] legi sla te zo ning regul ations to hopefully improve the quality of life in urbanized are a", and bj would like 10 model [predict I me.' locat ion of' furure urban gr owth: cit)" and sta le de partments of commerce , .....hich are mandated development, onco to increase the tax ba se ;
10
st im ulate
tax -assessor offices, which must maintain lega l geographic descriptions of every pa rcel oflaud. ass ess its value. and le vy uiux-rn lflagc rate; county and stale dc panments of transportat ion that maintain ex istin g facilities. hopefull y bu ild ne w Iac iluics w ithout damag ing the environment. and prep are for future tra nsportat ion dem and: puhlic an d pr ivate utili ty compan ies [e .g .• water, se.... cr. gas , clcct ncny, teleph on e.'. cab le ) 10 predict whe re ncw dc r nund wi ll oc cur and plan for the mos t e fficient and cos t-cffccriv... metho d ofdel ivering the se rvic es: pub lic service co mmissions, wh ich arc mandated to make the utili ty se rvices availa ble economica lly 10the consumer: depart ments of parks. recreatio n, and to urism to improve public recre ation facilit ies; de pa rtrnerus of emergency management/preparedness and homeland security, whic h are responsible lo r remov ing rhe threat and/or m itigating destructi on and allocating. resourc es in the event ofa disaster or terror ism :
-143
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\ 1.
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...dn hydro logic cond itions. cli mate .,nar) ' prod ucnv ny te.g.. Imho ff: 2005,. .: educated , professional users o f urban info rma tion oJ' hngworth, lyQ7; Jensen a nd Hodgson. :!0(4 ). The urban suburban land they manage or develop is o f signil1cant monetary value. Therefor e, it is not surp ris ing that c it)". county. and slate agencies as we ll as private co mpa nies mvest hundreds o f milliuns of doll ars eac h yea r ob ta ining acrial phot ography and other form s of remotely se nsed data 10 extract the requ ired urban mformauon, Idea lly'. most o f thi......patlal urban informurion il> placed in a national spatial data infrastructure where it ca n be accessed by a variety of public and private users .
13
Re mote Sen s ing th e Urban Landscape
govc rnrncms, the priv ate sector a nd acade mic c and the internati onal community [Jensen ct al.. 200~1 l "kwf0l'illK Spa lin/ lhll" Infrastructure: Tile SDI C~ ,GSD 1. :!OO(,) introduces reg ional. national and nat ional organizations to the co nce pts and su ndalds implcrncming a g lohally eornpa nble Spat ial Data In nn e. Se lected da taba ses from the South Carolina Data Infrastructure are show n in Fig ure J3-lb i!.J1d C Plate l.~-I . Urba n Re s o lu tion C onsidera tion s
Many of the de tailed urban/suburban attribu tes that ncsscs and agen c ies requ ire are summarized in TaNt r and Figure 13-2. Thi~ cha ptcr review s how remotely data may be of valu e for the collection of these aunbae, rem otely se nse urba n pheno me na . it is tirst IICces~ apprecia te the urban anribute's te mpora l. spec tral. and lia l rcsoluuon cha ructcnsucs.
Nationa l Spat ial Da ta In fra s t ru c tu re
Urban/Subu rba n Tempo ral Resolution Consideraxa
In the Unit ed Stales (a nd many o ther nations) . an interagen cy Federa l Geograph ic Data Committ ee / FGDC I pro motes ihc coordinate d devel o pment. Ul>C. sharing. and d issc mina lioll l1 f the nat io n's d igi w l geog ruphic informauon re sources ( FODe , 2( 06). T hi s na tionw ide dat a publishing effort is known as the Nal irll1<11 .'i" lIia/ lJ
Th ree typcs o f tem pora l resolution should be consitkret whe n mo nitoring urba n enviro nme nts using remote dat a. First. urban/suburban phenomena often prog:i:SS thro ugh an id\' lllitia hle (/el'e/opml'lI/al cycl~ much l ike \~
tauon progresses through a pht·/I
four !rtllflt'wl'l"k Ihemll/if' (IOlah, l ln·: cadastral
boundarie s or poluical un it.. hydrology trans po rtal io n
and several nth ..r themattr t"'I"n.t.~I'\. suc h as urb an/sue urban land usc and land cc vcr. The H IDC dc\c1,)pl> gCl>l> patial data standa rds for implemen ting the 7'lSDI. in cooperation w ith stat e. loc al. and tr iba l
2. land subdiv ision [l.c.• parce ls su rvey ed and gradcdt 3. roadst din or puved j 4 . hu ildi ngs (presenc e or ab se nce )
5. landscapi ng (partial or complete]. Single- fam ily re...ilknl ial ho us ing dev elopm en ts III S. Diego . CA. undergo a sunilar cycle [Figures 13-3bc).lt
445
Urban Re s olution Cons iderations
it)'.
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at National Spatial Data Infrastructure frame wo rk foundanon . thematic and lither layers (a fter I GIX' , 20061. b l Selec ted data base s Innu Sou th Car olin a's spatial 1.1"13 mfractru ctu rc ( pl.:a'>C s..' t: C.. lor Plale 13- 1).
j
, imperative thai the image ana lysl understand the tempo ral development cycle of'r he ur ba n phe nom cn .. heing a na lyzed . lfi t is not understood. embarrass ing and costly image interprctation mistakes can he made. The second type Ill' temporal resolu tion is how often it is possible for the remote sen sor sy stem to colle ct data of the urban landscape, e.g.. eve ry X days, I fJ days, or on demand. Current infur nuuion is critica l for mos t urb an applications. Generally, sensors that can he pointed o ff-na dir t c.g.. Gc-oEye IKONt )S; Dig illllGlooe Quick Hirdl have higher temporal resolution than sensors thut only sense the terrain at nadi r (e.g., Landsat Thematic Mapper). Urban nppllcntions are usually nut as time-sensitive as thnse dea ling with high ly dynamic phenomena suc h as vegetation where a life cycl e might take place durin g a sing le seaso n. For these reasons. most urban app lications tcece pt traffi c count trans po rtation studies and emergencie s) only requ ire that imagery be colleered every year or so . Orh ital charac re ns ncs of the satellite platform and th...' latitude of the study ar ea also impact the revisit schcdul c . Remote se nsor da ta may be co llected o n demand from su bo rbita l mrcraf (a irp lanes. helicopters] if weather co nditions permit.
Fina lly. tem poral resolut ion may refe-r to ho \\ often la nd managers requir e a cc n am type of infonna uon. For ex ample. local planning agcnci cs may need precise population csnmate s every 5 - 7 years in ,u1d iti(l!1 III the est imates prov ided hy th c de cennial census. The temporal resolut ion requiremears for many ur ban application s arc summariz ed in Table 1.1 -1 and show n grnphieally in Hgurc 1] -2.
Urban/Suburban Spectral Resolution Considerations
Most imugc nualyst s would ag ree that when ex tmcnng urba n/suburban in formation h o m remotely sensed data , it is o ften more important III have high spatial reso lution (c.g.. S 5 x 5 Ill) tha n h igh spectral reStI]utio n {i.c., a large number o f hand s). For e xample. loc al po pulat io n est ima tes based on building unit co unts usually require a m inim um spatia l rcsolution nfO . ~ 5 - 5 m to .X2 n - 16.4 fl ) to dct cct. d istinguish betw een. and-or identi fy the type- of ind ivid ua l bu ildi ngs. pracuc ully any \isiblc band tc .g.. gre en o r red) o r near-infrared spectral band at this spatial r~'S(llul ion will do . O f cou rse. there must he sunlc tem spec tral contrast be tween the object of i nle re~t (e. g.. a building I and ih bad, ground [e.g.. the su r-
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clear p.. l y~oll~ rcprcw nt thc spaual and temporal r.....utrcmcnte for sd\'Ch:d urban annbutcs hs ted in Table 13-1. Gray boxes de pil:t the spana l and tempora l charac teristics o f the majo r rcmo ..: sensmg ,)'\ lcnt5 111.11 may lie used to ex tract the requircd urban infurma llc," (adapted from Je nsen and Cowe n. I
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II ~ en'''ll~ do: nwtd IUld prod""'I "'" potential C - k"ld Lnll-lnLul.l"," ... n e~ s l",u'I""'t.t iu" In fr•• lruel " r r 1- ~ ... I n." '" crolerline 12 prt'C ir;c n.wl " io.ltb
T3 - lrallie counl S!oo>es (.....'5. ~,I"f>L"'.,'"
1- 5 )'''' ''''
t'tt.:. l
TJ - ... 1'1."'11 " ud,,,,, tlilil~
lI3 - I"C~1I""
or p" Ie., m~nll<,I"s •• uh,llIli,~u
[li~i l. 1 H e..tinn Model (l) F:~11 0 1 cl igllal'''l f~c~ model u"d 'ur d 'll'lu lt"mll n n",
\ltlell...,I"r.: in l lJ " lll \! I ~ w""l h...r r r,~\ld iuTl \12 CUfTC1l1 Irmp",alut'C \!J - , ,",,, "i r alld pr"C ;r i l~ I''' " mud " \14_ "",.,,'" well,her m,,,," \15 ,m" nno,in!! mh,," h"al i,I Llnd ellect l'rhllllll) d r"I"I!..\ ' HI impervi ous ,urr",,~ m"pp",!! H2- ,ucam ~enl"rhtl e and n,>od p lain dc l ill~all un ("ririrs l .:,,,; rnn ,,,,·" t.l ,\ ru , \ " ~,, m " n l Cl _ " ..hie "",,,, ill' " ,,"' ;ronmclIls C2- d)'113mic ...:nsu;,., "''''i",nmcll b Di...
1- 2 years 5 - 10 m;n 10 -6Om;n
"a" .\" _!'I R. un....R
0.2~ - O. ~ m 0.25 -0.5 m
Pan _\' - MR Pen- V" ihlc Pan • Vi, ihlc I'an _ Vi.iblc
1- 3U m IU5 _ 11.6 m
.'a" _V, UDAll
I - 30m 0.25 - n.s m
In(ra,' r u rl u ,-r
UI - ~",IIII, lny hn'-IlI.lII'I''''l!.nd r"ull ng V2 - rn: c '",: ""lily line " 'idlh, ri~h ... ,(-,.."y
't'" I'm" rJ:~nc)
I
~
5 yean.
1- 2 ycal'1< 1_:: ) ""n.
tlZ~
-
n,t> m
I'an . \1- !'I k
r .m,·h",nlal'C, lt D AIl
5 _ 10 )'c"n. 5 - to year'
0.25 - 0.5 m 0.25 -0. 5 til
Sl"rw J'an .V;, ihle, l. tnA R Stereo l'all -Vi, ihle, lt DAR.
3 - 25 min
I - Sl m I - S km I · 4 km I -4 km 5 -;\O m
V - Mk- n lt Till WS lt ·llKll R"dm WSK_llKIl R." d" ,
3 -25 min 5 - lOmin 5 - llI min 12 _ 24 hr
I -~ y cars
0.25 - 10 m 1 30 In
I - 2 yea rs l -b "" "'Ih,
(US -2m
I - 5 years
," m
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V _ M R· \
Rr'\.IIn. c
Dfl -
rn:-cmt'rg""c ~' '1lI.lI~n)
DE1
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D13 - damaj!'...t hUII.Utg scod OfA - damaj!cd 1ran'P''''.I;on Df.$ - datn:JgN "ti\lti"", r;cn ;""
...
Spectral
Spa t ial
Tem poral
Anribute s
1 - 5ycan 12 hr -Zday..
1- 2 days 1-2daya
1 - 2days
1- 5 m U2 5 - 2m 02 5 - 1 m 0.25 - l m 0_2~ - 1 m
P"n ' V , !'IR P.n · "Ill - Radar Plln · ~ lll. Pan _ ~ lll. Pan - NIR
C1 IAPTER
448
13
Rem ote Sens ing t he Urban l andscape
a. Single-fami ly rcsidcnua l development ncar D..."T1\l.'f. co. A pared ofland 1n3)' progress from rangeland (stage 111<) fully deve loped, landscaped, single-fanuly residenual housing. (stage IO).Th e stages o f reside ntia l developme nt w crc identified based on the presence or ab-ence of five fa ctors. including pa rce l clearing, subdivision, road.., buildings, and degree oflandsc aping (Jense n and Toll. 1983),
h, Cleared. subdivided. terraced lots with dirt wads 0 11 SIl'eP slures being de veloped I'msingle-family r~':;I ..lcntia l housing in San Diego. C,\.
Figure 1303
c. Smgle-family rl.'si tknlia l hllus ing in various stages of I;l\Usuucuou. Ro.... s on e und hll' ill Illl: IOIl1c1l have foundation f,"-llings. Rows three and four have sub tlooring and arc being framed
Examples {If slages in the development cycjc of single-family rcsi.lcn li,\l housing in Denver, CO, and San Diego, ( 'A Remote sensor data may capture urban hllld use in 011<: 01 many sl
ro unding landscape ] in orde r to d e tect. dis tinguish be tween. and ide ntify the object from its bac kground. Th ere are relat ively co arse regions o f the electromag net ic spectrum that arc very use ful fill extracting certain types of
urban, sub urban info rmal ion ITable [3-1). For exarople. USGS Lc vcl Ifl l.mdcovcr is bes t acq uired usi ng the visible (0 .-1 0.7IJ m: V). near-in frared (0.7 - r.t u m : t\ IR I. middle infrared (1.5 - 1.5 um: \ lI R ), and or panc hrom at ic (0.5 - 0.; j.I\\1) portions of the spectrum. Bu ild ing perime ter, area, and
u,
n Resolution Considerations
II HI
449
+
t
'" "'"
70 -
.'III(S -
-
", -
.," '"
!O - '
, s
,
~
"
1
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• ,•
~
,
~
~"
,•
..
Urba n/Subu rban Spa tial Resolution Considerations
,
.."' - , ....!~~ll!' " ..
O '~ ===
•
~ "i
00 - -
11 1
"'
'" Figure 13-4
• [
II
III
[V
Lind Cover Cia" Level Retanonsnip he m e,.'111 'SGS Land-useLand-cover ("Iasslli<,;"l illn Sysrcm and the , pallal rcsoteuon uf the remote sensing sY_" <'m totte n referred I" as
ground -resolved d i,la llce in HI d e rs ), The Nuunnal Image lntcrp rcta bilny Rating 'ccalc (~II RS t is provrdcd fur comparison. A l"'IIRS vcru rating Sl.Igfcsts lhatlhc imcrpretabibty "fthe- imag e i
information an.' bes t acquired usi ng black-a ud-whnc panchrornuric (0 .5 0 .7 pm) o r col or image ry (004 n.7 uml, The thermal infrared po rtion Ill' the spec trum t3 - 12 urn: T IKJ may be us ed lu obta in urba n surface tempe rature measure ments (DouSSI.'I and Gourmc rcn 2003 ). Acnv e microwave sensors may Ilhla in imilgeT) o f dllud-shroudt'd urban aTt'as (c .g.. Canadiiln RADARS AT C· band . and European Spac.: Agency FRS- I.2 C -tMnd ). l'l·'H· infrared l a~ cr lighl (e.g.• IO::!4 nnt) can 1'0..: USl.'d til l.'olke t U DA R digita l !ourran' model Iinot. illl..:rm.:diatl' and lasl retu rns plus inlensity data ( Iit'lJg..s"n d 31.. 20(5 ).
oc
Unfortun atel y. they also encountered co nsidera b le sp ectral con tusio n betwee n so me urban land cover ty pes te.g .• spe ci fic roo f a nd road t~ pes ]. Smal l (2()()2 ; 200 3; 2~ ) summaril ed how different materia ls fo u nd wi thin the IFOV of a sensor s),>I..:m treterred 10 as endmrmberv s uc h as co nc re te. aspha lt vegetat ion. .: 1<,;. ) contribute to urban spec tra l reflccrane e and how the y ca n he discnuin gted using spec tral mi xtUI'<' analysis [re fer III Jensen (2005) fo r ,I discussion or spectral mixtu re analysis]. So metimes the only way to extrac t the urban infonna uo n req ui red is to utilize mufuple lyres (If remote M'nsu r data 1I1 the san lt' ruvcstigauon refc rrcd 10 <.I.S melts-sensor data fusion (Gam ba ct 31.. 2003 I.
\lan ~ urban applil'i1liuns can also conducted using hYPI:r. sp\:c tral fem tlte sensor da la_ I krold cl al. (::!U04 ) oolkcll'
tra ined image an a lysts do rely tin black-and-whitc ton ... or c;slor ill aeria l photog rap hy or other types o f imagery to
e xtrac t usefu l urba n in formauon, How eve r. in many mstance, the Ib'omt" /ri.. spa tial clements of ima ge intcrprcranon such as obj ect shape, size, tex ture. orie ntanon, partern . and shado w srtbouene nrc onen j ust a ~ useful if not more useful ~ a ll c !.... mcms ar .... discussed in Chapter 5), Generally, thc h igh cr the spat ial resolution (If the rem ote sensor data . the more detailed info rma tion that ca n be e xtracted in the urban envmmmem. Uut ho\lo do \lo t' know " hat spaual resolut ion ima geI') to 1L..... fo r a speci fic urban app lica tion" Fonu n
( 'rileria
One solut ion migh t he 10 use the milua ry and or civilnm vers ions o f the National Image lmcrp rcunion Rating Scales (N [IRS ) de\ do ped by the lmagc Re solution Asses sment and Reponing Sl;lnda rd~ Committee ( 1RARS ). :"J [1 RS is the met ric use d by the intel ligclll'e comm unity to charcctcrizc the usefulness o f imag..:I') for intelligence ptlTJllISCS [ Leachtenauc r er 31,. 11)9X: Logicon , 19'J 7; Pike . 2U(J6; FAS . 20( 6 ). \I any urban una gc-imcrprcta rion las lu. arc sim ilar to rhosc re'luired lo r int.:lligl' l1ce app lication s. Ttl.: f\ IIRS criteri a consist Ill' 10 rating It' \" els (O-I)J till' a gi \-C:n Iyl'\: o f imagery 3rrhcd al thw ugh <,valuation by tra in.... d image ana lyst s. Th .... IR..\RS cllm m itk l· makes it c ko.,r lhal spiltia [ resolUlion (grountl-reso lved d ist3nl'el is Ililly I'n e of Ihe mcasuft'S of th... inte rpre tab ility of an image. althoug h il is 3 \-"Cry imporlanl onc {Figu rc 13-n O lher (;ll-tOrs such as film quali~', at mosrh~rie haze . Cll/llraSI. ang le of oblh.luit y. and no is..: ean rl'
450
C1LU'ln{
it is nOI opt imu m to r this discu ssion because I ) the civil NIIRS criteria were o nly recently made available t Leachtcna uer e t al.. l ')
A figure of merit fo r measuring the reso habi lity o f a film ca mera syste m oft en used by pbotogremmernsts is call ed the
area ... dgJII.,'; '"'I.'r
13
Re mo te Sens ing Ih e Urba n Landscape
aeroe
lIumill" I .lpal i,, { It'.'IIIUliu l/ ( al ~(J call ed K,v,md-r~.\IJI\'ed
TablE
ex am ple , the Land sat 7 Enhanced Thema Mar re r Plus ha s cix multispectral bands at J O x 30 m nal spatial resolution . a 15 x 15 OJ panchromatic ba.nd.w flO x 60 m therma l in fra red band . The S POT 3 HR\' has three mul tispec tral ha nds w ith 20 x 20 rn nominal reso lutio n and a sing le panchromatic band at 10 x 10 m.
fa n c.. ). For
Another ge neral. nom inal spatia l resohnion rule is that ~ needs to be a mi nimum o f four spati al o bservations It,,pix els ) w ithin an urba n object 1(1 idcnufy it. Stated anodllr w 01)'. the sensor spat ial resolunon should ~ one-half widt h ofthe smallest obj ..ret of mtcrc'lit. For exam ple.toidelti l)· mo b ile homes that arc 5 01 wid e , the m inimum sp.vilI reso lution o f image ry needed wuhour haze or osher pm.. lcms is ~ 2.5 x 2.5 III pix els (Jensen and Co w en. I ml. II is p..l:-:-iblc III idcnt ify IIr hmJifmi/llIp la nd cover versus other land cover for regional u r global applica tions ~ co arse spatia l re solution satellite re mote sensor dati. FIl ex ample. Giri ct al. 120(15) compared the agreement bl1\l~ the Glob al Land Cover 2000 dataset derived from the FrClld: S POT I x I km \ ·cgl,.'1a tion sensor- data, and the MODlSG\(l. ha l Land Co ver da taset de rived from .\10 DIS 25 0 and 500 11 data rcsam pled to I x 1 km . Unfortunately. tho: pcca agree ment fo r the IIr h(/l1lhllllfUP land-cover class at the pc" pixelleve l was poor in 15 ofthe 16 biomes examined. T he temporal, ~Pl"CI r.lI, and spati al resolution requirements lor selected urban aunbute, summarized in Table 13-1 atlIJ Figure 13·2 .... ere synthesized Inuu practica l cxpcricrcs report ed in j ournal art ic les, sy mposi a. chapters in books.and go vern ment ami stll,.· il:ty manuals [e.g.. Avery and Bellin, 19'J2; Light ( 1'l 93. 19% 1; Ph ilipso n, 1'l9 7; Haack ct al, 1l)'J7; Jensen and Cowen. I IIQ<); Donnay et nl., 2001 ; Jensen et al.. 2002• .lenscn
Remote Sensing Lan d Use and Land Cover
Th e te rm !tm,I II.'e refers ttl hllW thl' la nd is be ing USI."t rial-I:o mmercial silt
c<
IIOte sensing land Us e and l and Cover
)e
13-2 .
Four levels of lhe USGS r.oml-( .:",·/I.'lIId ·C ,,,",,r CI""'I!kmioll "1'.
:lassifica l ion Level
Remote senso r Data Characterislics
NOAA AVIIRR (I. I)( I.ll..rnl./'o.l()J)IS 250 m: SUO x 500 m), Landsat \tSS (7\1 >( 79 mi. Thematic Mapper 00 x 30 mi. Indian llSS (n,; x 72.S m: ) n,25 x .'n.25 m: 23.5 x 2.U mi. SPOT \"egeLJlion 11 x I km l. RA DA RSAT II 00 x 100 ml. aerial (~ 5 0)(
photography 1:120.000 10 I c .ro.ooosca le.
II
LJndsal 7 Hnhnnccd Thematic Mapper Plus pan (I S x 15 m\. SPOT URV Jl'l1l11O x 10 mi. SPOT II R\ ' XS (:!O x zn m).lndian IItS pan 'S .lI x s.s mi. ( i,'I.'!:Y": IKO\,;OS I I x I m pan :" x ..j m mult isp.:ctral l. RA[)A RSAT (11 x 'I rr u. acn al pll(lI~ra phy 1:60.000 to l : l l0.000 ~;Ik
Indinn IKS pnn (S.f\ x 5.S rnl. (ieo!-:ye 111
IV
IKONOS l l x 1 m punt, [)j ~ i l
Uigilal( IIntllt ()Ul(I..Blrll pan CO.nl x 0 .61 m). aerial alM I"g Ill" digitul phl' lllgraphy I :t>,(IO() ro I :20J)(Kl(O,25 - I Ill) ,
htion. popu lation estima tion. lax asscss meru . dC\l:lopen of l oning regulation... etc. (Cu ll ing",~nh. 199 7: Willi et al.. :!OO3b ). This me ans Ilt31 urban information ~led fo r one applicatio n might h" u ~cfu l in another.
and·UseILand-Cover Clas sification Schemos
~ best ....ay to en!Sure that UrOOll infnmlation ueri\ed from rote se nsor da la is use ful in many applic;t1i(1ns i~ t(1 Org:llle II acrord ing til a sta nu" ru ll.eu lam.l-IIW Il r 1
.mcr ir lill P la n ning ,\s..lIda tiu n " I ,llntl- Ullsetl ], \..ificalioll ,sta nd a r d"
lit m()'o.t com prehe nsin: hierarchical c1a..si ticalion lo),st...m urban/ su burbll n la nd us.:: is Ihl' L
I
Jsoeiatio n ( 20IJh j, Th is standard u pdates the ltJb5 S'
451
w ith the I f),'{ 7 ....·'<111.1",." IlIdll"''';u! CIa", ilk" ,ion (S 1(' ) '\/(1/1' lit/I and me updated vorth Aml'rinm 1",IIHfr;af CfoHi(kotinn .\Jullliord i :\A ICS. :!()(l(,l. The L. ll e S requires ex tcnsivc inp ut from i ll .f ill' da ta collection. ae rial photography. and satellite remote sensor data 10 obtain mformation atthe pareel leve l on III..: rilllo\1 ing Ii \ c ch urac rcnstics: uctivuy. func t ion. own ersh ip. site. structure (F igure 13-51 (American Planning Assoc iation . 20(0 ). The "ysll'lT1 provides
LS.
GCt.l l .~.: ical Su nc~
-Land-L'se/L an d -Cover
Cla,,\jli cal illn !")"1(,111 for \'''r wjth Remot... St' n" nr Data" Th.: U.S. Gc" lug i':-lll Survey L.mJ- CldL.llld-Con·r Classification ,S:r." I·m (Anderson et al.. 1'n 6; USO S. 1(,1(,12 ) wa s sp ecifically de sigu c d I" he re source-or iented (land cov en in con tra..l .... uh vario us people or ac tivity (land -usc ) oriented sys tems. such as the SI<1l1d
452
(U.\l'TF I~
13
Remo te Sen s ing t he Urban Lan dscape
American "I ;to ni" !.: ,\ s\ocia linn I ,a nd -lb \ f,>(1Clas,ifka li on
ralTt'1 III IO-S-I Ol:I
10· , ·100 10-5- 100 lU-:"i- IOU 10-5· 100
Fig ure 13 ·5
Actil ll,
Dl.'5C'ription
Funt'tlon
S, ' 1('01
l>r...:riplkJn
2 100 2200
, hI.'l"I'mg
2 1HI
r....U ur.m t
~S1 0
U-la,1 ...10 and .."...·ICeo full . """, ic,", resta ura nt
"'''''
"""131. n"lJg lU\J."
tx>: u
r ch g l UU> 11ll>\JIU\lum
f ll m il U.-c'
2121
fu m ll ll ~
"c hicub r pan ing
5200
f'o1r~ j n l:
e tc .
etc.
etc.
2 111U 5210
fXl lil1es
The Am erican Pbul1ing As"udatiun developed the L..md-LJ'I.>.-.I Cf""\i{icu/i",, S:r "/t"1IJ (Lile S ) that contains rtctniled de finttious (If urban/suburban lnndus c. The system incnrflnr alcs mformntio n dcnvcd il1~ilrl and using remote ~cll"ing ll: dll1i,-!un, Thi s is an oblique aerial ph ul,,~rarh Ill' II 1ll.11I in Ontario. CA. H ypothet ical ucuvU)' and structure codes associa ted with this large parcel nrc idcnufl ed. Sil,' de velopmen t and ownership infor-
m.nion uuributc tables arc not shown (concept eOI
or nations, For example, Table 13·7 documents how the i.and-Use/l.and-t;'ovrr Clw" ilit-arion ,~~'~ relll for Use wilh Remote Sensor Dolo has been modified to include 22 class es for the vanonot tund-Cover Characterization based on continuous production of a U,S. Nanonal Lend-C over Dataset (NLCD ) derive d fWlII Landsat Thematic ~l a pp,; r or other data. Many of the Level II classes arc best derived using aerial photography (US(iS. 2nOfi). The same classes arc also used by the NOAA Coastal Services Cen ter in the creation orthe Coa stal Cha nge Analysis Prog ram (C-CAP) products . l\OAA C-CA P produc ts include land cover for the most current date available, a fiveyear retrospective land-cover product, and a prod uct that documents changes between the two dates (1' OAA. 2(04 ).
"" sn,: i ~ l i " n l ,
Urban Land -Use! Land -Cover Classification (Levels I to IV) Using Remote Senso r Data
The ge neral rd,ltitlilship he1.... ee n USGS lund-cover c1a>sifi. cation system le vels (l - IV) and the nom inal spatial 1'l.'SOllC tion Ill' the senso r system (ground -resolved distance ill mcwrsj was prese nted in Figure 13-4. Generally. CSGS Lc"c1 1 classes may be inventoried e ff ect ively using sersos with a no minal spatial res olution of 20 - 100 III such as !be Landsat Multispectral Scanner (~ 'SS ) with 79 x 79 III oonunal spuual reso lution. the Thcmauc Ma pper (T r-. I) at 30)(30 m. S POT HRV XS at ~O x ~O m. and Indian LISS 1-3 t7~j x 72.5 m: 30.25 x .' <>.25 m: 23.5 x 23.5 m. respceliwl)"l- or COUI'Sl:. any sensor system .... ith higher spat ial resolution C<1It
R.
453
Remote Sensing Land Use and Land Cover
Table 13 ·3.
U.S. Geological Survey I.tI/ld, C,,'/Lm,I,ClJ"t"r ( ·/u ,..,j i< Yll j" Il .\\'., (<:m Ii,,' Use 'nIh R,·mo,<".'Wn.wr
Ta ble 13-4 ,
Uroan Residential. Commercial and Services - Levcl l aud II arc rfl)l1l lh~ I./SG!lwnd-U.", if-" " d·C",·<'r CI,t"I![i,·"tirlll S\" "',,, .lor f " ' j ' ,,"lIh -nsor lJulu. L ~ vc b Ill . IV. and V are log ica l ext...nsions.
R""w,,' ....
lAsl,s (A n..krwn 1:1 al .• 197 6 ).
Classifi catio n Leve l
Classil lc atlon Level
l' rb a n o r S .. ill. .. p La nd II
R~"krmal
12Con uncn: ial and Scn ice'l 13 111IJustn a i 14 T rnn, ponal;on . COO1 munkanOOs, and l"l ihl i~
15 loouw1aJ and Commo.-n:ial C"rnrl<'''~'lo 16 Mncd L:rt>.In or Hu,lt-up 17 \;1Nn or BuilH,&p Land 1 "'ltrk ullunll .• n d ~1 {"ror1and and f>aSIUtt ~2 Un;1\lanh. GIU,n. \-1I>C~1ll"Ib.. Oman...~ ,u.IIl"rh"ul'ufC
11 _
01 111 ........ 1 _ ~
11 1 ' 1 \ · _ . - . " , , _ 111: \_1<_ I I : ~I_,-...
1I11 '~
,IJ,.... .. ( · _ ( n:._ I< _ '........,.... II::':
II:t~~
I :C_ ....... _
. l...... _ ... - , .... '
I:lllr-... 11111'... _
1:11) - " " 1: 11. ..... "" .. _
'21: _ l:ll l ~
1: 1 1 : _
m ll .......... " I : 'l l~ _
Ill l ' 11 11:
_~_l<" ,
\Io .. '-I>R. ~ ..... ,
~.
11.. ' _
hr... 1 l and 4 1 [kc,dlJ<'tl, h >rnt l aoo 42 h ..-rgrccn r........' Lan d 4:! Mv.ed f urnl. lalld
..... _
....._
11' l _ 11 11 _
23 (" OI"lr",c d fC'Cdma 0",:..,,,,,,,, ~4 0dl0If A grM:ull ....lland Ita nllel a nd 31 Ilemaceo\" Ran ~d.nd 32 Shrut>-Brudl land ltantleland H " n ed ~tld:md
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121 l J R _ 111. 1.....,m 111.1 \~ " 1oOI) 1: 1"2["........., ..... ~~ _
52 La~ c , 53 Rc.....rH" .. 54
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u.:.-,_ary)
1111 Ul1ll101el l1I ' :M....
3-noJ E,luancs
lJPH ~
6 Wetlan d 61 f ure ' leoJ Wetl.."d 1>1 Nu n1i',",,' I..-d Wetland
1:1 .11"""'-" ... ......
Oll rtell I.an d
11Dry Sa il Flats 72 llcllcne, 73 Sund y A reas (lIner '1han B.-a.,nes 74 H;H"e 1:0\p<'l'1."d 11.,,<;10:. 7S SII'p Mines, Qu alne. , .. ( iruvd Pil'
Ill " R........_«.....-.:"'I ,..t>I"l 111~ j """'''''''''''' ~ I ' .."''''''' " ,",".,1< ~1I) 1:191 11,"0"')1 ll l¥l f',," ~.I ' .u,"'O'"''''' U I\I-l(""lf 111'l,w,"," "",, 12' '''' '\
r",·.,,,
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tI"
76 1'ran,i,,, ,,,,,1 Areas 77 Miu oG Barren I...ml
I!1QIw
Tund ra
Snn,h and Bru, n Tun.ll;, ~ 1 I krN" Cl IoU' Tu", lri ~1
10 Bare Ground l'undm ~4
Wet Tundra
H5 MC'N TWldra 'I
h a nn ial Sill'" " r I.... 'II P"n"lln,al $no",f,c1d. '12 G ille": '"
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.,OI,...
un MaI",,1
Il .:.!1 HooJolaI
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454
Ta ble 13·5.
Urban lndustna l Land-usc Classificatio n - Leve l I and II are nom the USu S 1...l'ld- U-",il.u",'·Cm'er Cl"" ',14kllU" 1I "'.1'.1/. ,,,,fi'r U.fC ,,#11 R,'mo{t' St'II.l
13
Rem ote Sensin g th e Urban Lan dscape
Table 13-6
Urban Tr.ltl~p,m,l\ i un.
C'om m uni~alit'ns.
Utilities.
Table'
and I'ldu sirilll/( 'ommcrcrat Com otexes- LevelIMol
II das...:s urc fro m the USGS L.,md-U,,·jwnJ·(ortJ
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C lallS iflcatJo n level C lassification Le ve l UI_ IJI~,_
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be used to acquire Level I dal:.l. Color Plate 13·2 presents Le vel 1 urban \":II, non-urban land-cover information for three counties centered 0 11 Charleston, SC', extra cted Landsat .V1 SS da ta ac quired 011 six dates from February 14 . IlJ75.1o Feb rua ry 3. IIN4, Fo r glohnl projccn, Level I landcovcr rna}' be extracted from more C tl lt r s,' -atial resolution imagery /c .g ., AVI1RR at 1.1 x 1.1 km )[S250x 250111(1r500 x 500 m H e .g.. G iri c t al.. 20 1 Typ ical urban spectral re f n zed in Figurc 1., -6 . LJ r'
"steel -gray" on color-i because the urban le rm i, nnd asphalt roads, parkin ically reflec ts h igh prol a nd ncar -infrared radi..r.r lure co ntrasts sharply' brigh t red ,' r m llgcl1la t , vegetation reflects s u.
.ia.unurcs arc summa,I, r typ icall y appears , 'I' -om p os uc images
I'
.i .narily of ccncree "
'lnd hare soil. typ-
,I
, -,
II
.idem green. red.
tt'; 'ray' urban signaraces that appear 1: 1 sges because til<:: 11
(If
near-infrared
455
ftmote Sen sing Land Use and Land Cover
13-7.
LalHlfll lnry Sp c'el r n nu liom...ler ne necteoce C o m mo n Urban .\ Ia te r ia ls
U.s . Gt"vlogieal Survey L,,,,d_V.\t·if.
Characteri~lifs tlf
.i..\~'i;
"",~G -
-
30
: Ot'H lul!"'d 21 Low-lntcnsuy Residential 22 High-Imcnsuy Rcsid<:nl ial
23 Commen;i"li lndustriaVrransponalinn
. . .. . - - - -
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,.
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~
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FON""i tl'd l lpland 41 Decidcous For",..., ~2 Evergreen Forest 43 '-1i.\..-..I Forest
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6 .\ on-:'\a tu ra l \\ "'HI )'
M Orchards.Vmcyard-, Uthcr - Herhaceo u. l 'pla nd "'lllluraIlS,'minalur al Vi1:..' lllliun 71 Ij rasslands.He rbaceo us i Herb aceous 1'1an ll'd iC u lli n ll"ll
SI Pasture.Hay lI2 Row Creps S.' Small Grain s S4 la llow lI5 Urban/R ecreation Sf, G rasses q W"'lland \II Woody
Wetlands
92 Em ergent I lcrbaccoux Wet lands
mcrgy wh ile abso rbin g mu ch of th e inc ide nt green and red ~a\( le ngt h energy, as d isc ussed in Charter 4. Water abso rbs most of the incident radium I1U \ , causi ng it to a ppea r d a rk o n color-in frar e d imagery, easily d istinguishal'lk from the urban lands cape, Co lor co mposites o f ..lownrown C harl l:SkKI. SC produced usi ng many orthe major se nsor systems, are provided in Chapter 7,
· -
H
__
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~t Health y gra...~
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A ~troturf
j Barren
31 Bare Roc k/Sand tl ay 32Quarric~tnp \ linCS
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Figure 13-6
05
.
Asphah sh ingle (b lack)
o (1.4
.
0.7 0.' 0.6 Wa\ e le nglh , um
O.Q
(0, 0
Pc re<"m reflectance curve s for com mon materi a ls found in urban en v rroemcnts. The reflec tance spectra \\ ,' reobtilin,'tl in a co ntrolled laboratory enviro nm<·nl us inl!{ l1GE l{ I soc spcc troradiometer.
Senso rs with a min imum sral ial reso lution o f 5 - 20 m are generally requ ired to .. ibtain Le vel II mform ation. SPOT 5 sensor sys tems provid e \0 " 10 m multispectral and 5 x 5 m panchro m atic data . RADA RSAT pro vides I I " Q m spatial resolut ion data for Le vel I and II land -cov er inventories even in cloud-sh rouded u opic al land scapcs. The Landsat 7 ET M" has II 15 " 15 m panchromatic ha nd, More detailed Leve l III cla sses may be inve ntoried usi ng a sens o r with a spatia l reso lut ion o f llpprox imatcly I - 5 m such as: IRS- l e D ran (5 . ~ x 5.1\ t11 da ta rcsumplcd to 5 x 5 Ill): la rge-sc ale aerial photo graph y; IKO NOS ( I x 1 m pan: 4 x 4 III mulnspcctral): Q uick Bird (0.01 x 0.6 1 m pan: 2.44 x 2.44 m multi spectra l): and O rbvtcw 3 (1 x I m pan: 4 x 4 III m ultis pectral], The sy ncrg istic use o f high spatial resol ution panchromat ic d ata (c.g., I x I m ), merge d w ith lower spa tial reso lution mul tispe ctra l data (e.g.. 4 x 4 Ill), provides an image-inte rp retation enviro nment that is s upe rior 10 using panc hnunatic dat a alene (G amba 1'1nl., 201H: Je nse n, l Oll5 ). Le vel IV cla sses an d ca dastral (propert y-li ne) info rmation is be st monitored using high spatial reso lutio n panchrom atic se nso r>. including Quick Hird ll.6 1 "n.b! m panchromatic d a ta. ste re oscop ic analog aer ial photog raph )" (~0.25 - I m)
456
(, lI A rn:l~
a nd stereosco pic dig ital frame camera image r)' [c.g.• Le ica \rcn Systc ms A irbo rne Dig ita l Scnsor ADS-IO ~ 5 x 5 c m j]. Urba n land-usc and land-cover cla sses in Lc\d s [ throu gh IV have temporal attribute requ ire ments ran ging from 1 -10 years (Table [J-I and Figure 13-21. A ll o fthe sensors mentioned ha ve tem poral resolutions of' < 55 da ys. so the te mpoTa l reso lution of the la nd-usc-hi nd-cover attribut es is satisfied by the CUTTent and pr opo sed senso r sys tems .
aeerc
Rem o te Se ns ing th e Urba n Landscape
a detac hed d welling composed of severa l ana ched (this is not true in the centra l bus iness d istrict ). COlllend'. a company producing finis hc d sle c1ty pically requireu 1o:!' large, line, lr bui lding (I~l ml ) that can h uu~e the varioussea processing acuviucs (function} , An ana lyst must be Cart howcvcr, because a huilJing 's usc may ch ange over nee T hus, a kno wkdgl' Il l' the seq uence- of-occ upance of Ni... ings in a region becomes important.
Single-Family versus Mu ltifamily Resid ential
As previously mcnuoncd. urban land scap es are noto riously comple x ( RiJ d. I QQ5: Small. 211UI: 2(04). While simple binary urban/non-urban information is valuable for assessing grow th trends t c .g.. Color Plate 13-2 ), it docs oot provid ... the kH~1 of land-use land-cover derail necessary 10 mak e wise decisions. Therefore, it i ~ use ful to provide add itiona l deta il aOOUI the e xtraction of the follow ing urban land -usc.' inform ation from remote sensor data :
rc..ide ntic ! hou sing
indu stria l
A ., illjl f,,-j.,mif r ft','i,I... ltt' i~ de tached fWI11 any olh..T!loIl-ing struc ture. In de ve loped co umric-s il usua lly has J ~ driveway. a sidew alk leading 10 the from door. a front yri a hack yard (linen fcnc c"lII. and a garage Ill' carport, It is llllIo ally .:::: 3 stories in heig ht. Several s ingle- fam ily homes' Richmond , C A , are in the process ofh.:ing framed in FipiR 13-7a. Completely laudccapcd single-family residences Boc a Rato n, Flo and San Diego. CA , arc show n in Fi~ 13-'tb,c. ,\ I (lhilC' homes (t rai lers l in d...· \ d oped countries m usua ll) much sma ller tha n orhcr singfc-farnily homes [a pp roxima tely 5 III single- wid e; 10 III doublc-w idct, tardy haw a ga rage (bu t may ha ve a carport) . and may or maytKt have a pal cd d ri\ ewa) or sidc walk I Fig ure 13-7dl.
transpo rtatio n infrast ruc tu re co mm unic atio ns and ut ilities ,
Residential l and Use
The home in almo st allcultures is the single mo st im portant JlI lssession a person acquires in a lifet ime. It shehers (he fam ily and usuall y repres ents the household's greatest ceo nom ic investment. Inventory ing (he locat ion, typ e, condition. and nu m ber of residences is on e o frh e most imponam tasks performed us ing remote se nsor data . D iscrim inating between Leve l II res ident ia l. c01l1ll1('rcia l. indus trial. and tran sp•.lrtatio ll la nd-uses re
In developing count ries. si ng le-fam ily res idences ma~ COl\lOist o f a bu ild ing, hut. tent. or lean-to dependin g upon cultu re. For example. lrad itio n:tl housing assoc iated wilb ! pa sto ral vill'lge in Kenya is show n in Hgu re 13-1'a. It may te permanent or temporary (seasol1al I. The st ruct ures may con, ta in individ ual or exte nded fatui lies. Somer uncs it is difncull III identify suc h structu res in developing countries because they :lI' C made oftbc sa me mate rials found in the surrounding comurysidc, resulting ill low object-to-back ground con, t ras! (Jensen et al., 20ll::!l.
w
In developed countries, l/IullifJ h':/i/ll/il.I' residences USUJ II~ have mor e than O1\e side walk. may ha ve large collective abo veground o r bc lowground park ing gilfages O( parking l(ltS, may he ~ 2 stor ies in hc ig ht. :md shaw front and bad yards tF igure 13·\).. ). The rl' may h..' a co mmun ity pool and; or lenn is COlllt, VII I,/c.\('.1 (two attac hed housing units) and tl' iph '.H',' (lhree allnclll'u ho u" ing unils ) ulOua lly have tI\<·oor Ihree walk.... ays and dr i\ cw 'I) S, resp...'Cti vely. Somelime~ I co mmon par k.i ng are a i ~ pw \' ided . It is olk n d illicult to det eml ine hl)W ma ny fami lies occ upy s ingle res id....ncl'S in del eloping cn untr ies. When there are mo r.: than thl'« allached hou sing un its. it is usua lly ca lled an apartme nl DI' condo mini um ( l'igurt.' 13-9I"1,c ). Such co mplexes olkrt I,,"'C UP) a n c\tens ive a rea oflant!. rise man) "ttlries ahtl\"e tbc gwund, an d in larg.. . e itlc" lila) be h igh-riw bu ild ings.
a.
"
ident ial land Use
457
•
t
Several sing lc-f:'nni ly reside nces IWlIlg framed in Richmond. CA et r I II ) lcouncsy l ' ri ~ C. B":l1l<'Il 1.
b. /\ single-family reside nce in Boc a 1(;11 <111, Pl., ..... ith one sidewal k. OI1e d n veway, lind II fCIKCd b~I.. YJrd ( k vd 1111).
UIl,,'I)' spaced s ing le- fa illily residenc e in San Diego, CA, with sidewal k, one driveway. a nd 'It;ca''l~ IJlly a s mall swimmmg [level II r I),
d. Si n\!k -fami ly traile rs {mobile homes ) in a tra iler pa rk l1t'ar \1yn lt' !'k 'lCh. Sl · Clew II I 12).
lilt
Fig ure 13-7
Examples of surgle-family residcmiat hl' lI,i ng CI"', d I I I I.
13
458
Remote sensi ng t he Urb an Landscape
:'oi airoh i. Kt·o) 1t
--
-. --.
-
'0Traditional
Kenyan villa ge ... ith indIvidual 0.1 " dl ings sum..und..:d b)"a communal IiU"l;lock corral . Figure 13-8
O. Meltiple-farmlv informal skirts ofNairobi, Ken ya.
(~ uallcn
Examples o f single- and multiple-ram iI)" residential housmg in
In developing countries, rural peo ple tl ock to the city to hopefully obtain an improved qu ality o f life only 10 lind few jobs and no available housi ng (Da Costa and Cjmra, 19(9).
This often resul ts in the crca uo n (If mtormol [squ atter ] developments whe re mu ltiple families Iiv!.' in buildi ngs consuucted with any materials that can he: found (Je nsen ct al., 2002 ). An inlonn a! sett lement o n the outski rts of Nairobi. Kenya . is shown in Figu re 13·Kb. It is usu ally possible 10 dete rmine if a bui ldi ng is a single or multiple-family resi de nce using ima gc ry with a spatial resolution fro m 1 -5 m. Sometimes it is necessaryto me rge multiple types of imagery such as Landsat Thematic Mapper and rad ar imager y to identify villages in tro pica l part s of the world ( Haack and Sloneckc r, 1( 1)4 ), O n numerou s occasion s visual, head s-up o n-screen image interpret atio n of ur ban struc ture ou tper form s co mputerass iste d d igital image proc ess ing (Jense n, 2( 115 ), Visua l image inte rprete rs arc able to ta ke into acc o unt the sire. situ' Ilion, and associat ion o f structures , These clements of image interp retation have been very d iflieu h to incorporate into an alytic al methods of d ig itul ima ge classification. Only no w are analyt ical neural net wor k-based image interpretation syste ms begi nn ing to include the fundamental elements o f vis ual image interp retatio n into the image-analysis process (Jensen et al., :!OOI : Qi u and Jensen. 200..t ). For examp le, Figu re 13- 10 dep icts the user interface associated with a neu ra l networ k-based d igital image processing system that
It
h,...,..ing on 11k' out-
dc\el "l"m~
t'tlUnll")- .
assists a n unagc interp reter to arrive at the co rrect lMd-
(OH'r or land- usc cla ssification for a parti cular pared ~ land, ln the pa st, th..- interpreter had to rely on complfi branching dich otomous keys to ass ist in the inlel'J'rdatlOll process . 1'0 w. the ima ge ana lyst ca n draw a polygon al'Ollnl a feat ure suc h as the on e she w n in Figure 13· IOa and then enter in the cbaractc rtsnc s observed in the polygon of iraeest using; a sim ple poin t-and-click menu such as the roc shown in Figure 1.'- lOh, The c baractensncs might indUlk the number of sidewalks. th... prese nce (If II driveway and:« garage, park ing lots , mu ltip le stories, and ge neral sizc oftle phenomena. The neu ra l netwo rk then processes this infor, marion and reports hnck tothe image analys t what it hd i ~vt\ i ~ the mo st appropriate lund- usc ur land -co ver code. Tht neura l netwo rk is trained using real-world empi rical example" and in cuecr it 1"/11'//,1', Thc neural netwo rk classifies. non system C' 1J1 also be used 10 photointcrprct other lam! uses. incl uding comme rcial. services. an d industri al (Jensen et al.. :!O(j I), Neura l network or e xpert ..ystc m-assisted intl.'!prcrction systems wi ll mosr likely be the means in the iimm by which most derail ed urhnn mfomuuion is e\entUJ.I~' extracted from digital remote sensor dl1ta (J en sen and 1I0llg· SOli,
lOW I.
Building and Cadastral (Propert y-Une) Infrastructure
In addition to fundamental nominal scale land-use and laMcover info rmatio n (i.c.• ide nt ifying whether an object is I
Res
4 59
Resident ial L and Use
L Condomi nium rCl'i,k nlia l h,>u~; ng in Colorado (Ie\ el 11131_lbe numm of dli\el'ay~. sidewa ll-s. ,111..1 no" r structures mdrcates how many housing units are present. I hc !",, -Ieft condo i~ a Iourplex. The 101' righ t b a S<.-\~"1l "le'\ . Ihe b onum1"0 condos an: lht"plc ~ .
b. Two- Sl" !) ' apa rtmen t com plcx in Cohrmbia. SC (le vel 1123 ). '" nh sidt"" al" and pa rkin g around the perimeter.
num~'TOUS
Figure 13-9
c. Twelve-story sludcnl -holl~i ng apartment com rlc\; at the Univcr.ity ofSouth Ca rolm a (Ic\cl 112.1 ),
Examples " I' rnuluple-family rusidcnual housing (b el li ::! ).
C II .-\I'TF.R
460
13
--
gem ct e Sensi ng t he Urban Landscape
:'rl l'ural I ma~l'
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a. User -interface.
-'
b. Data collection interface.
Figure 13-10 a ) The lIscr·; "I~·rrace of a Neural ~CI'" ork Image Interpretation System Ih313M;S(S an image a nalyst in the classiIicano n of diflkult urban landuse In this e xample. the analy~llIst'd \ Isual on-screen dlglli..mg to outline an unknow n objec t o f interest. b) The interpreter then used a point-and-cfick d ialog 1'>0.\ ' 0 i
..
a si ng le- tinn ily residence ( I f a commercial buildi ng). tran sportenon plann ers. utility co m panies. tax assessors. and otbcrs req uire more detai led info rmanon on huilding footpri nt pe rimet er. area. height. driv ewa ys, patios. fences, pool s. sturagc build ings. aud the distribution <11' landscaping every on e 10 fiv e years (Tab le l.~ -l ) ,
ca n he identified b)' a surveyor in the field and the information overla id onto the enhophotograph or planimetric map database to represent the legal cadastral ( pro~ny ) map. Many munic ipalities ill the U.S. usc h igh spatial resolution ima ger)' as the sou rce for some of the cad a stral information and as a n image hackd rup upo n which surveyed cadamal an d tax in fo rmation arc pcrtrnyed (Cowell ami Cra ig. 2 0lM~
It is possible 10 identify the presenc e o f indiv idual build ings using monos copi c images and several clements o f image interpretat ion such as sil l.'. shape and context (Tullis and Je nsen. 2003 ; Je nse n cr ;11,. 200S ). I Iowcvcr. dera iled building foo tprints lind propert y lines arc hes t obtained using stereoscopic (ove rlap ping: I panc hromatic aerial pho togra phy or ot her remote sensor data w ith a spatial reso lution of ~ 0.2 5 0.5 m t e.g.. Ehlers et a l.. 2tlll3 ). Fo r ...s ample. panchrom atic stereosc opic aeria l pho tograp hy w ith 0.25 x 0.25 m ( I OJ spatial reso lutio n was used to extract tile e xact d imcnsions o f Indi vid ual houses and outbuildings. trees . pool s. dri veways, r... nccs. and contours for the single- fa mily residential area in Figure l j- Lla.b . In many instan ce s. the fen ce lines arc the ca das tral property line-soIf the fe nc... lines an: not \isiblc or ar e nor truly o n the property tine. the- property lines
Detaile d buildi ng he ight and volume data can also be ex tracted fro m high s patial re solution (O.::!5 - 0.5 m ) stereoscop ic imagery (C hapte r 6 ). For exam ple. consi de r the wirefr ame thr.....-dime nsicnu l ou t line of the United Stutes Capitol shown in Fig ure 13·1 Ie. The pe rime te r. area , volu mc. crd squ are foota ge of l h i ~ hu ildin g are now available. Such det ailed building informa tion ma y al10\\ the exact type of roof to be idc nuficd (c.g., riJ ge. mansard. hip ped, lean-to. Ilal. ctc.). which rna)' he used to infer the date o f hllilding co nsrrucuon I Lo and Yeung. 20(2). Bu ilding informanoe ca n also be o btain ed from high spatial resolutio n satellite imagery. For e xample. Fraser et a t. (200 2) fo und thar buildings co uld be ex tracted fro m -aereo IKOf'OS I x I m imag-
t
er
o
,
•
nlial Lan d Use
•
461
.-
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temcel panchromatic I :2 .400-~le aerial phot ography I'LmlTll<.'1ril: (."(.y) cad astral lnforrnancn ':Atra l:t..-..I from the "~",,,;ic aerial photngTaphy. includinl,! 2-ft eon loIH'I. I"-llldfoctpnms, fences. r.:uining w alt,....nd larg.: trees (1enlo<:n [o""ClI.19991.
c . Wire-frame mrormanon "fthe U.S. Capit ..,1 ':Alracto;o.! from lo~c scale \ " n ;cOI I a"r;0I1 r ""I"I;1'3l"h). mcludmg precise b uilding footprim, height. area. peruneter..lIld volume. The 1"'0 ph,,'lngraphs mOl) be \ ic"' ..-.J 101\-'fl.,\)!i,wpi''0I11) (C(lurk'S>" UI S)~I..-ms. U C. San Diego. C 1\. and f\larclIni Integ rated Sy~l ...ms. Inc.: (.~ S()(·!:. r Sell.
Extraction of cadastral inform1ltiun fro m stereoscopic vertical m-nal photography using a ) trad itional, a nd b.c ) soft-copy phn·
togrammctric t ...r hniqucs 11'1...,.-<:, ref...r 10 ( ·hapl...r (,), Such infurmali"n i, \ ilal III tlie Jccurate inventory vf residential, com· mcrciul. JnJ industrialIaudusc. Itcan be acquired us ing traditional sure c) illg or ph"\ "grmmn"tric techniques.
with an .l.y accuracy o f 0 .3 - 0 .6 m and he ig ht a ccuracy
Pop ul a rlon ":\ tim:uin n
8S - 0.9 m. oecooomic Characteristics Derived from Sing le· Multifamily Residential-Housing Information
led socioeconomic aunbutes ma y be e xtract ed dir ectly remote sensor data or via surrogate inforrnuuon ic ed from tile imagery. Two of the most important are lation es timation and quo li!..· f!(It(e ind ica to rs. derived til) from sing le- and muluple- family rcside nt tal- housstock information .
Know ing how many people Ii, e with in a specific geo gra phic area or ad ministranve unit te.g.. cit y. cou nty, state. co untry ] is \ 'CI") powe rful mfomunion (Je nsen ... t al.. 2002 ). In fact. some hav e sugges ted tha i the g lobal e ff ec ts o f inc reased populauon density and ecosys tem land-cover convers ion may be muc h r no rc significant than those aris ing fro m cl ima te change (S kolc , 19( 4 ). Population estimation can be pe rform ed at the loc al. regional. and na tionalleve l based on : coun ts of individ ual dwe lling units (req uire s 0.25 - 5 m nom ina l sp anal resolution (Je nsen e l 31., 20 lJ5):
t3
462
meas urement of urbanizedland areas (often rcfc rrc-d to as settlement siTe) {e.g .. Tatem et al., :!OO-ll; esumau..' s deri ved fro m land- use/land-cover classification (1.0, 1995; Sulton et al.. 199 7; Sunon, ::00 3 1. Remote sensing tec hniques may provide population ..-sumales tha t approac h the acc uracy oftradiriona t c-cnsus meth ods if su fficient ly acc urate in .•ifu (1;113 arc available til calibrate th... rem ote sensing moo d . Un fortuu arcly, the grounJ.ha-.cu po pulat ion estimarionc arc often ..voefully inac curate. In many instances. the remore se ns ing me thods may b..· MIIK'riM 10 the g roun d-based met hod s.
or
Th e mos t acc urate remote sen sin g method estimating the pop ulation of a local area is til count illdi l'idlm l d lld/il l): l/11il.\ based on the foll owing assu mp tion s II indgrcn. 191\5; Ln. 199 5: 11,, 11., 19KX; Haack et al., 199 7 ): T he image ry mu st have sufficient spnua! reso lut ion III allow idcuuficauon ind ividual structures even through sparse tree cover and 10 determine whe ther the struct ures an: rcsidcnrial. commercial, o r industrial.
.,1'
Some csumcrc o f the average number of persons pe r d"elling unit must he available. Some e-umate of the number of homeless. seasonal. and migratory workers is requ ired.
It i" assumed all dw elling units arc occupied. and on l~ /I fami lies live in each unu tca librutcd us ing ill situ
Remote Sensing th e Urban Landscape
is toe time-consum ing a nd co sil y (Su lton ct al., 1997 han- suggested that this method req uires so much jll til calibrate the remote sensor da ta that it can become ncnally impractical. Therefore. othe r methods hal( developed. T heil' is a relations hip be tween the urba nized built-t4' (scnlcmem site) e xtracted from 3 remo tely sensed and senlcment population (Olorun fcnn, 19X-'I: r
a
X
/,/>
where I" is the radiu s o f the pop ulmc d area circle. e s empi rica lly der ived co nstant of preporuonalny, P is thc~ ul.nion. and h is an empirically derived exponent. Estiw o f the se parameters arc Fairly cons istent ut regional _ bUI the es tim ate of th e 1I pa ra mete r varies between re~Ofl> Sutton \'1 ul. (1t,l'J7) used Defen se 1I 1d l.'Ilruiogicai Sale Pro gram Operational Linc scan S)'stC11l (DMSP-OLS) \ near-infra red nigh tt ime 1 x 1 km imagery In inventory cxmu for the en ure Unite d Stat ....s ( Figure 13-12). Whell1k d:lt;l lIere uggrcgatcd to the state o r county level. analysis (If the- ct ustcrs o f the saturated pi"el s predic:ed Polulanon wnh an ,;' '"' 0.81 once aga in. Sutton (2003) nightumc I>"- I$ P-OLS imagery to measure per capiuill usc consumption as an aggregate index for Ihe spatiall~ tiguous urban areas o f the conterminous Unitcd Staes populauon ol'2:: 50,000. Tatum ct al. (2lX)41delineated ~ mcms in Kenya using Landsat T \1 and J ERS- \ symbdi. aperture radar (S A RI data wj th the glial of p~ medium-scale population ma ps for improved public planning.
informauon j.
This is usuall y perf orm ed CICI) the In seven years and requires high spat ial resolution rCI11(lh:~ )Y sl'I1SCl! d,lta (0.25 5 m). For ex am ple. ind ivid ual J wdl iug units in lnnc, SC were c\ tr:lcll·d Irom 2.5 x 2.5 m airc ra tl l11 uhispl'c tnll data . ( 'o rrdatillll of the remote sCllsing----l.l<:rlvcll dwd lillg IInil d:lta with 13ure:au "fthe: Census dwel ling unit d,lta for the 31 census h loc k arC:l ) iclded an R.' - l Ul l. "hil'h accou nted l(lr XI JlC"1"l-'\:'nt Of lhc ~;I rianee_ T llese lin din g, suggest Ilwl the ne l\ h ig h spat ial reso lution pam:h rul11;l li..: '>Clblll"S may pw \- ido: :l good sllurec Ill' inro ml:ll ion for moni toring the housing stock of a Ctlmmun ll~ \lll a w utine l>a,i,. f h is " ill en ahk InClll go\ernmcnts to an tIcipate and plan for s..:hooh and othcr :>cr\ ices" ith data that h:b a much more frequl.'nl h.'mporal re solut ion tha n lhe decennial census. ThIS da la will alSl,' be u f \ alue for rCOl I es!.atc. marketing.. and otht'r bU:>Lne:>s applications . Unfnrtun;Jtc!y, thl' d \\ el ling -ull1t approach is not suitahll.' for a reglona lma tional Cl:nsus of J'I..pu latillll lx'Cause il
Re s id e
Fig'
Q.
A. se
'q'" E br aj
..\ lIotlll'r widely ado pted populanon cs tuuanon tC'C hni'lllC& based on the use o f the Level I - [II land -use inlilrmaTIi¥l " his app roach l1SS U111CS thai land usc ill an urban am! ~ closely cor re late d with popu lation densit y, Re,c~rclIrn e~ t ;;l h l ish nn l.' mr iti cal v31ue tOT the po pulation den~ ity fll ":
qqs
1lIe.
a
,,
,
463
lSidential la nd Us e
JUre 13-12 Defense Met.,:o rolugieal Satellite Program Opcr"lional Lincscan System (O\tSP-OlS) , i~ihle l>Cilf_mff3rC'd nigh ttime 1 x I km imagery of the con terminous Unncd Stat..,;. w hen the data .... ere aggregated to the ~I.ale or county jcvet , ~['lI tial analysis of the c1 11~ter,. of the ",-luraleJ pixc b, predicted pu pu !dliOll with an R? c O_I' I (Sulton ct al.. IQQ7; e"Une~) Am.TIc:m Society for PhOlogTilmmctry & Remote
IJ l i l~.O r. l .i re
~~~mg ~.
Im lica lo n
kquate incom e. dece nt hous ing. good edu cauon, health vices. and a goo d physical cnv ironment (c.g., no hazards refuse) are important ind icat ors lit" . . lll:ial well-be ing and olity uf !lfi.' (Lo and Faber, IW S: Lo and Yeung 2002 ), :aJualing the quality Ill' life of a population o n a con tinuing 5i, is imponar nbe cause il he lps planners and governmen t enctes involv ed with the delivery Ill' huma n services to be areof pmhk-m are as .
OlSt quality-of-f Ic studies have been based (Ill the analysis socioeconomic informtnion derived fro m ill situ cnumcrIn. Rem ote ly sensed images have rarely been use d in .ial studies, Only recently huvc facto r unalysis studies rencntc d how qua lity lit' lite indicators (such as ho use ue. median family inco me, ave rage numbe r of rooms. nagc relit. and education] CUll be estimated by C-\lrucli ng urban attributes fou nd in Table 13-X from relatively high nal resolut ion t ll.25 - .10 m ] image ry (L indgren. It,lX5; lz. J9lo!8 : Met)' and Bcr liu. 1991 ; Hauck et al.• 1991; l,o IFaber. 1995; 0.1 Costa and ("inlra. I"}lll); Lo and Yeung. 12: Jen sen et al.. 2005 1. Note rhar the au ntuues arc mged by silt' (bui lding and lot) and situation. The site y he situated in positive and ncgmn e surro und ings. remote sensing- d..-r i\ cd ullTi butcs mu sl be corr c lat..-d h ill sit u censu s oMen:ll illns to compute thc q uali ty-o f..
:!<
life indicators Lo and Faller (I t,lI}X I suggesl thai in many cities gree n vegetation is \1.'1)' prec ious and cos ily. and thai un ly the wealthy can a fford to include grass and trees in the ir living environment. T hey found that greenness mtorma non de rived from Tl\1 da ta was highly co rrelated w ith quality o f lifc . Qualit y-o f-fife indicators arc usua lly co llec ted every 5 I (J years_
EnvlrunmcmalIu flucnc cs i\ ~ ~u d a t l'd w illi ZOll l n J: Lon ing i, a tuolurbuu plunncrs usc 10 control physical charucrerisrics o f dcveloping landsca pes by imposing restriction o n vnriahlcs such as ma ximum huilding height and dens ity, extent lit" impcrv il\lIs surface and ope n Sp
C HA Pn :1{
464
Table 13-8 .
Urban/S uburban anrib urcs that may be c~ tracl"d from remote ~n",'r data and USloJ IIl1lS~SS huusing 4L!il l i ly and.or "lual il} of life.
Fac tor
Sil"
A ttributes
Buildinll single Of multiple-family sin ' ( m~ height (m l age [derived hy convergence (If evidence ) ~aragc [attached. detached! Lot s ill: { m~ l
sensed data. First . the St.juilrc footage (or m:) ofindivi buildings is determ ined trom high sp;l1ia l reso lution imatery, Loca l ground- reference in fo rma non abou t cnc'1!) CISsu mpuon is then o bta ined for a representa tive sample hom es in the are a. Regress ion rela tio nsh ips are then denll'l III predi ct the antici pated en"rgy co ns ump tio n for the l"t]!' It is also possible 10 pre d ict ho w m uch solar photo\ olllt enc rgy poten tial a geograp hic reg ion ha s hy modeling . ind i\ idual roofi t,p square footage a nd or ientation It knott n phutovoltaic generatio n co nstrain ts. Both applicJ. nons require high spalial resolu tion imagery (0,:;:5 - I (Curra n and Hobson. It,lX 7; OOL :!()f15 ). Regional . national energy co ns ump tio n may also be predicted ~ D~l SP image l')- tc .g.. 1".1\ idge et al., IIN 7: Sulton eI
that ty pe sim I foro:
oftl 10 ')
rcrr see cor me
tiOI
1'0147 ).
backy ard 1m: )
street frllnWge lml drive.... ay (pa ved . unpa ved)
fenced pool tmgroend. aboveground ) patio. deck ou tbui ld mgs (s heds) dcn sll y ofbuild in£s per l()[ percentlandscaped health o f scgelation (e.g.. ;";DVI greenness ] fron ts pal ed ( II" unpaved road
abandoned autos refuse ..\ d ja{e m:~ 10 Co n lln u " i l ~ Am" lIitks
schools , h" Plllllg ch urches IlI'spi"" s
tire station Il]X"1l '1';1':1:, parks.\! lllf cour ses marsh . \ I1 J :l n m· ~ I" ~ t1 i"Ul n'\ or lIal ard \
heavy strcctrra fl'ic railroad or switc hynrd
airports and -or
Com
Rem ote Sensing th e Urban Landscape
a.
Iroru yard 1m:)
Situa tio n
13
ll i~h lpa lh
Numcrou -,stud ie-s have doc um ented hllw high vpaual ~ tion ( I - 5 r n} pred aw n therm al infra red image ry (I( - IJ !1A can be used to incemory the fI.' lal i\ equality ofhuusing imtltauon if Ljthc rooftop materia l ic known te .g.. asphalt \Cl'SllS wood ~hin!:des). 2 ) nil moisture is pre-em on the roof. and] the orient ation and slope o f the roof arc known (Eliassoo. ItN:! ). If energy con servation or the generation of solar ~ 10\ onaic pow cr we re important in cou nmcs. these \aria~ wo uld prob ably be collected every o n,' 10 Ii \ e years. Ac tive and p
Comme rcia l and Services Land Use
freew ay l ocate d 011 n Iloodplain sc wage-l rr nlm,·nl plant mdustrial .u cu
power plant or ' Ubsl;}ll,' n ove rhead uulity lin,." steep lelTain
Energy Demand and Conservation
Loca l uThan suh urhan energy tk ma nd (s ometi mes referred 10 as h,·at- I'lild J" ns it~) rnay hi: csti rnJt,-d using. rcm lltd ~
People eng age in commerce (husinc ....) til provide food, c lolh ing . and ..hd ter lilr thenheh es ;md thei r extended families . Many \-Iorl.; in the sl:T\in' indu sl';"s p rovidi ng ,'duca· linn . m,-dil'a t sani tation. tir l' a nd po lice protec tion, etc . ttl imp ro\-c Ihe quality o f life li' r Ihe en llre co m munity _ l nt~ estmg.ly. man y \lf lhesc ac ti\-iI16 arc \is ihle in tho: land:;ca ~_ C('lIlm e rcial and s\:rvice ael i\ ities o ften hal e a un ique nJ· rura' .{;gnamn· dd i nl-d as Ih..: assemhlage o f s[lC'Cili c mat";" a ls an d strur.: tu res Ihal r.:harnc lcriL": c.:nain :111.1\ iti;:s in a part icul.lr cult ure. Each cu lture has cu mme rce and ser..iccs
er
cc
'"" f,
rc
•p o
c s
465
Commerc ial and Se rv ice s Land Use
ilt arc unique to tha t culture. For example. there arc many ~pes of commerce found in Asia tic urban enviro nme nts that SIm ply arc not found in Western urban landscapes. Therefon:. an interpreter must understand we ll the cu ltural milieu i the count')' o f interest before he or she attempts 10 iO\ enU) and map the commerce and se rvice activitie s using smote se nso r data. In fact . if an interprete r has not act ua lly een the phenomena on the grou nd and docs not understand pletely the cult ural signi ficance and purpose o f the comeercc or acti vuy. then it is un likdy that 3 co rrect imc rprcran wi ll be ma de [Jen sen et 31.. 2no2 ). The author extended the L"SGS l.A.md- L·selLt.md-Co \'('rCtassfication System in Tabl es 13-110 J.l-h 10 include Le\'e1 IV llld sometim es Level V clas ses. Thi s extension is prima ri ly .. U. S. an d wcsrcm European land",apo.'S but ma y be generally applicable to ot her dev eloped nations. It represents a rommon- ,cnse hieran:hi eal system thai can be aggregated leek to Levels I and II. It is nOl complete in con tent ; rather, ~ reflects an attempt to categori ze the land use that accounts b approximately Q; percent of the urban land ucc cncou nrreo.1 in mo st developed cities. 11 uses common terminolog y whenev e r po ssible. A detail ed dcflninon of eac h class is not pr(l\'idcd he re. However. it is instructive to provide numc r!XIS exam pl es of the va rious ty pes of land UM: and C0l11111eni 00 unique characteri st ics that al low on e Iype of comme rce or service 10 he di stinguished from others.
The Central Business District
The central business district (CB Il I of man y ciuec is the m(l~t distinctive urban landscape With ill' high-rise buildings lIld the highes t densi ty of land usc . Muny CllDs have changed co nsiderab ly in recent yea rs. particularly in the Uni ted SIMes. Urban geographers usc the term deindll'\lrializanon IU de scribe the loss o f manufacturing industries in Cities today. an d the rise of ,,·/"Ii(l/)' and qUall'rnar)' commercial activi ties. notably financial services. insurance. and real esta te. There arc also many other profe ssional services tha t characterize the modem cures and the phe nomenon of slIh~rh,miziJtirlll . Ix",. ruow n Scaute. \VA , is an excellent exam~c ora central business dis tric t ( F i~ ure 13,13). Numerous high-rise office buildings hou se the financial se rvic es. insurance. and real estate lion s . I tow ever. some (If the towers also remain singtc- and multiple-Family residences.
The C HD" of so me cities in the Un ited States have bee n I) transfo rmed into po vert y urcas. ~) genuilicd . meaning that onlyolder people live in thl'm and that ,<'ery ti:w yo ung la mlliesare pres ent. and o r 3) r~-Cll n struClcd \00 ith ne\Oo bui ldings
Figu re 13 - 13 .-\ fl
Image {colln.,s)'
1' (l SI II \ '1.' Systl.'ms.
Inc_I.
III attrac t p rofe ssional middle-class people and thei r small
famil ies (usua lly ~ 2 child ren) to return and stay. These and other condi tions mak e it difficult In identify the exact land use ora particular parcel of land in tile central busi ness di strie r. lnstm obse rvation is usua lly required in add ition to the analy sis of remotely sensed data,
Commercial Land Use
.<\ utllmn th l' and "uIII The developed world and es pecially the Unite d States is enamored w ith the nutornobrle an d other loons of personal trunspon auon. incl ud ing trucks, sport uti lity vehic les . rcc rcauon \ chides. and boa ts . Much of our d isposable income is spent acq ulTing and mainta ining lht....c veh icle s. Th ~·rcloH: . the- urba n land scape is lith:rcd w ith dca le r-; hips tll se ll them. sen-icc stati "ns til li ll thcm up wi th petroleum di sti llate
466
C H:\ pn ;R
3. Automobile dealership in Columbia. SC (level 12 11 1). Can for sa le are arranged systrmallcally for t>uYo:'f inspeclion and .:'3'< of exit and return .
13
Remote Sensing the Ur ban L andscape
b. T)l" <:31a utomotive So.'I"\IC'e Mall.m '" j,h multiple islands iOf Ihpcusmg gaso hne Of I.h,,-s.:l f\ll:l aOO a ma in bu ild ing coru.ir.u~ Ii .-.cr\ icc bays or mirn- rnarkct 11.:-, ...1I :!l l:n Jhe c ircular 'op$ lillrf underground petroleum slur-J.~'" u.nls arc \ iSlbk in this c:umrle.
Figure 13 · 14 Examples of comm.. reral aUlolT1l .ol lc establishments 1k\ o:l 12 11).
products. and bus incs~:; that repai r the m. Finally, their rema ins can often he see n in automobile junkyards. New an d used ca r. truck, and boat deale rships arc rclmiv cly easy to idcnlil)"due to the myriad of'vehicles Of bo ats pa rked systema tica lly in large parking lots, thc presence of large show rooms• and att ached service ce nters ( Fig ure IJ· l·b ). Isolate d se rvice and repair businesses arc mor e ditfl cu tr 10 identify but usually have sma ller p.trking lot s with many can; prese nt in the lot in various slates o f rep air. Gas service stations o ften have a se parat e island str ucture with ils own cano py \\ here the fuel is d ispe nsed . a detached buildi ng that is usually a mini- market. and occasionally anoth er bui lding when: automo biles arc w ashed. Gas statio ns arc 0 111;11 IIK·alel! (HI corner lots (Figure 13-I-Ib) . Numero us cars are o ften located around the perip hery of the service- stuuons.
F
bu ild ing tc.g.. sporti ng goo ds. garden, cl othing. market. toys ). The building usuall y is one of the large-.t (m~) in the region ( Figure 13- 15 location
Fi nan ce li n d ('o nst r uc ti on Junk ynrd s have ;1 largl' num be r o f ve hicles arranged in II haphaz ard fashion. runny m i..sing hoo ds and trun ks. Als o. grass may be grow ing bet ween the cars. ma king it stra ightforward 10 drsun guis h it fro m a dealership.
Department stores t e.g .• \ValMa rt, K-Man . Scars-Roebuck ) co ntain many type s of prod uc ts locancd .... ithin a single
Com
T her e art: ofte n a tremendo us numbe r o f banks. brokerage firm s, insurance agencies, con struction fi rms. and real esne offices in the ce ntra l busincss d istrict or a majo r cit} te.g., re fer to the image o f' Scaulc. \VA in Figu re 13-13\. Parking may be \ iviblc abovegro und. in multiple-story aboveground parking struct ures. or unde rg rou nd . For exam ple. consider the Affi nity Office Building loc ated in dcwrucwn Columba, SC (F igure IJ-l t>
me
Commercial and services Land Use
467
Figure 13-15 Example of dcpanrucm ~ll)fe "nd mall commercia! [and us.: in sorne developed c<"mlnc'S. An isol.ucd Toy....R·Us. Inc.• defl'l rtmclll store Iat IS Independenl ufl tlc mall t lcvt'l [113 11. 1l1c m,,11 commercial cl>mpk" Ct<:\c1 12 [32) i~ anchored 11)' three maJur chains: Scars-Roebuck, Inc. tb). BcI~. Inc. Cc l. and Dillal,l,. lnc . (d l. The centra ! walkway of the mall is encl"'e...l "llh occasional s kylights. The m;.11 is completely ""rro untlc>J II) p;lrk lll~. some Ill' whi.:h I" aSl'h.lh (\laTin and sonic concrete (light). I hc roof uf Whi l.:" department store Ce ) is asphalt. barely d i'li lL~ lI j , hahk from the {'nrking 1m. ~ " I e' the rmnu-ruus airconditioning unils on each huild ing.
bcuscs banking, brokerage fi rms. insura nce agencies , an d an airline ticket o tfice. Parking for chis bu ildi ng is pnmarrly aboveground. It is impossible 10 idc mify (he specific act i\ ities laking place .....ithin this office building. Therefore . it is often necessary 10 sim ply label the hui Ming or parce l a:. being ('fml/>/t'I"!::i
or
desir es 10 ma p the' e xact perim eter of the bu ild ing in its proper planimetric: (.l.y) posinon, O ne ca nno t simply draw a polygon around thc hlp o f the hllilding an d ass ume thlll il is in us proper planimetric position. O ne might thin k tha I relief displuccr ncru would be absent from high spa tial resolut ion
imagery obtained fro m sensors placed in o rbit. Unfo nuna tel y. lhls IS nOI Ihl' case. 'IS de monstrated in the GeoE)'e IKU :-.J OS I x I 111 imag e of downtown Sea u le. \VA . where bui ld ing displaccmcrn is srill apparent (Figure I .~ -I J}.
Isola ted. detached banking faciluics typically have a d rivethro ugh po rtico struct ure w here fina nc ial transac tio ns lake place (Figurl' D·]hh). O ne pa rking a rea is usua lly a"..o cratcd v\ith v.a lk-in ban kin g. \\ hilc the other pomon o f the parking area ~o:" ices the dri ve-tbmugh traffic. One must be care fu l not 10 con fuse the d rive-through hank bui lding v. ith a gas station that also has a drive- thro ugh portico. t'onsuuc uon companies ot len ha H~ heav y equipme nt (buc khoes, dump truc ks, ct c. jlocmed on the prope rty. as well as stacks or piles o f raw materials (c.g .• lumber, cement. palC!lI;"S ofbricks).
46B
( ' I L\ I'TE R
a l"llmm"'1 ~ ial finand al ".,0 leo. . ind udin!! banking (I....d 12141). insurance [level 12142 1. and real esta te transacnons [le vel 1214} 1. take plac... in th... A ml1l l~' Ottlcc nu i1dil1~ in dow ntown Columbia. Sc. Building relief displa cement in l h i ~ original 1:b.lMlO-sca k vertical se n..1pho!\lgrd phy prv it.l..-s lktaiktl info rmation abcet rhe Iacadc
13
Remote Sensing th e Urban Landscape
b. An ist>ldkd ,;mall b
(sid c ) of th ... f,IlI1 d ing and :Ji,ts in huild ing im age iml.TJll\"lation.
Fig ure 13- 16 F'Iamplcs of commercial financmt ....-rvices (level 121';1
Food a nd Dru g The urban landscape is replete \\ ith many food and d rug busi ness es tabl ishmen ts . Chninsrorc markets and drugst ores occupy larg e hUlldi ngs " ilh ex tensive parking facrlities. T hey may be isolated . but arc oft en [uuud attac hed . Fur example. consider the unachcd drugstore (1) and supc rma rkct (2 ) shown in Figu re 1.\- 171\. T he IiIOU and drug esta blishmcnts share a large common parking lot. The cxact land- usc code of suc h buildings is ofte n difficult to dete rmine wit hout ill ",jill inspection beca use the large extended building and p'lrk illg fuciluics ma y ap pear sim ilar to other commercial
enterprises. Fast-food rcstuurams geucrully occupy n-lariv cty small, sing jc-stcry huil din gs. T hey arc located on both majo r an d minor roads. ha ve modest hut adequa te pa rking fac iliti es. a nd often exhibit a " ing lc automobile d rivc-th rough wi ndow lane thai encircles the t>u ilding ( Figure 1]·1 7t>c). T his is important bec ause drive-t hrough hanks typ ically ha vc mu ltiple drive -th rough lanes. There arc usua lly numerous entrance s and exits tll the 101 . The lot is usua lly modestly land scaped. Som et im..-s there arc elaborate playgrounds with gymnasium equipmcru present in front oflhl.' rl.'stau r.mt s.
More- ex pensiv e. upscale restaurants arc larger in si/e (m-], have wett-manic ur..'d lawn and tree landscaping. occupy a much larger lor. and have large r park ing areas than fast-food res taurants . Both fas t-food and upscale restaurants have a large number of vents 1111 t heir rootlop s. Sometimes the smo ke discharged from the vents disculors the rooftops .
Fun eral al ul
(' l'nh'h' l"~
Hav ing traveled the equivalent of 100 rimes aro und the Earth in our aumnmbilcs during a lifetime {the Earth is llnl} ~5.0 0n miles in circumfcrcncc t ;Ind c.ucn at far too muny fast -food restaurant s, American and Western Europeans linally reside ill a cemetery " r mausoleum . Interestingl)', cemeteries ofte n con found image inte rpreters. yet they have unique charactcnsncs ( Figu re 13- IXI. In developed nations they gcncmlly ucrupy all expensive and ex tens ive tract of land. often udjaccmto churches. The landscap ing is usually meticulous The ro ad nl'IWl1rk is intrica te. w ith man y narrow roads. O ften. the road-, Iolluw the contour of the land . But must important. there arc hu ndr c-ds ofsystematically spaced sma ll wh ite dots o n the landscape. There is otlcn a shed on the propert y w ith heav y equipment tbackhoc l and \JUllS locatcd in Ihl;' shl,.-d tlr 1>11 Ihc g ruuml out of sight from tbe
Comn
".12 f,
469
ommerc lal and Serv ice s l and Use
LExample of d drugst"TC (r.:~'d I:!I SI ) (lfI the kfl (11au...:hed 10 a supermarket (lew l l~l S2 1
on the r ight (2). The smalloue -story hlll!
fOlomat (3l.
r", j ,
a 01ll."-h' HIT
h. A fact-food restaura nt (le \ e1 12 153 ). r-;Ille the ample p
Ftgure 13 -17 b,am pll-'; of I.""" ,moJ I levc11215)
oJru~
commercial businesses
t . A,nuther fast-food n..~laur;ml (k\ d 12 1:53) Again nUle Ihe dri\ cthrough window lane loaded", Ilh cars.
pohlic. A mortua ry or funeral home may he located on the property, II is o ften a sing le large- t'ouilding with subvra nrial parking.
People thro ughout the .... orld )\lVC 10 go (In ov ernight and extended vacau ons . Th is has resulted in a p lethora o f small motels that ca ter to the motori st and large r hotel s that arc used lor roth husin~~s and pleasure. One Ilfthl' major d ill er -
cnccs be twee n a mo re l and a hotel is size, Morel s lend III he smaller and have fewe r stories (Fig un: 13-ll)a) . Hote ls arc etten impnsing struct ures risi ng 2: 4 sto ries (Figure 13- 1%). Both motels and hotels usuall y ha ve large par king areas and s.... imrning pl lol(s). Mo te l pnrkin g is etten d irectly in front o r the ren tal un it, whe reas hote ls oft en have large und erg round parking areas Ihal at c d iOicll lt to detect. Hotels often ha..... tennis courus. whereas molds us ua lly do nul. large hote ls tend to h.: located nea r major thoroughfares. airports. and limned-acecss highways while motels may he loc ated j ust
13
470
Remote Sensing th e Urban Landscape
Con
,Ix> seal
Th. "I ind
P" Th ,~
..
,n II
T Ftgu re 13-1 6 A purtiun .,1' Ill.: Elmwood Cern ..,~'I)' in Columt>ia. SC (1ev ,;1 111(1). ori~in ally recorded 011 1:10.000-sea 1C' aerial ph,,'u~'T;Iphy_ Th.. small white dots are mdividual headstones. The larger white seructures ... nh shado.. s are mausoleums. llIc t>u i ldil1~ at the right is a large ma usoleum .
a. The 1!eM! of Cawlina :\Iv l..:! {le,,:1 121721. Many ofthe cars arc par ked d il\'clly In fnl ll1 o f
h. I cm porury h"u~i ng .il lh.. Columbia Plaza 111'10:1 (J,,: \c1 1117l l. Nut.. the high-rise hottl complex. the 1
the patron's ruvms.
for [oaili ng and unloading convennon exhibus. TIle po,,[ is ins ide til.: building. Fig u re 13-19 Commercia! motel ami hold temporary
hou~ ing
(Ic\ cl 12171.
a
"a
s a
•
~ me rc ia l
a nd Servic es land Use
47 1
anyw lll..rc. Hotel s usually have me re luxur iant land-
fairw ays, numerous brigh t sa nd traps. and well-manicu red gree ns ( Figure 13·23).
arc al so sp,..ciahzed campgrounds that cate r spccifi:lilyto the motorist . Th..-se han: unique attrib ute s. incl ud ing lIdi,'idua l d riveways wher e the car is parked and CIllJcrete peds where a lent o r recreat ional vehicle may be placed. e is oft en a centrally loca ted sw immi ng pool and oth er ecreetionat am enities. Th e campgrou nd is o ften q uite large t!Id loca ted nca r a major high .... ay. Campgrounds arc usual ly ...ell-manicured.
Sw immin g pools arc easy to iden til).' if on e re mem bers that there is usually a dark er deep end to the pool and that many pools have pa ra llel swim min g. lane lines o n the bo ttom o f the pool. They co me in a trem endou s variety of shapes an d sin'S hut a lmost alwa ys hav e a signi ficant amount of dec k surroun d ing the m. T.... 0 e xamples are shown in Fig ure 13-24.
I
110 0101.'
lind Gard en
This type orbusiness (e.g.• Lowes. 110mc, n l.'pot ) usua lly ba-, asinglc large building. atta ched greenhouse(s). and rows o f shrubbery outside or adj acent 10 the building. A lso visi ble art palette s of fertilizer and other mat eri als, yard machinery loch as 1.1'" n tractors and tra iler s sitt ing outside the b uild ing. md a large pa rking 101. It is usuall y situated in the city on a major highway or in suburbia near residential ho usi ng. Recreauc n The post -w w lt ba by boome rs arc mat uring rap id l)' and so the ir chi ldren and grandc hi ldre n. Msn y of the adults are out of shape. ha ve substant ia l disposab le ince rne. and .... ill obtain mo re and mo re leisure time, es pecially \l hen thl.'Y retire. Th c-refore, it is nOI surprisi ng that a great dea l oft ime . money. a nd landscape is devor ..rd to public and co mmercial recreation facilities. especially golf. Also. num erou s amu se ment parks are now rounne ly ava ilable that co nta in a variety ofrecreational facilities. These arc rel at ively ea sy to ide ntify on rem otely sensed data d ue to their un ique shapes and curvilincnr patte rns. For ex am ple , co nside r the roller-coaster. go-cart track and water-s lide faciliri..,s located in Myrtle Beach. SC , in Figure 13-20 . In.'
It is a re latively straig htfo rwa rd ta sk to idennty basebal l dia munds. foo tba ll or socc er fields. running tracks. and tennis courts usin g remo tely sensed data. because they arc la id Oil! according til st rict spec ifications. Examp les of these acuvines and the d ime nsion s of the d iamond s, fields. and co urts are sum marized in Figu res 13·2 1 a nd 13-22. Perhaps the g.re
Man y co mmunities usc tax doll a rs to support public stadiums. coli seum s. or co ncert ha lls . A good ex ample is the Univc rsu y o f South Carolina Coliseum (F igure 1)·.25 ). These taciluics arc used for an amazing varie ty o f recreational and! or c-erer uonial purposes. includ ing illdl.m bas ketball. circuscs. trac tor-pulls. roc k concerts. grad ua tions. ere. The)' a rc usually e xtremely large multiple-story buildings that are well-landscaped and have extensive park ing.
It is practicall y impossible to identify a movi e thea ter locat ed with in a ma ll. Howe ver, man y thea ter complexes arc now bu ilt unatt ached w ith num ero us large screening rooms and am ple pa rking. Some co mmu nities still ha ve a dri ve -in movi e thea ter that at times has been one: of the most diffi cult feat ure-s to iden tify in the urban landscape. Th e drive-in movie t heater s ite is us ually fan-shaped . With a large vertical structure at the apex of the fan (the sere-cn ). It lypiea lly ea~L" a lon g sha dow, de pending o n the t ime of day . A fan-sh aped mad netw ork is fo und w ith in the site. and there are po les placed sys temat ical ly about every 5 m on the g round that hol d the detachable spea ker. T he co ncession sta nd is almost a lways located in the cente r of the sill.'. There is usua lly no landscap ing. the terr ain bein g com posed of asphalt or gra vel. W:lrrho ll\in wS hi p pin g w arehouses receive goods and then reo rganize the mater ials acco rding to a hil l of lade n fo r shipmen t via truc ks. railroad . or sh ip to an inter im or fina l destinat ion. T he)' a rc usua lly \'cry large bu ildings w ith modestlandscaping In the case o f truc k transpo rt. there is usu a lly a large parking lot w ith an elc vat..-d 15 tl high 1doc king system on o ne or multiple sides o r rhc bu ildin g. Forklifts arc oft en present inthe ya rd . Oc casionally. so me nonperishable com moduies o r container C3r}!O box es may- bl.' X'l:n o utside in the parking arca . The mos t diagnostic Icatu rC'S arc th e tractor tra ilers that are situale-c! with Ihl.'ir ha,,' k doors aga inst thc hu ild ing or arrange-c! sys tematically throughout thc sitl.'out \If harm's way. Shipp ing and warehousing alon g harbor waterfronts usua lly invoh~ e:lItremcly large warchouscs sit uatl.'d o n the doc ks or iml1lc:diately inl;md . For example. cons ider the ae rial pho-
C H,\ P I F R
472
13
Remote Sen sing th e Urban Land scape
Co n
J'
a.
Roltcr-cua~l ...r
reereanonal facilit) , 31 the M)rt lc Beach. Sc. Pavilion am usemen t park (lev el 11191),
b. A lypical go-can trac k. The O\'Crp.1S' and musl,,1" the corners an,' ccncretc. "hik the remainder oftl1l,'
c. A waH.·r-slide ride tha t empties into a pool.
track i~ asphalt. Fig ur e 13·20 L'cmmcrcia l recreation amusement-park t':!c itillcs (revet 121',l11.
tograph (If a portion Ill' the Scanl..., \VA. harbor ill Figure 13:!6. llcrc. piles of minerals ore being loaded omc the ship fro m the conica l storage str uctures using a sop his ticated overhead conveyor- heft system. Extensive la rge warehouses arc als o located nearby. TIll' minera ls were brought to the shi pping facilhy most lik ely hy the adjacent railro ad.
O ther Commercial Fina lly, there is the mauer ofwhat tu do about allt he other my riad uf commercial landuscs Ih;1\ arc found in alm os t every urban landsca pe (hobby .c;h0!'K, Forom ars. clo rhing -aores. bow ling aile)'". etc.j. It i~ im possible 10 determ ine what typo: o f bu siness i ~ be ing conducted from their re mote sens ing attr ibutes. Only in J im mvest igation w ill 3.t!ow them to escape from la nd-use class / 7, Othe r Urban or BI/ill-llp L.mdcalegory in Table 13-3.
Services (Public and Private)
In developed countries. mankind has organized a sophi.ti· cured in frustrucrure of pnh l i c scrv ices to i III prov e the quality o f life . Some of the bui ldings a nd grounds assoc iated with thes e ser vices have relunv ely diagnos tic c haracter istics lhat a llow them Itl be identified in remote se nso r data,
Puhlic lJ u ild in ~s a nd "'acililil's (Ad m inisl r atin n. Flre. Ponce. Rl'WUC. Post :.I. Llbru rtcs, J' r iw lIs) Preenunent puhhc facihucs SLJ.:h as state capitols (Figure 13·
n al ;II\U major admi nisuauvc bu ildi ngs ( Figure 13-2ib) art re latively easy to idcnnf y in remote sensor data. They usaa lly have ..trikmg architecture because they are SUPpl.1Sl>d to last an d inspi re us fur many gene rations. They typically have
473
Commerci al and Service s Land Use
...111 R~ ...," ~l1 lli~m " ..d
b. Capuol C lf) 11.omh...'T"i (lmfeMlonal rmnoe-Jeague baseball stadium. L'ofurnbia. SC (origma ll) I :n .()()() scale].
c. High schoolbuschall diamond.
d. Atlanta Fulton County stadium. horne uf the protc ssion al Atlanta Braves hasch alltcam (originally 2)< 2 Ill ).
Figure 13-21 Examples of high school. millor-kagu., ami professional basc bnl! diamonds [leve l 12 1')~ ). l h. baseball-dia mond (hme'1lsions remain the same while the facilities for the team ami SpeC!; IIHrS chenpc drama lka lly.
....'ell-landscaped grou nds and am ple parking. w hich may he located in m u ltip le-sto ry parking garages. Nationa l monuments suc h as the S ta tue o f Libert)' in New York and L'Arc de Triomphc in Paris. France, otlcn have vel')' diagnostic architect ure (Figure 13-::!7cd . resrccll\dy).
Conversely.the only way to idcmify fire-and-res cue services is if the engines. res cue vehicles . and'or lin:lighling or rescue equipment arc te m poraril y visjble ours.ide the bu ilding. Also. some lire- statio ns have a t....o or th ree-story towe r nearby " here they practice Ilreflghting. It i:; possib le to
13
474
teo
,m,
,~I
Fo ol ltall
,~
~
~ IL r-, I .,. . ... ',.. .... -. .......... .", ~
Rem ote Se ns in g th e Urban Lan dscape
~ <,
-, -,
~
""I.
aoo ve-
~ I so~
II. Dlm~slons of II f'lOIhall
li~ld .
b.
L:n i\~i l y
o f Sou th Cllft' hna fonlOitti stadium Oeve1 121931.
-
A
1 i
'r >
.; ~
L
!"I - h '
1
~4'
h •
.-
..
)
I
I..
.:r
31M! _ l 'lIf c . [ ) lm c ll s illIl S o f 3
soccer field .
d. High school soccer field and track [le ve l 12 IQJ) , The goal peru; revealth at the lit'ld is alsoused tor I(ltllhall
i 78
,.-
....,
:!
c. Drrucnsious of a tenni s court. Figure 13-22
E:\a mpl~'l> o f II univer;j[~
f. Muluplc re mus courts at a tcnnrs dub ( I<: \ cl 12 1'ol7j.
football stadium. high .;chool socce r fie ld and track. and com munity tenms club.
Comr
475
temmercra t and SCrvices Land Use
F"tgure 13-23 L c... -ot-l iq~ lK'Ii.11 pht>lOj,.'Taphy of .1 gnl r COUI"'!>C near A tlanta. GA. with multiple long. cureilincar ruirvo O1y5. bright sandtraps. and m..nicured gr~'l;n~ (lc\ c1 1219.. j ,
Figure 13-2 4 Large-scale vertical ucriul phtltugr
identify a po lice sreuou i f the cars parked ou tside have numbers on their roo fs.
buildings. with a mp le parking nearby. In fad. rhey may be indist ingu ishable fro m lcc al Iibrancs .
Regionat po st offices arc large buildings wit h extensive parking and a sign ilkan t number o f postal trucks and smaller post a l vehicles present. Local rost offi ces art': difficult to ident ity because the y arc small . well- la ndsca ped
Prison s art: usua lly easy to ident ify because they have large buildings. amp le parking. guard rowers. mul tiple rows o f very high fencin g. and restricted access. Exercise fields arc usua lly prese nt \\ ithinrhc fenc ed perimeter.
476
C I L\ I" I EH
Remote Se ns ing the Urb an Landscape
Figure 13-25 M ult ipurpose coliseum « tadium l associated with the Unh,t"I"1\,ly "fSt"Uh ra rolina tlcv el l~ I,}(,). A rec reatio nal u r c ultura l nell! is laki n~ plac..· 011 this date.
Figure 13-26 Shipping ;lnd ....arehousing of groin and other commodities in th... Seattle. WA, harbo r. ;-':Oll.' the conica l M"r,l~c structu res. th... danorale c"n\l<.'}'or -l>clt system. 111..- 13I);c rec ta ngular warehouses. arid railroad Sf'll'S that transport raw matcna!s 10 and fromthe facility.
corm
~merc ia t
and services Land Use
a. Sl"t..- Capitol "f S"lJlh Carolina In L'olumbia l lc\ d 1:'.11 1).
c. Ellis Island and lhe Statue of Liberty '\3ti"n,,1Park in '\ew YI'Th. ~,. ( 122 17 )
d. Low-obliq ue "",rial photo,:r"p h "f I: Arc de Triomphe in Paris (122 17 ).
Figure 13-27 Public ad ministra tion buildin gs, nat ional parks, J.ntl monume nts.
4 78
CU \1'1 F!<
Remote Se n s ing the Urban Landscape
Ind.
i1 IT U!>U
An
oft
ote So 0'
1
"sI
,
;
b.
a. Fig u re 13-28
E~ampk'to
(If univ crsit) public ed ucation facilities {level I ~:!l:! -\ I. a.] Vertica l aeria l phuwl;rap h of the manicured (lllh.. Umversuy o(Soulh Carolina. founded in 11<111 . At one tim",ruostofthe buildings surrounding tk hON;SIMC were fur udminist rarors, class...s. and students and their cucndon ts. ~ " ..... most o f the bui ld ings facing the horseshoe are admhustrauve. This t}TJ('" of archncctura! design is common on other south ern campuses such as the CnlHni ty of Georgia. b.t Low-ob lique photograph of the Uuivcrsuy of Cal ifornia at Sam.. Barbara in Goleta. CA. w ith its varied arcfutectura l forms. well-m anicu red landscape. and nuncare net work o f w
"h(lrs~h(l"'''
Edueatiun Universities arc rela tively easy til ide nt it): in high spatia l resol utio n remote sensor data. Except in the dm\ ntown ar eas of the largest cuies (e.g.. New York. Chicago. AtlilnLH I. unive rsit ies us ual ly e xhibit a gellgraphic ally extensiv e collection of build ings. ope n SI1ilCCS , rec reat iona l f,lcil itics Is\.\ Imming pools, baseball, tc.lolha ll, socce r. trac k. te nnis'), gym nasiums. coliseums. and stad iums. Many Ill' the ed ucation buil di ngs arc mulnplc-siory. Als o. large uon nitorics ,In.' often prescm. Tilt' problem is usual ly de c id ing whe re the forma l university begins and cuds. Two diffcrcnr examples of umvc rsuic s arc provided in Figure 13-~R. T he University of So uth Carolina was founded in l xn l . All of ih... original administration buildings. studcm donnuorics, anJ teaching facilities were systematically or iented to look ou t upon a landscaped par k ca lled the ..horscsho...." (''In\ l·.... c1y, the oblique aerial pho tograph of a portion of the Uni\ersity of Ca lifornia at Santa
Barha m reveals the unsystcnuuic place ment of facilities interspersed w ith
Elementary l'Chonl<, have relative ly s maller bui ldings, ample parking, and a few outdoor flckls. TIICY ra rely have a poolor a foot pall stadium. Eleme nta ry schoo ls may he fenced.
It is difficult 10 itk nlif; medica l business omces or health and fitness clubs. They appear sim ilar to ma ny other nonde-
scrip t commercial acuviucs rhat can take place in a building.
:fustrial Lan d Use
cwevcr. it is relati vely easy to iden tify hospitals. The)' arc sually \·cry large multistory buildings with man y add ition s. .mple pa rking is necessary, Walkways. tramways . et c.• hen connect one buildin g 10 anome r. Sorneumes it is possiIe 10 detect t he emergency-roo m automotive entrance. omc hosp ita ls have a hel icop ter land ing pad on the gro und ron top ofa building .
Indu strial Land Use
1Ihis section inuod uces the concept of imug..: inte rpretat ion r the analysis of aerial photography and othe r types of high rial resolu tion re mo te sensor data for ex tracting industria l douse informauon. Th e heurist ic rules discu ssed lire igned 10 ena ble the interpreter who is not II specia hs r in dustrial image interpreta tion 10 ident ify those industries imarily from their image s a lone. If the image an alys t ca nlKIl spec ifically idcruify an indust ry. how ever. he o r she ;houkl st ill he' able In place it in a category that limits the lind of mdusrry it may be . The term industry include s those oo,incssl's engag ed in the extraction of raw materials. the proces.\i/l.l: of materials. and the fabri cation o f imcrmcd iatc
and finished products. First. howe ver. il sho uld come as no surprise that milita ry intelligence g:n h",ring orga nizations throughout the wo rld are very interested in monitori ng the industrial land-use of foreig n co untries . The y have developed excellent ind ustrial urget image ana lysis manuals that may a lso be used for civilian applicuuons. Several ofthe more impo rtan t ma nuals focu~ on I ) gene ral indus trial target analys is logi c IDuD. I(7 6). 2 ) the coke. iron and sted indu stries (DoD. Il)nla). 31 power and water faci li tk~ (DoD. 1(77). and 4) the petrolcum industry (OuD, 197Xhl. Co pies of these manuals mny be viewed at the Federation o f American Scienti sts hom", page {Appe nd b, A I.
4 79
from their d istin ctive forms. patterns. and rel ationships. one freq uen tly can infer the kind of ma terial or equipment obscured fro m view. For instance . unusually sha ped buildings may he specially de signed to ho use speci fic kinds of eq uiprnem. S im ilarly, ch imneys and stac ks by their number and arrangement may indicate the specific kind o f furnace or oven from which smo ke o r nox iuus gase s arc being vent ed. ldcnnficarion o f the various industry-related co mpo nents in an image may a llow the industry to be placed into one of three maj or ind ustrial catego ries (e.g.• ", PIC, 1'161 : Avery and Berlin. 11)92): extraction pnl(;cssing: fuhric urion ,
When allc mpting 10 categorize a n indu stry using remote sensing dna. il is recommended tbar the analyst I ) first decide whether it is an e xtract ion. precessing, or fabricat ion ind ustry: 2 \ if il is ,I proc essing ind ustry. deckle whether it is chemical. heal , or mec han ical processing . in that order; and ]) if it is a fabrication ind ustry. decid e whether it is light or heav y tabricauon. T here arc a tremendous variety of Industries. It is only possib le 10 prov ide a fo: w reprcse ntativc examples o f each major industry category.
Extraction Industries
EJ,II',/Cf/I·C' ind ustr ies extract the natural resou rces of the Earth \\ ith the minimum handling requi red to accumulate raw materials in a form suitable for tra nsport atio n or pro· cess mg. The ext ract ion usually take s place from a sha ll mine. opcn-p u m ine. well . or cu tt ing field. e.g .. forestry clear- cu rung o r hig h-grading {Tnble 13·4). Extractive industries typically have seve ral o f the toltowing diagnostic recognition tcutu res:
Industrial uma-Use Classification Logic the presen ce o f open-pit e xca vatio ns. ponds. mine openings o r derrick s: Industries o tteu have uniq ue' assemblages o f raw ma terials. equipme nt. final products and wa ste. as well as buildings that cha racterize the indu stry. Somcrirues these industryrelated compo nents are visible 011 the phot ography or imagery: at other times the equipment or material may he: sh eltered in build ings or otherwise o bsc ured from view. In th is case. images of other compone nts. not signific ant in themselv es bu t closel y associa ted w ith the hidde n e ssen tia l components. may still he: recorded on the image ry. Moreover.
normal and ove rsized handling eq uipment including bulldozers, dump truc ks. c ranes. pow er shovels. dredge s. tree-c utters. and mine cars; an clabornre transpo rtation syste m to mo ve the raw material about the site . incl ud ing conveyo rs. pipel il1 <:s. railro ad s. drag lines. and/or road network :
480
C H .\ P I } :K
13
Remote Sens in g the Urban Land scape
Indust
Catchment basin Tai lings pile
n-
J
Open-pit m ine
,u Tail i ng~
pile
Figure 13-29 Panchmrnnuc ~lc r" "pair Ill' lhe Kenl1<."1:o11 Rl
ex tracte d hulk materia ls stored in piles. pond s, hop pers. or tan ks; and p iles or ponds o r wa sil" that haw be en separated from the valuab le materia l o f inIe rest .
Allthe ext ract ive industry features are rarely seen at any one loc ation . O tte n the surroundi ng count!') sid ... shl)", c\ ide nee of rect a mauon. reforesta tion , c IC.• in an attempt to repa ir the e ffect s o f the ex tractive industry. A 1:19.200-scak black-and- w hire penchromatic srcreopa ir of the Kennec ott Ridgeway l\Imi ng C ompany located nea r Ridgew ay, SC , ob ta ined on March 16. 1991. IS she.... n in Figure 13-29 . T.... o wry large open -pit mine s arc visjblc in the
pho togra phs . They arc surr ounded prima rily by lohlolly rlO~ plantatio ns , The raw o re-be ar ing ma terial is extracted from the earth using hug h shovels with in the ope n-pit mines. It is transpo rted to the central facility by d um p truck s using I complex networ k of w ads. T he gold is separat ed from the ore -bearing roc k using a chemical proc ess at the mine- centra l procescing facility. Two elevated r i b o f material thal have already been proc essed (\II1.:n referred to as tailings piks) arc \ isjblc. No te that a substantial amoun t of lhe prece s-ed roc k material also has been used 10 construct a catchmeru basin . The m ine .... as de..... omrn ission..-d in 1999. The process of resto ration is underway. The larg.est "fltm-pil mme in the w odd is the Hingham Canyon Cop pe r xt inc ncar Sa lt Lake Ciry, UT. operated by Ken-
481
iIlus tri al La nd Use
a. lu'" -obhquc _,,;rial phvlv graph of the Bingham Can-
b. Tertesrna l photograph o r the mmc reveals o re trains,
yon Copper Mmc n~,1T Salt Lake L'ny, UT. the larl!...sl open-pitmine in the world .
huge shovels. and a lk nsc nt;lwork of pllwcr-line JlI'ks.
Figure 13 -30 TIll: Bingham Can~'ofl COPJX·r \t ine nca r Sal! Lake Cily. UT. ISan ext racuve indusny (1.·\,e1 l3 1:!1 1.
nteOU Copper Corpora tion. II is -I km in length and has a depth ofl\()() m. II is one ofthe fl;:\'\ featu res that man has erened unn can be seen from ~ rac ... (another is the G reat Vi all of Ch ina) . \-Im c tha n J billion to ns o f co pper ha ve been extracted. mor t' than five tunes the material excavated for l!le Panama Canal. Figure 13-30.1 is a low -oblique aerial photograph c tth e min e. Figure lJ-Jllh is a terres tria l photograph tak en w ith in the m ine. The ter restr ial photograp h pro vidcs inform.uion on j usl how large the mine is when we discove r th at the da rk linear fea tures located a lo ng: the farthesl wal l are act ua lly four lung tra ins that arc used to remove ma teria l from the minco The rai lroad tracks spiral down ro the IO\\ C"'1 lev el.
open-pit g ravelmine in South Carolina is show n in Figure D-] Ia. Material is dyna m uc d fr om the wa lls of the excavatio n a nd ca rried by' truc k to a collection po int at the base o f IIle m ine. A conveyor belt then ca rries the unsorted material up IUti III to the surface. w hero: it is sorted into various gra des o f g ravel and sand. The so rted material is then transported by truc ks to fiual destinations. Precipitation cnnnot e scape the pn. resulting in all interna l drainage pond ut mebase ofthe m ine. 1\ 11
Figure I3-J I b dep icts a sma ll portio n o f a petroleum extraclion we ll field situated in the mountainous wr rain behind Ventura, C A. Each c1<.'aring co nta ins line or more ni l we lts that an' connected via an intricate svsrcm of dirt roads . The oil is actuall y pum ped by pipeline from the wells to collec ting po ints not present in thc pho tograph.
Processin g Industries
rmn:.~.\;lJfI, ind ustries subject the accumulated raw materials to me chan ica l. che mic al. or heat treatment 10 rend er them su itable for further processing. or to produce materials from which goods and equipment can be made.
The processin g industries art' c harac teri zed by the presence of faci litie s for the storage and ha ndling o f large quant ities of bulk materials.These materials may he sto red in the open in pil es . ponds or reservoirs, or in stor age containers such ilS silos. bins. hoppers. bunkers. and open o r closed tanks. The materials arc ha ndled by p ipe lines. co nve yors. and fixed cranes . 11'; well as ra ilro ad cars and other mobile eq uipmen t. The \:011\ eyer-belt system used to sort the gravel in the ope np it m in", pre viously discussed is a good example. In addition. other outdoor equipment arc commonly present. inclcding blast furnaces, kilns. chemical -p rocessing towers. la rge chim neys o r many stac ks. indicative of'rhe kind o f proccsses being carrie d out. Th e precesses invo lved usually req uir... la fl!l' qua ntities o f power. which is ind icated b~' the presence- o f coal piles. fue l tank s. boiler houses. o r transformer yards if electric power is employed or produced. Th... buildings thai ho use the processing equipment frequcmly arc largc or at least complex ill outline and roo f struc ture . Since the process ing ofmw mate rials usually invo lves refine me nt . piles and ponds o f waste
13
482
Remote sensing th e Urban Landscape
mousu
arc co
waste The p
;mag( me
ch• • he
\ 1eo a An opcn-pu gravel mine in S"ulh Carolina (1o:'\(:l lJ l21:). The gravel is Im" Sport ed from the: base (lrlhe mme \ ia OJ "inglc conveyor ben rc several sorters al the: lop of the mine. Truc ks transport the 501'1I:d mat erial 10 final des tina tio ns.
h. Petro k um c\lracl ion from 011 ....ells in the __ lams t>chind vcmura, CA I level 1315 II. Each c~
contams ('Ille or mO«' oil wclh that afe corm«\Cd \ an intricale sys tem of..hrt roads.
Figure 13 -3 1 E\a ml' lcs o f ope n-I'll mining and petroleum ... \ lraclion ind ustries.
erv
m' m' sto SU I
cr.
;n ca
,
or
o c
,,
a . Lew -obliq ue photogra ph o f mech anica l processing 31 an
agric ultural milt .... here wheal is processed into bak ing Ilour for human consum ption and animal feed . T he grain is stored in III... :>ilu~. and the prtll:css ing la~cs place in the buildin gs. Flour and t.......· d are transported 10 market b)' In/f,;1.( 1.:\.: 1 131 11 ).
b. Low -oblique photo of mechanical processing laking place er a scwugc-rrcanncnt plant in Ne wport Beac h, CA (leve l 13215 ). Soh d, nrc mec hanically se parated fromhquids. hence th..• term mec hanic al proc essing . to.:OIC the :;.o:tlling and acration ponds. Purified etllucnt is pumped son m 10a submerg..od out fall 111 Ilk- l'ac sfic ( kean tlcv el 131151.
Figure t3-3 2 Examples of mec harucal-proce ssmg industries Hevel IJZ I ).
lustrlal Land Use
483
~ commo n. and care is req uired 10 dist ingu i!>h betw een rste \ crsus use ful raw marena ts store d in a sim itJ r manner.
merged outfall in the Pacifi c Oc ean . Water p uri fi catio n insta ll,ltio ns a re a lso mechanic a l-proce ss ing indust ries .
processin g indust ries can be subd ivided on the basis of rage componems into three .suoca ll.'gtlric:s:
A hyd roelectric ptl.... ..n plan t ut ili7cs the "hy drost atic he ad " of wa ter stored in rhclake to spin turbines that create elcc tnc uy. For example. co nsider the hydroelectric generati ng facilities at the Lake M urray Dam nca r Co furubia. SC { Figure 13-33}. Fo ur int ake to.... e..... transport wat er do.... n 200 11 10 the turbine IWUM:: \I here the water pressure sp ins the tur b inl.'s gel1l:rating electricity. T he water then enters the Sa luda River. The electric ity is trans port ed to the reg io na l pow er grid \ ia a large substation co mplex. T here is also a thermalelectric po we r plan t at this locat ion whic h w ill he di scussed in the heat -proce ssing indu stry sec tion
Ie
mechanical
chem ical
beat processing, '!Ie subca tegories
hav e funct ional sig nificance.
C h e lllic:l l - r ron'~s i nl:
..x hanical- pmcessing ind ustrie s size. son. se para te . o r orh-ise change the physical fo nn or appearanc e of the raw lerials. The image com pone nts that cha racte rize the IleChanical-pll'Ct.'Ssing indu,tries art: the: bulk ma terials scred in pile s. pond s. or reservoir s. o r o utdoor eq uipme nt sach as silos, bins. bunker s or ope n tank s. as \I ell av a n abun4mce til' handl ing eq uip me nt such as conveyors. la unders. cranes, rai l cars. a nd other mo bi le equipment. The proc essi1~ involv ed may requ ire large qua ntit ies of powe r. as indieted by.. the presence of bo iler houses \I ith the ir fuel s upply. or transformer ya rds when electric powe r is em ployed. Many of the bui ldin gs may be large or 'It least com plex in 'lllltlinc and roo f stru cture. Piles o r pon ds of waste a rc qu ite common. The iudu suics in the mec han ical-pr ocessing cme'gory diller from the other procl::ssing industries in rluu they ve fe.... pipelines. closed or ta ll ta nk". or stacks other th an boiler hIlUSl'S. Fu rthe rmore. there is a n absence nf the: ilns associated w ith the heat-processing indu-a ncs. uec hamca! proc,,'ssi ng take s p lace at the Adlu h f lour M ea l and Feed C ompany {level 132 11 ) in Columbia. SC' ( Fig.u rc 1~-32a l. G rain arr ives at the m ill by .... ay of a ra ilroad spur behind the build ings or by truck. Th ree large concrete s ilos «ore the unprocessed wh..':II. Wheat milling takes plac e in lafl!c. co mple x buildi ng 10 lhl.' right Trac tor tra ilo: rs I:tao:led up to the build ing tran :>pon Ihe tinishcd llour to loca l Jnd regio nal m.lrkcl. Figure 13-32 b dep icts a 10.... -ubliquo: ph(llo graph o f mec hanical processing ta king p lace at a se wagc-tre:
luduv n-ics
Chemical-p roc essing ind ustries utilize che micals or chem ica l proce sses to separate or rea rra nge the chem ical consutucrus ef thc raw ma ter ials, Petro leum refi neries and fertilize r p lant s nrc good examples . Pressure, hea t and catalysts, or other chemical s may be emp loyed. C losed ves se ls for ho lding. or han dl ing fluid s. gases. or suspens ions o f solids in liquids. and the u-c of fluid 110\\ in process ing the raw mate ria ls arc typica l of these indu stries. Consequently, the image co mponents that c haracte rize the chemical -proc essing indust ries are an ab undance o f d osed ta nks, p ipelines , and such large proc ess ing equipme nt :\s lowe rs for c racking or distillation . As \\ ith a ll pwcessing industries. those in th is cat egory ha ve facil it ies for the storage and hand ling o f hu lk mater ials and require large quant ities of po.... cr. The building:l. frequently are complex. a nd extensive waste pi les o r pon ds are common. The AI Qa im superp hosp ha te: tenilizer plant in Iraq is she.... n in Figu re 13-3 ~, No te the exis tenc e o f numerous enclosed stora ge tan ks. a large conica l pi le o f mw ma terials, a ci rcul ar p ond. and la fl!1.' p rl1cess ing huildings (sever al with recent bom h damage). Phosphates ma y he used to produ ce explosives suc h as those usc.1 in the Okl a homa li.'d e rnl buil d ing homhing. Thai is why thc)' ar.:: talltetl'd Juring war. Indu st ry gcn er;ltcs a sig nificant am ou nt of chemical halard(IUS wasles, So mc I." lrnpanies USl· rl' llw te sl:lIsing data 10 do c· umen t the ini tia l con diti ons undc r wh ich the materia ls are store d and then mo nitor Ihc surfa ce e Xpfe"SiOll all er they arc stnre d. r or ex amp le. Figure 13-35a is :l II,.... -u hlil.j ul: aerial phohlg nlp h o f the l o .... -lcvel Wa ste Mana geml' nt s ite al the Dcpartm.::nl l,f Ene rgy's IOO EI ;'\lev'lda Tl' st Site. Th is 1000ation pnw ide s etli ciem d isllPsa l llf radi oa..:ti\ e chcmical ....ast ..... gl' uer,lll'd in the nuclear \\ capons progra m. Waste is trucl t.-d tOlhe site in Dl'pan ment (lf Transpu n ati on appro\ ed
484
Remote Sensing the Urba n Lands cape
FiglJre 13-33 Aerial photograph of'tbc Lake I\lum~ Da S( ', hyJ rt'l("k-c-mc rower planl lle\d t;!1 anJ the S..ludarbcrmat-ct..-ctric puv. ..'T~ F r intake lowers provide lhe hl~ sure water thaI dri\l"" the turbines tb3l: P"" ducc lhe elec tricuy, The 1h<.·nnal-cld1r.c power pl.ull bums coal thai produces see In drive the separate turhi lll"S that pmlIct d ..-..:tn<.:i l}.Tho: cool is dehcered
~)
and lransported from the railroad cars roil pi!.: \ ia clime) .'!" bell,. The elc..~ & d,strihul..>J from the sire Imto the regiaul rower gnd via lhe:SIlbl.lalion
containers (i n this exam ple dnuust ami buried in the large trench . As it fills. the pit is cove red ~ jill Sl';1. Figure IJ·JSh is a low-oblique photog raph of radinac uv e wa SI;: be ing stored in a !;lI1k fa rm at the llanta rd . WA. DO E facility, The lank farm- store hy-produr t materials len On-T from plutonium extrucuou o perat ions pr ior to pcrmnncm disposal. T his by-product mate rial ha s no useful purpose a nd is stored in a pprox imate ly 177 underground storage tan ks with a cumulative 101<11 o f 55 rmflion gallons capacity. with
so me individualmuks wllgil1g up III LooO,OOO g'llln!ls. The trailers and cars in the ]OW l.'T right o f the photograp h provide some idea o fthe s il o.: ofthe Wilks.
Petroleum chemical-processing mdusmcs co nve rt raw crude oil into gasolmc. diese l fuel. synthetic textiles. and plastic. The plants usua lly have a n ex tensive. ofte n dense nctw ork of above nr underground pipel ines suc h a ~ those found in a petrole um re fin ery in Tc'(a., ( Fig ure 13-36;»)_ Storage tan ks arc etten com pletely su rrounded hy Eart h dike revetments that can contam the chemical i f a sp ill occu rs. For ex ampl e. Fig ure 13+3bh dep icts a tnnk farm at the petroleum re finery at ,\ 1 Ba srah.l raq , in le)'}t. Several o f the tan h arc on tire
and kak ing . The ta nh J iles arc containing mu ch of the spill. Figure 13-3(,c depicts tho:A llan tic Richfield pt:tIllkllm storage and transport fac ilities 111 Seattle. WA.
The heat-p rocessing indus tries utilize primarily hear to re fine. scpur.uc, or re- form lite raw materials. or to derive energy Irom them. [ron and steel production and therma le lect ric powe r plants Ihal burnnil o r coal a n: good examples. The image com ponents th.u d ist inguish this category are the large quanuucs of coni or other fuel. large chimneys. large numbers Ill' ~tac b, !lu es and ki lns o f var ious kind>. Althoug h pipelines and tanks Ircqucmly arc e mploye d in rh..-se ind uv ries they aTI;" us ually not abundant. and their presence i ~ outw e ighed by the image compo nent s cvidencing the usc or heal. As w itll Ihe other proc es sing industries, these ha ve ex tens ive taci fnic s for han dlin g and storing bulk mat erials and req uire large <.luilrt t i t i e~ o f fuel or ~)w er_ lJfl!e ou tdoor equ ipment. suc h as bla st furnaces an d kil ns, onee are employed . The hu ild lngs trcqucmly are complex. and piles o f "aste arc com mon.
In'
485
Industria l La nd Us e
FIg ure 13· 34 Imag."!) ..,f lht' AI Q ain. supcrp hospllale fertilizer plant in Iraq. obunn...-d during lht' Gulf War in 199 1 (U.S. Navy TARPS image released under the Freedom of Informa lion .\ ( 1 10 WilIiam ~ . A rkin) .
--
a. R.,di" 'll"li ve hanrdllllS waste h..-ing , t<'n." ! in drums al the Department ,,1 1·.lIng)'"s Nt'\ "d a Tes t snc Lo.... -Lcvcl W", IC Man~gemenl facility. Th e wa.' le is e\eI1l1l;11I) covere d with sa nd (CO UflOy Dt'p;lf1rn"nl of fn erg) . ID W1\2 12; Julin Prke. FAS ),
11. Hazardous-waste «orage l'lIlk~ ntrhe DO E Hanford . WA facility, At one lime ap pru.\ i tlldtc1) 2,300 person nel sllpptlfted the total tank farm activities HI Hanford (co urtesy Department \ )1' Energy. I D 303-
Iron a nd sled heal · proc !.'ssing ind ustries are US tl 311y straightfonl ani 10 id...-ntify on re mote sen~tlr data. Fo r example. Figure 13-37 is a historica l ae rial photograph o f a small portion
house thc, steel rolling mill.. and hla..t furn aces, many support buildings. and considerable smoke from large stacks .
cfr hc Bcthlchc-m Sled Company at Sparrows Point, ~ D. in
Nuclear faci 1ilief> are abo relative ly easy to ide ntify. The Fast Flux Test Facility at the Han fo rd si te in eastern Washin gtc n if> a ';OO.megawatt therm al reactor cooled by liq uid
1952. The photogra ph record.. num ....rous lo ng bui ld ing s th at
.....
OSll·Uot; John Pike. Federation of American Scienlists).
486
CHA t>T ER
a. Large-sca le v...r nca l aerial photograp h of a dense network of pipes ,11 a petroleum refiner)' in Texu .
13
Remote Sens ing t he Urb an Landscape
b. P<:l rol~ m refinery at AI Hasrah. lraq. Kote lht: targe tanl-s lllIl Eart h dikes that separate the 111_ Th i~ photograph was acq uired in 1991 durmg the {,ul f War, and some tanks are on fire and leaking (l~ Na vy TARrS imagc released under the Freedom o f Illfonn aliOll .-\cl 10 Wi1I i3m M. Ar kirn.
Fig ure 13-36 l-xamplc s o f chcmrc af-pr cc e- smg
(bcl l.l 22).
c. Chemical proccssmg, )lvragc. and transportation of petroleum products atthe Allant ic Rich field tncrhnes in Seattle. WA. ~Olc the petroleum tank farms. tanker )h,ps. and railroa d tan l.. CaN.
indusme s
lndl
487
ncr strtar Land Use
Figure 13-37 Bethlehem Steel Company 81 Sparrows P(\1nl . \H>. ("IfI ,\ priI 2';. Il,lS2.
sodium (Fig ure I3 -J Xal . [I .... as built in 1'17X 10 test pla nt eqcipmeru and fuel lo r the U.S. Government's liquid me ta l reactor deve lopment program . This program dc mon srrau..'d me techno logy nf commercia! breeder reactors . The co ntainmen! dome is easily identified in the image . A bove ground esung of nuclear materials has been banned for deca des. However. underground testing continues. Figure U -3Kb depit: ts the res ults o f one test at the Nev ada Test Si te wh en: a 100 kiloton explosive was burie d und er 635 fee t of desert alluvium and det on ated on July fl , 1962. displac ing 12 milhen IOns of earth, Unde rg roun d tests cond ucted by nat ions through out the worl d o ften leave craters suc h a~ these as ev idence ofwhat has take n pla ce . Below Me some add itiona l Iund.nuenta l image-recognition
features that may he use d til distingu ish among the three Iypc~ 01" proc essing industries: itechanical-Proccssing Indus trie s : few pipe lines or closed tanks little fuel conveyor-belt syst e ms etten present few stacks no kilns. Chemical- Processing lndusrnes : man)' closed or tall tanks. inel ud ing gasholdcrs many' pipelines much large out donr processing equipment
Heat-Processing Indus tries: a few pipelines or tanks large acrive chi mneys and.or stacks large quantities offucl kilns,
Fabrication Industries
Fabrication indu stries assemble the mechanical and che mical subcom ponents into finished prod ucts such as auromohiles, truc ks, boars und sh ips, trai lers. hea vy equi pme nt (e.g.. b ulldozers], plastic prod uct s. and electronic devic es. The fa brication ind ustries may be subdivide d into heavy and light fa b rication . Heavv-fabrication indu stries oft en have tall heavy stee l fr
Tran
Rem ot e Sensin g th e Ur ban Landscape
' BB
o. Figure 13-38 a ) The Dcpanmeraof t:n<'" rg}' Fast Flu>.: Test Facility at Hanford, WA, has a 40(1-mega...an thermal reactor. 1110." dome 'Sill: c"()fIlai nm....lI slnKlun:, b) The Sedan Crater Il.;b form cd .... ben 11 lOO-L iiotOll C''''p losi\l~ buried 635 fl beneath lhc ikso:n •• detona ted on July to, I'Hi::!. at rhe Nevada Test Silo.". displacing 12 million tOIlS of earth. The massive crater is 320 1'I~. 1.2l.iO n in diamc lcr. T\O,o cra l,;n formed from OIhn dt"lon al io ns arc ...-en in the dista nce tcou ncsy Dep t. o f Energy).
He3\ )' Machinery Fabr icati on: storage yard (or heav y me tal shapes piles ofstructu ra l steel and other ma terials finished hea vy m ach inery . Ra ilroa d Machinery Manufa cture and Repair: railroad locomotives and'or cars unde r con str uction • ra ilroad track ne two rk.
transported 10 an d from the busi ness eit her b) truck or III the railroad spur. A vertica l pl.' l'Spe..:ti\ c of him s uch structura l st~'t:l is useda the buildin g o fa pt' wer plant is presented in Figure 13-39\!. Aerial images such as this can document the progress spec ific dates in the cons rrcct iou proc ess .
OIl
Li ght Fa b r tca t lnn Shipbu ildin g : sto rage yards fu r sled plate extens ive dry -do ck an d ramp facil ities shi ps unde r con structio n large cra nes. Struc tura l Stee l f abricat io n: stor age ya rds ofstructural stcd • struct ura l steel fabricunon ya rd. A structura l stee l fabric at ion ind ustry is show n in Figure 13393. The actu a l fabncauon o f the iron-and-s teel girders used in build ing and bridge co nstruction takes place inside the large elongated bu ildi ngs . The iron and stee l stoc k mater ia ls a n: so rted by si/e and type in the ce ntral ope n-a ir sto rage yard. Two o verhead cranes (not visible) move the iro n-and stee l raw materi als back and forth (left 10 rig ht ) into the bu ildin gs to r fabrication . Raw an d finish ed materi a ls are
Belo w arc some or the fundamental image-recognition features that cau be used In dis tinguish among the major light. fabr ica tion indu strie s. Aircraft As sembly;
• aircraft or seaplane r,11l1pS(II' taxiways adja cent 10 or connected to the fab rication building hangars • finished airc raft stor ed in the op.:n. A utom obile
,\ s~ e m h l y
tea rs, truc ks. motorcy cles ):
s ingle - or m ultipl e-s tory buildings finished pa rked vehic les a rrang ed in an orderly system tcstt rackrs] tractor-trai ler shirring facilirics w ith cars on trailers rai l shirpi ng container curs . Boa t Bui ld ing and Repair:
• 489
portat ion Infra stru c tu re
,;wy fabrication at th... Khne lron and SI...e1CO, in Columbia. St: . lrun 3ml ~Iod i. '>IlR.'J b) ~iLe and rypc in the two open-air storage )'3nh, Fabricatakes place inside the buildings_ Raw materials and finished products arc poned 10and frum the faciluy \ ia truck s or the railroad spur{ le\ d 13314).
b. A dewiled vertical "erial pho!
Figu re 13-39 Examples of iron and ~ted fabrication and the 11:< of such makrials in the building of a power plant.
shipped from the sh ipr ing bays located at the back llf the building .
boa t com po nents stor ed in the o pen
Ilbcrglass form s bu ilding where li hc'l! l3 ~s appl icatio n ta kes place boartrailers finished boa rs in oren sto rage .
A f ish-canning plaru loca ted in SJ n Ped ro Hamo r. C A. is found in Figu re 13--10b . H IC ships moor ar thc dock ne xt to the plant. TIle ma nu facturing p roc ess (canning) takes place w ithin the Inrgc buildin g. Num erous tanks hold chemicals used d uring the- ca nn ing proc es s. The plau t is dischJ rg ing effluent into the harbor using an undergro und pipe .
I Packing:
hold ing pens a few ta nks
railroad s id ing Transportation Infrastructure
tractor-trailer parking.
iles; tractor- trailer shi pping and rece iving bales orcotton or ot her raw materia l
Transportation planners ett en usc remote sensor data
p ipel ine s and ta nks when creatin g synthet ic fabrics autom ouv e-compone nt
manufacturing
eo mp;tn )
III
nubia. sc. is show n in Figure 13--IOa . Raw materials are not s uscepnblc to damage by the Su n o r prcc ipnat ion sorted and stored fly type ill the ope n a ir. Fab rication s place ins ide the building. T ile finished products arc
10
upda te transpo n anon net.... o r\. maps. evaluate road and railroad conditions. sludy urban traffic paucrns at chok e po ints such as tun nels. bridges. shopping malls. a nd a irpo rts. and co nduct par king studie.. ( 1 I a a~· L. ct a l.. 1997 ). Th e mm t comprchcn sive wo rk to date ( I n remote se nsin g ap p lied 10 tra nspo rtation problems was cond ucte d hy the Nat ion a l
13
490
a. Light fabrication compan)". Some of the 1'3'" materials arc sorted b)"I)-PC: in the open air. Fahrication \.al~ place in !he Nn ldmg.
Remote Sensi ng t he Urba n Landscape
b. A Iish-canmng
Jl lan ll~C'1
13324) in San Pedro Haro,."(,
CA. and iii as:;oo,:ialL"d pollution.
Ftgure 13-4 0 Examples of light fahricalivn (manufacturing).
Con sortium o n Rem ote S<:n~ing in Tran sportation sponsored by NASA and the Department of Transportation tf\ ( RST. ~(06). Th irumala i (lOO)) re viewed "eRST research performed by co nso rtium me mbe rs on: a ] envi ron men tal impa ct for mult imodal co rrid or imp act p lanning. hI haza rd and d isaster prepared ness and li feli nes secur ity. d in fra structure asset managem ent and sec urity, and d) multirn odal tra nspo rtation flow manag ement .
Road s a nd 1IiJ,:lnn l)'S Road, may he un pave d OT pav ed, Paved highways rna) he access ible to motorists at almost an y locat ion along their rout e or they may he limited-access (freeway s, 1011 ). T he general updat ing of II mad or highway networ k cen terline map is a fundamental task . Th is is often done every one 10 five yea rs and , in area s w ith min imum tree density, can he acco mplished using imagery .... ith a spat ial resolu tion o f I 30 m (Lacy, 19(2). If mor e precise road dimensions arc requ ired suc h as the ex act wi dth of the TO;\ d and sidew a lks. then a spatial resolution 01" 0.25 - 0.5 III is required (Jen sen ct al ., 1(94). Currently, o nly large-scale aeri a l p hotog raphy can prov ide suc h planimetric informa tion . In addition. consider the aerial pho tograp h of the intersect ion sh ow n in Figure 13-41a. Th e stoplig hts suspend ed across the street. ind ivid ua l cars and truc ks, and e ven the right-o f-wa y w hite roa d ma rkings arc visible. Future unma nned aerial veh icles (U AVs) ca rryin g lightwei ght d ig ita l ca me ras might we ll provide sim ila r high -resolution inform ation at a reasonable cost l " e RST. 2(}(X1).
Ili gh....uy interchanges arc use d 10 route tra ffic onto and off nflimued-accev s highways. They com e in an end less \'~ of shapes and siz es a nd are relati vely ea sy to distinguish ea remote sensor data . For exa mple. conside r the classic limired-access interc hange show n in Figure 13--41 b. It is gClld:o slop ing a nd has very long entranc e an d exit ramp s lhat allcs tra ffic 1\, merge carefully w ith ot her tra tfl c . J'\e_\t to lIIcteomlog ica l investigation s. truffle count stud io of automobiles. airplanes. hoats, ped estrian s, and pcopl( in groups requ ire the highest te mporal reso lut ion daraonee ran g in ~ from 5 III 10 minutes. h is difficuh to resolve lIle type of ca r or boat usin g even I x I OJ data . This task requ ires high spatia l reso lution imagery fro m 0.25 - 0,5 m. Such information cun only be acquired using aer ial photograph y (' I' v ideo sensor s that arc l jlocarcd on the l Op edges of hu ildin gs looking obliquely nt the te rrai n. (II' 2) placed in aircra ft or helic opte rs and Flown repeti tively ov er the stud)' are as. Figure 13-4 1c captures the pmking chamc rcrisricson parking lilt at It siug le insuuu In time . Whcn such informslion is collec ted at an o ptimum time of J ay. future parking and tra ffic mov ement decisions can he made. Parking smdies requ ire the same high spat ial reso lution (0.25 - 0.5 ml but sl ight ly 10" er tempo ral resolu tio n I 10 - 60 m inutes). Roa d. ra ilroad. and bridge cond itions (cracks. pot holcs.eic.j arc routine ly monitored both ill snu lind occ asionally usir.g high spaua l reso lution remote senso r data . For examp le. Figure 13-4 1d presents a pa nch roma tic image o f a highway and ra ilroad br idge. Careful inspec tion by' a trained analyst pro-
Tm
49'
tra nsportat i o n In fr ast ru ctu re
I
a. lligh spatial rt"IDIUl iOll image o f an intersection acqu ired usin~ kite aer ial plmt,,~raphy.
b. A hm ucd-accc ...... highway Ink'l\:hange In T.:'l.as.
d . A ~-ria l phologruphy of highway and railroad bridges.
Figure 13-4 1 Example s 01 roods. hrr uted-accesv highways. 11l1<.-re hang<.-,;. par king. and bridges reco rded usin g \arium scales of ae ria l pho tography (level 14 11)_
vides significa nt infonunnon aboutthe couduicn ofthe wad and bridge. Road and bridge cond uion call be doc ume nted using hig h spat ial reso lution ae rial photog raphy « 0.25 x O.~ 5
rm
Ibilru lul~
Ranroa drracks. focornonv es. ca rs. and tenuiualtaciliucs arc relaliH'I) easy to dist inguish o n high spatial resolu tion im a ge f)-- be ca use
CHA PTE R
492
13
Remote Sensing the Urban Landscape
Tra n s
Z u ric h Tra in Statio n. S \\-itll'r land
Figure 13-42 The train stali,," in Zurich. S.. itzerlend. recoorccd on Augusl 16, 1002 IcI,urt.:S) Illg ltalGlobo:. lnc.).
the trac ks rarel y mllv c from yea r h i ye ar:
lon g runwayt s }
the: tracks have no right ;mgt.:s. o nly gradual curvilinear
flight-tra ffic control Io\~ er(s)
turns: tcrmmafrs l lciv ilia l\]
railroad bridges become narrow as opposed to highway bridg es. which generall y sl ay the same width as the road:
han gar s
railroad cross ing signpllsts and thei r attendant shadowsan: located at almost every maj or inte rsection with a Wild ;
an extens ive tarmac mad network coneccnng the hang;m and terminals with the runways
railroad tracks rarely cr oss other railroad track s: and
large pnrking areas
locom otiv es and railroad ca rs arc large. long, and linea r,
visible aircratt.
m ak ing them fairl y easy III identify.
Much o fth e ac tua l work or a ra ilroad lakes place in the rai lroad marshalling (, Iassilk a tioll) yard. 11 is hen: thur railroad cars go ing the same direc tion d ow n the line or railroad ca rs goi ng to the identical destination
Airpu rt C ivil ian and milit ary airports usua lly have:
Rural airports etten have a sing le run way. a w indsock. \ ISI' hie planes. and II hang,tTo r two. Fig ure 13- B;1depicts a bip lane reco rde d at appro:\ima!ety6 x (l in . spatial resolu tion. The bipl ane photog mph we, acqu ired using kuc ae rial photograp hy. A po rtion of the El Toro\larinc Air Stat ion , C . \ ( I x I It).reeordedusingacon· ventirmal camera is found in Figure I]~ J h . An IKO\ OSII x I til) imag e o f the Rona ld Reagan l'\3tional Airpo rt is presente d in Figure 13-43 c . The civilian airport has an e:\ltllsivc termina l system to move people to a nd from the plane.
a, 01
493
jra nspc rt at lo n Infrastructure
./
•
A \ ima g... biplan... ,,,,-oro..>d OIl appro:\lmat...l y 0 x (> 10. spat ial res lIiulioo u~i ng kite aerial phn((,;;rap hy rcounesy C ri!> C & '1l(00),
I.
b. JC'I aircraft OI l the 1-,1 1 0..-0 ..h rin e ·\ 11 Stalion. CA , recorded OIl appro:\imalclr I x I ft s(lillial resolu tion
c.Panchromauc I x I m im.lge uf Ru ua h.l Rcal.!"n "' alional AlrptlM in [court cs)' Space lm aging. (f Cf\l'yc, lnc.j.
Y,:a~hlllg h 'll,
DC. reco rded by the U;.o:,\O S ... tclhtc in I ~J<,l
Fig ure 13 -43 Examplc-, " I' aucran. tarmac. hangar>. and ml lna r) and ( 1\ ,11.ln rcrmmals ( Ie \ od 1-1 1J j.
l
C II.\ PTER
494
a. Sailbo.lts at illll:ho' in a harbor ncar San Francisco. C t\ [ courtes y ens C. H..-nIOO ).
Remote Sensing the Urban Landscape
b. lligh spanal rC!iOlulion vertical aerial phtltug ntl'h uf t\loche barges on l~ \1 i s~i ~s i rri Rive.. t1cin{l pushed tly two tugboats.
c. Four battles hips, ' .,.,0 troop transp o rts. ami an aircrnft currie r in stora ge at National C it)', Still Diego, C 1\
Figu re 13-44 E~ 'Ulll'lc 'i of'boats and ships reco rded on remotely 'cn~c'tt image!")' dcv et I ~ 14 1.
Conversely, so me military mrport s do not have terminals. as the crews are ferried 10 and h um the uircraft by vehicle.
T hey are o ften seen as iso la t...\1 man-made reflective o~j cxts on a relat ively uniform wurcr su rface. \\ hich can increase their objec t-to-background co ntrast.
"mils a nd Shi p..
Small boats and large ~hip!o arc rclanvelj easy to id,'mify using: high spatial recolunon rem, lie sensor data for the follow ing reasons:
Boars and ships have rclauv e ly unique shapes (i.e.. tk length is almost al.... cys at leas t t.... o times greater than the wid th. .... .th a rda ti\ d) p ointed 00.... I becau se they need to
Co
495
munl c a tlo ns a nd Utilitie s
:\I ilita r)-Appticanons - .....,., ,.....,..........
a Submarine base at Andreyeva Guba. Russia. obtained lin February Q.:':()().l
b. Aircraft grav eyard nt Davis-Mom han Air force Base ncar TU~Ml n . AZ. on August 11. 2002.
;:jgore 13-45 .. Two submarmcs are present at In.: Andrc~e"'l1 Uuba. Russia, submarine base (image courtesy (If l ma~eSat Internall,mal. In~ . l h. Th<, Aen"f"lcc \-ta i nt~n ance and Rcgcncranon Center (" \-iRe ) at !)avis·Monlhan Air Force Base in Tucson. AZ. ,h'n:s more than :'i.OUOaircra ft and providl's spare parts for n ld....r aircran in S<.'I":I ~'" thro ugho Ulllll' ""m id. The center annua lly take'!> in abou! -lon aircran for slorage and •." pons about tile loame number for return to active sel'\ice. N"llte lhc B-52 bombers In the !o" ....r lel\ poruon of the image that han' been cut into piec .... using a large blade dropped by a crane . The pieces are lell o ut in u.c open for an expended period o f umc fur snetlnc nuticua l technic al means ( i.e .• spy s.ue [[lle} verific atio n as part of lhe strategic arms limitation treaty (SA LT II Treaty lind Protocol) agrtt ille nls be twc-en 111<: United States and the Union of Soykt Socialist Rcput>lics umage court esy o f OigitalGlobc. lnc.j.
hydrod ynamicall y s fice thro ugh the "" urcr with a m inimu m amount o f fr iction. Boars and ships range in Sill,' from rhe sm a ll fami ly row ooals. pow.. r bll
and spect ral reso lution re mote se ns ing technology to mon itor the locat ion and d isposition of military equipment. For
example. Figur e 13·4 5a dep icts two subm arines al rhc Audreyeva Gu ba. Russ ia sub m a rine base. Aircraft in storage
!t lh.: Aerospace xtemtcnance and Rege ncra non Center at Davis-Monthnn Air Force Hase in tucson. AZ. arc sho.... n in Figure 13-4 5b.
Communications and Utilities
Urban/s uburban environments arc enormous consumers of e lec trical po wer. natural gas. tel ephone se n -icc. and potable wate r ( Haack et al.• 1 ~"7 1 . In addit ion. they create g reat q uan tit ies (If refuse. wastewater. and sew age . The re mo va l of stor m.... atcr from urban im pervious surfaces is also a scrions problem I Sc h u lt/~ I"XX; Jen se n et al.. 2005a ). Automated ma pping.fucitiucs management (A\l!I-'M) an d geograp hic information sys te ms «i IS) hav e been developed to man age e xtensive righr-o f-way corridors fur various utilitie s. es pecially pipelines (Jadkowski ct al., 19<)4 ). Th.. mo st fundam ental ta sk is to upd ate mar s ttl show a general ce nterline of the uti lily of interest such as a power line righ t-ofway. Th is is relatively straig htforwa rd if the ut ility is not buried and I - 30 m spa tial resolution remote scnsor da ta is availa ble . It is a lso etten necessary 10 ide nufy prototype util ity t e.g .. pi l~lillc) rou tes [Feldman et al., 1995). Suc h studies require mor e geographically exte nsive imagery. such as Lands at The matic Mappe r dura. The refore. the maj or ity o f
CHAr • .:Ie
4 96
a.
Fcn~ c,j
water tower with adjaccmmanu.... nal ll'c buildin g.
Rgure 13-46
b llmp le~
13
Remot e Sens ing t he Urba n Lan dscape
11. WIS TV- IO television stauon i!'> in the huilding on the right. It h.t-; a 11111"'11113 on th.. rout" lind a large circular satellite dl~h in the parkmg Id ~ govc mmctu oll;l:c building i, \11\ the left.
of utility u ensnu..... ion facihtie s (l e\ <:1 I-B).
the actua l and proposed right-of-way may be obse rved .....ell on image ry with I JO m spat ial resoluti on obtain ed once e..'cry o ne 10 the years.
When it is necessa ry to inventory the exact loc ation of rhc uti lily Ioot pads. tra nsm issio n IO \\ CTS. ut ility poles. man hole coveo.jhc trw centerline of the ut ility. the wid th of' thc utjlil) right-of-way, and the d imensions of build ings. pumphouse... and subsrauons, then it is necessary to have a spat ial resolut ion of fro m 0.15 - 0.6 m {Jadko w ski et al. 1(94). Fo r exa mple, Figure 13··H, depi cts a water-s torage lower and the satellite transmission taciluics associated .... ith a televis ion station.
aml]og (II" d igita l stereoscopic large-scale metric photogra phy .... ith a spat ial rc....ohuion of ~ 0.15 OJ m; U DAl{ data with masspo im post spacing of < I m and vertical acc uracy o f approximu tclv 15 em. Digital so ft-co py photogrammerry based on hig h spatial resolmion remote sensor data has revolutionized the CKJt!lll and avail ability of digital surface and digital terrain modctl (Jensen. 1'}95: Linde r. 20(l3) (Chapler (,). The extracnen rl high resofuuon b ald-earth UTf\- ls using U DAR is bce(lm~ less expe nsive and may be the t.::eh nology of choice in I~ fu ture (l laala and Brenner. Ill·)t); Hodgson 1'1 nl., 2 ()O~1 (Cbaprcr WI .
Ur b a n Digital El e va t io n Model C reation
,\ d ig ita l mod e l of' rhc earth's eleva tion is referred to gencrica lly as a digita l eleva tion mudd (1)[1\1). l f thc OEM co nta ins buildi ng and veget ation elevation in fomnuion. then it is ca lled a ,Iigifa{\'/I/:!(/('(' "'mil-! (DSM l. lf all the building and vegetation in formation have been re moved. thcn it is called a bald earth .Iigital tvrrun mod.:1 (OT.\I ). Most G IS used for socioeconomic or environmenta l planning in the urhan environment include a OSM or OT"I {Jense n ct al.. ~OO51. T.... c sensors thai can prll\ ide such in forma tion are
Te rrain ele vation in urban enviro nme nts d.lt.'s not ehangt very rar 1d1y. Th e refo re. a DT\I of an urbani..ed area need on ly be acqu ired once every I to 5 years unless there is sig nificant development and the analyst desires IIIcomp areIII ditfc rc m d ate DSr--1s or IJT\h ttl determine chang e in telT3ll eleva tion, identify unpe rm itte d additions onto huildings. eM' identity change, in hui lding hl'ights. fi gure IJ- 47 depicts I) 11 large-scale aeria l photograph uf downt(ll-\ II Co lumbia. Sf 21 a dig ita l surface mudd of the sam .' area ex tracted fnIn the stereoscopic photography M ric ling the height {If e\~ building. J lthe orthopnotograph draped 0\ cr the DSM. ereal ing a \ inual rea lity representation til' a majo r sirce-t. and~ use ofthc 1l'\\1 for model ing fhc optimum locat ion for 1<.lC3f.
~n
497
Dig ital Eleva tion Model Creation
a. Panchromatic vertical aerial phomgraph.
c. Onh"pholO draped ove r DS M
1>. DigH,,1Surface Model IDS\1j.
0.1 ,
Cellular phone transceiver location model
Figure 13-47 al Vertical ae rial photography o f downtown t'olumbie. S{ ', I'l l [)l!,.'Hal ~lIr l':lI'<' model dcnv ed using S"n ' Cl>lly photogramtue try an d ster..-osc opic imagery, C) lJil!ilal crthophoto draped ove r the DS/l.1. oj l ll., ap plicruion ofn G IS int crvisibiliry mode l 10 idcntif) dead zo nes lhm wou ld he produced if a cellular phone transceiver II ere located un this particular building.
mil a cellula r phone tran scei ve r (Jensen, 1995: Cow en and Jensen, 199 R), A rch uccts. p lanners. e ng mc'ers. and real estate pe rso nnel a rc begi nning 10 usc such informa tio n for a variety of purpo ses, A digital surface model of a portion of the Westing house Savannah River Company' nca r A iken, Sc. is show n in Figure 13-4 8. This three -di me nsiona l sce ne wa s deri ved from UDA R last rerum da ta obtained al a flthl ing dcnsuy of approximately 10 em. Xotc that this i:. nut a bald-earth digi-
tal terrain model as the huilding: and vege tation elevation intormauon are sti ll present 10 the SI.:~m:.
vcndcrhoc (:!on5) compa red nnd contr aste d elevation information derived usin g phntogrammcrric versus lidargrammetric methods for transp ort ation engineer ing design purposc-s as part o f the U,S. Department of Transportauo n's
l'ational Consortium tin Remote Se nsing in Transportation resea rch program (NCRST, 10061, lie found that elc-varion in format ion de rived from lidarpramrnctry was J US! as etfec-
CHAPTER
498
--13
Remote Sensing the Urban Landseape
syst ems that some time s gen erate dead ly tornadoes and hur· rican es. Full hemispheric disk images may be ob tainedevery 25 minutes . Intense thunderstorms in relati vely smaller regions ma y be imaged every 3.1 minutes. The spatial resolution is I x I km for the visibl e band and 4 - 8 km forth, thermal infra red bands. European nations use METEOSAT w ith visib le near-infrared bands obtained at 2.5 x 2.5 kmand thermal infrared dat a co llected at 5 x 5 km every 25 minutes. Early hurricane monitoring and modeling based on these data have saved tho usands of live s in rec ent history. For example, in 1989 Hurricane Hugo caused approximatelySI billi on in damage to resid ent ial, co mmercial. and industrial fac ilities, but no live s were lost because of remo te sensing assi sted ea rly warning and evacuation .
Figur e 13-48 Analytically hill-shaded digital surface model ( DS M) ofa portion of the Westin ghouse Sava nnah River Co mpany near Ai ken, SC, deri ved from last return LIDAR data ob tained in Nove mber, 2004, at
a posting density of approximately 10 em. The elevation of buildings, trees, transportation features and the terrain ca n be ex tracte d from the DSM .
live as that derived photogramm etricall y for transportation applicatio ns .
The publ ic also relies on ground-ba sed National Weather Servi ce Weather Surveillance Radar (WSR-88D) for precipitation mapping and timel y severe storm warning (Chapter 12). Th e maximum ran ge of the NEXRAD radar is approximately 250 nautical miles. The N EX RA D net work provides significa nt improvements in severe weather and flash tlood warnings, air-tra ffic safety, flow control for air traffic, resource protection at mi litary ba ses, and management of water, agriculture, fore st, and snow removal (NO AA ROC, 2006). The Doppler radar "c omposite reflecti vity " productis projected onto a Cartesian geographica l map w ith a I x I krn resolutio n out to 230 km or at a 4 x 4 km resolution out to 460 km . The dat a are obtained eve ry 5 minutes in severe we ather mod e, every 6 minutes in precipitation mode, and every 10 minutes in clear air mod e.
Meteorolo gi cal Data
Daily weather in urban environments affects people. schools, businesses, telecommunication, and tran sportation systems. Great expense has gone into the development of near real-time monitoring of fronta l systems, temperature, precipitation, and especiall y severe sto rm-warning sys tems. Th ese imp ortant meteorological parameters are monitored almost excl usive ly by sophisticated a irborne and groundbased remote sens ing systems. For examp le, two Ge os tatio nary Operati onal Env ironmental Satellites (GO ES) are positioned at 35,790 km above the equator in geo-synchronou s o rbit s. GOES West obtains information about the western United States and is parked at 135° west lon gitude. GOES East obtains information about the Caribbean and eastern United States and is parked at 75° west longitude. Every day millions of people wat ch the pro gr ess of fronta l
Hi gh spat ia l resolution (5 - 30 m) day- and nighttim e thermal infrared data may be used to obta in deta iled qua ntitative spatial information on the urban heat island effect (La et al, 1997). Landsat 7 Enhanced Th em at ic Mapper Plu s, with its 60 x 60 m spatia l resolution and A STE R w ith its 90 x 90 m spatial resolution are parti cu larl y useful. Th e sp atial informati on can then be used to de velop "g reening" campaignsto ame liorate the urban heat island effect,
Urban Hydrology
Civil and hydrologic eng inee rs and urban planners constantly require up to date information about urban hydrology. Two useful measur em ent s that can be rem otely sensed inc lude impervious surface area and floodpla in del ineation.
an Hydrology
499
Ext ra ction of Imperviou s Surface In form ati on
a. USGS NAPP digital orthopho to I x 1 m (red band) .
h. Extraction of impervious surface material s.
Fig ure 13-49 Impervious surface s were extra cted from U.S.G.S. 1 x I III Nation al Aerial Photography Program (NAP P) colorinfrared digital o rthophoto quarter quad (DOQO) imagery of an area in Nort h Ca rolina [courtesy Tom Tribble and Frank Obusek: North Carolina Center for Geog raphic Information and Ana lysis; Jensen and Hodgson (20 04 )].
pervious Surface Mapping
mpervious surfaces such as asphalt. concrete. and build ing eof materials keep precipitation from percola ting into the ground. The greater the amount of impervious surface mate"a\ in a watershed. the greater the runoff and the higher the ak flow of tributaries that collect the increased runoff, Sigificant work has been con ducted to deve lop methods to xtract impervious surface information from remote sensor ata. Impervious surfaces such as parking lots, highways, buildings. etc. ca n be readily iden tified on large scale remote ,sensor data using the fundamenta l eleme nts of image interf,retion. In addition, the spectra l charac teristics of selected .impervious surface materials can be co llected and used to train digi tal image processing prog rams to automatically identify impervious surface cove r and quantify its extent [Ridd, 1995). For exa mple. Figure 13-49 demonstra tes how U.S. Geol ogical Survey National Aerial Photography Program (NAPP) I x 1 m orthophotograph y was used to extract impervious surfaces associated with a large mall in North Carolina (Jens en and Hodgson. 2004). Impervious surfaces can be inventoried most accuratel y using mu ltispectral remote sensor data that has a spatial resolution of 0.25 - 10m (Ridd, 1995; Ji and Jensen. 1999;
Jensen et al., 2005ab). Urbanization is taking place at a rapid pace in many countries (Jen sen et al., 2002). It is necessary to collect impervious surface information every one to fiv~ years in such environments (Table 13-1).
Floodp lain Delineation
The geogra phic extent of floodplain s can be identified using multispectral remote sensor data in conjunction with digital terrain model (DTM) information derived from terrest rial surveyi ng. soft-copy photogramm ctry, L1 DA R or IFSA R. Vegetation cover and soil associations are often in transition at the floodplain boundary. Therefore, it is possible to utilize mu ltispectral data to identify changes in vegetation type or soi l association and use this information in conjunction wit h elevation and slope data to identify the boundary of the floodplain. Multispectral or hypersp ectra l remote sensor data with a spat ial resolution of 1 - 30 m is usually sufficient for floodplain delineat ion when used in conj unction with elevation data. In dynamic areas . floodplain delineat ion should be upda ted every one to live years (Table 13-1).
CHAPTE R
500
Critical Environmental Area Assessment
Urban/suburban environments often include very sensitive areas such as wetlands. endangered-species habitat, parks, land surro unding treatment plants, and the land in urban ized watersheds that provides the runoff for potable drinking water. Rel atively stable sensitive environments o nly need to be monitored every one to two years using a multispectral remote senso r co llec ting I - 10 m data. For extremel y critica l areas that cou ld change rapidly, multi spe ct ral remote sensors (incl uding a therma l infrared band) should obta in :: 0.25 - 2 m spatial resolution data every one to six months (E hlers et a l., 200 3).
Disaster Emergency Response
The Federal Emergency Managem ent Age ncy (part of the U.S. Departme nt of Hom eland Sec urity) is ut ilizi ng rem ote sensing data as it co nducts the Multi- Hazard Flood Map
.- 13
Remote Sensing the Urban Landscape
captured in digital frame imagery in Figure 13-50c.lftle terrain is shrouded in clouds. imaging radar often provids the mo st useful information . Post-disa ster images are registered to the predisaster image s, and manual and digital change detection takes place (Jense n, 200 5). If precise. quantitative information about damaged housing stock. disrupted transportation arteries. the flow of spilled materials. and damage to aboveground utilities are required, it is advis able to acquire post-di saster 0.25 - I m panchromatic and near-infrared data within one to two days. Such infonnatioo were indispens able in assess ing damages and allocating scarce cleanup resources . Mayors and governors o ften use pre- and post-disaser remote sensor data to obtain a rapid assessment of the devastation. For example. before and after tsunami images ofBandAceh and Gleebruk, Indonesia, revea l destro yed homes. washed-out road s and bridges. and deforestation (Figure Il· 5 1). When this information is correlated with the parcel property va lue stored in a G IS for the same square km. a quantitative do llar damage asse ssment can be made. which is indispe nsable w hen requesting disaste r assistance.
Observations
Modernizati on program. This includes mapping and analyzing data for all types of hazards. T he program require s geo detic co ntrol, aerial image ry. elevat ion, surface water extent and other thematic data wh ich are used to produce dig ital !lood map s and other hazard-related products. A ll data are serve d via the Geospatial One-Stop portal and The National Map ( Low e, 2003; FEMA, 2006). Floodi ng (e .g., Mississippi River in 1993; Rhine and Danube in 1993), hurricanes (e.g., Hugo in 1989 ; Andrew in 1991; three in Florida in 2004; Katrina in 2005), tornadoes (every yea r). fires, tanker spills, earthquakes (e.g., Saugus, CA, in 197\; Nort hridge, CA , in 1994 ), and the 2004 Indian Ocea n tsunamis demon strated that a rectified, predisaster remote sensing image database is indispens able (Jensen and Hodgson , 2006). The predisaster data only needs to be updated every one to five years. However, it should be high spatial resolu tion (I - 5 m) mu ltispectral data if possible (Je nsen and Co we n, 1999) .
\\'hen disaster strikes. high resolution (,:S 0.25 - 2 m) panchromatic and/o r near-infrared data should be acquired wit hin 12 hours to two days (Schweit zer and McLeod, 199 7). For example, Figure 13-50a records the spi ll ass ociated with an overturned tanker truck immediately after an accident. Aeri al photography acqui red immediately after the letha l Sau gus, CA, February 1971 earthq uake is shown in Figure 13-50b. Torn ado damage nea r Mec han icsville, NY, is
Table 13- 1 and Figure 13-2 reveal that there are a numberof remote sensing system s that currently provide some of the desired urban/socioeconomic information when the required spatial reso lut ion is poorer than 4 x 4 m and the temporal resolution is between I and 55 days. However, very high spatial resolution dat a « I x J m) is required to satisfy many of the soci oeco nomic data requirement s. In fact. as shown in Figure 13-2, the only senso r that currently pro vides such dat a on demand is anal og or digital aerial photogra phy (0.2; - 0.5 m). GeoE ye 's IKO NOS , with its I x I m panch romatic dat a; GeoEye 's OrbView 3, with its I x I m panchromatic data ; and DigitalGlobe's Qu ickBird, with its 0.61 x 0.61 m panchromatic data, may still not satisfy all of the data requirements. No ne o f the sensors can provide the 5- to 60minute temporal resoluti on necessary for traffic and parking studies . The GOES satellite con stell ation ( East and West) and the European M ET EOSAT provide sufficient national and regiona l weather information at reasonable temporal (3 - 25 minutes) and spatial resolution s (I - 8 km and 2.5 - ; km, respectively). Ground-based Nationa l Weather Service Weather Survei llance Radar provide s sufficient spatial resolution ( I x 1°) and tempora l resolution (5 - 10 min) for pre· cipitation and intense storm tracking in urban env ironments.
References
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a. O vertu rned tractor-t railer tanker in Alaska (Jensen and Coo•.en. 1999 ).
b. Aerial photograph y of collapsed spans o f a freeway near Saugus, CA. immediately after an eart hquake in 19 7 1. This spa n was suppo rted by pillars that could not withstand the quake.
c. Tornado da ma ge nea r Mechan icsville . NY. Thi s is I x I ft spatial resolution imagery obtai ned on June I. 1998. using a d igital frame camera. Fire and medical rescue wo rkers arc on the scene (cou rtesy Litton Emerge. Inc.).
Figure 13-50 Exam ples o f high spatia l resolut ion imagery acq uired imm edi ately afte r disasters using trad itional metri c aeria l photograph y (a.b) and a dig ital fra me came ra (c).
References
American Planni ng Association. 2006. Land-Based Classification Standards . Chicago: American Plan ning Association Research Dep artmen t. http: //www. planni ng.org/lbcs. Anderson. J. R.. Har dy. E.. Roach. J. an d R. Witm er. 1976. A Land-Use and Land- Cover Classification System for Use with Remote Sensor Data. Washington: USGS Paper #964. 28 p.
Auch. R.. Tay lor. J. and W. Acevedo. 2004. Urban Growth in American Cities: Glimpses ofU.S. Urbanization. Wash ington: USGS Circular # 1252, 52 p. Avery. T. E. an d G. L. Berl in. 1992. Fundamentals of Remo te Sensing l~ Airphoto Interpretation. NY: M acm illan. 377-404. Bati st ella. M.. Robeson. S. and E. F. Mo ran . 20 03. " S ett le me nt Design. Fore st Fragm ent at ion. and Land scape Ch ange in Ron do nia. Amazonia." Photogrammetric Engineering & Remote Sensing. 69(7):805-812,
502
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Remote Sensing the Urban Landscape
Ts unami Impacts at Band a Aceh and Gleebruk, Indo nes ia
a. Qu ickB ird 60 x 60 em image of Banda Acch. Indonesia. obtained on June 23. 2004.
c. QuickBird 60 x 60 em image ofGleebruk. Indonesia. obtained on April 12. 2004.
b. QuickBird 60 x 60 em image obtained on Dec. 28, 2004. revealing massive piles of debris.
d. QuickBird 60 x 60 em image obtained on January 2. 2005 revealing massive erosion and vegetation denudation.
Fig ure 13 -51 Before- and after-images of BandAcch and Gleebruk. Indonesia. revea ling destroyed homes, washed-out roads a nd bridges. and deforestation (images courtesy of Oig ita lGl obe . Inc.).
Carlson. T.. 2003. " Applications of Remo te Sensi ng to Urban Problems: ' Remote Sensing ofEnviro nment, 86:273 -274. Chen, D. and D. Stow, 2003, "St rategies for Integrating ln for mation from Multiple Spatial Resolutions into Land-usc/Landcover Classification Routi nes," Photogrannnetri c Engineering & Rennn e Sensi ng. 69( II ): 1279- 1287.
Clapham. W. B., 2003, "Con tinuum-based Class ification ofRemotely Sensed Imagery to Describ e Urba n Sprawl on A Waters hed Scale:' Remote Sensing of Environment, 86:322-340. Cowe n, D. J. and W. Craig, 2004, " A Retrospective Look at the Need for a Multipurpose Cadast re:' Su rveying and Land Inform ation Science, 63(4 ):205-2 14.
1eferences
Iowen, D. C. and J. R. Jen sen , 1998. " Extra ct io n and Modeling ofUrba n Attributes Using Rem ot e Sensi ng Technology," People and Pixels: Linking Remote Se nsing and Socia l Science, Washing to n: Natio na l Academ y Pres s. 164--188.
Iullingvvorth . B., 199 7, Planni ng in the USA: Policies , Issues and Processes. Lond on : Rou tled ge . 280 pp. Curran. P. J ., and T. A . Ho bson. 1987. " Lan dsa t MSS Imagery to Estimate Re sid ential Heat-Load Den sit y: ' Environment and Planning, 19:159 7- 1610 .
Da Costa. S. M. F. and J. P. Cintra. 1999, " Envi ronme nta l Anal ysis of Metropol itan Areas in Braz il." ISPRS Journal of Photogramme try & Remote Sen sin g, 54 :4 1-49 . DoD. 1976 , Indust rial Target Ana ly sis Supplemen tal Reading. Washingto n: U.S. A rmy Intell igen ce Ce nter, SupR 628 10- 11. DoD. 1977, Power/ Water Facili ty Clue Sheet , Fort Bel vo ir : Defense Mapping Scho ol. DM S No . 527. Do D, 1978a. Coke, Iron and Steel Indust ries. Fort Belvoir: Defense Mappin g Sc hool , DMS No. 555.
DoD, 19 78b. Petroleum Industries. Fort Bel vo ir : De fense Mapping Schoo l, DM S No. 553.
503
FAS. 2006. National Image Interp retati on Rating Scales , Washington: Fede rat ion of Am erican Sci entis ts, Inte lligence Reso urce Prog ram , www.fas.or g/ irp/imi nllniirs . Feldman, S. c., Pell etier. R. E., Walser, E.. Smoot, J. R. and D. Ahl . 1995, " A Prototype fo r Pipe line Ro uting Using Rem otel y Se nsed Data and Geographic Informatio n System Ana lysis." Remote Sensing of Env ironm ent , 53 :123- 131 . FE MA, 2005. National Flood Map Web Service, Washin gto n: FEMA , http ://ha za rds.fema .go v/re sourc es/flood_map_svc . htm . FG DC. 2006. Federal Geographic Data Committee. Wash ington : FG DC. http .r/www.fgdc.gov/, Frase r, C. S., Baltsavia s, E. and A. Gru en . 2002 , "P roce ssin g of IKO NO S Imagery for Submeter 3 D Positio ning and Bui ldin g Extraction, Rem ote Sensing ofEn vironm ent , 56: 177- 194. Fried l, M . A . and 13 co-autho rs. 20 02 . " Global Land Co ver Mappin g fro m MODI S : Al gor ithms and Earl y Results ." Remote Sensing 0/ Enviro nment, 83:287-302. Gamba. P.. Hellw ich. O . an d P. Lomba rdo . 2003 , " Algo rithms and Techni qu es fo r Multi-source Data Fusion in Urba n Areas:' ISPRS J ournal of Photogrammetry & Remote Sensing. 58 :1-3 .
DOE, 20 05 , Solar Photovoltaics , Wash ing ton : Dept. of Energy. http://www.e ia .doe.gov/cneaf/so lar.rencwables/ pag e/s o larphotvlso larp v.htm l.
Donnay, J . P.. Bam sley, M. J. and P. A . Lon gl ey. 200 1, Remote Sensing and Urban Ana ly sis , NY: Taylo r & Franci s. 26 8 p. Dousset, B. and F. Gourmelo n. 200 3, "S ate llite M ult i-sen sor Data An al ysis of Urban Surface Tempe ratures and Landcover." ISPR S Journal of Photogramm etry & Remote Se nsi ng , 58:43-54.
Eliassen, I.. 1992, " Infra red Th erm ography and Urban Temperature Patterns," Inti. Journal of Remote Sensin g , 13(5) :869879.
tcVa40. th e In-
Elv idge, C. D., Baugh, K. E., Kihn , E. A., Kroe h, H. W. and E. R. Davi s. 1997 . " Mapping City Lig hts wi th Ni g httime Data from the DMS P Opera tio na l Lin es ca n Sys tem," Photogra mmetric Eng ineering & Rem ote Sensi ng, 63(6 ):727- 734. Ehlers, M., Jan o wsky, R. and M . Go hler, 2003, "U ltra High Resolution Remote Sensing for Env iro nmental Monitor ing: ' Earth Observation Magazine, 12(9):27-32 .
G iri. c.. Zhu. Z. and B. Ree d, 20 05 , --A Comparative Ana lysis of th e Globa l Land Cov er 2000 and MO DIS Land Cov er Data Sets." Remote Sens ing of Em -ironm ent . 94 :123-1 3 2. GSDI. 2006. Global Spa tial Data Inf rastructure (GSDI). Washington: Federal Geographic Data Committee, www.gs d i.org/ . Haa ck . B. K. an d E. T. Slon ec ke r. 1994. " Merg ed Spaceb orn e Rada r and Th em atic Ma ppe r Digital Data for Locating Villages in Sud an, " Photogrannnetric Engineering & Remote Sensing.60(1O):1253- 1257. Haack, B. K., Gupt ill. S., Ho lz, R., Jampo ler, S. , Jensen. J . R. an d R. Welc h, 1997. "Ch apt er 15: Urb an An a lysis and Planni ng ," Manual of Photographic Interp retation. Bethe sd a: ASP&RS. Haala. N. and C. Brenn er, 199 9. Extract io n of Build ings and Tree s in Urban Env iro nme nts. ISPRS Journal of Plw togrammetry & Rem ote Sensi ng, 54 :130- 137. Hammer. A.• Hei nemann. D.. Hoyer. C., Ku hlemann . R.. Lor enz. E.. Mu ller. R. and II. G Beyer, 2003 . "S o lar Energ y
504
C IIA I'rE R
Assessment using Remote Sensing Technologies," Remote Se ns ing of Environment, 86:423--432 . Hend erson . F. M. and Z. Xia . 1998. " Radar Application s in Urban Analys is, Settlement Detection and Popul ati on Est imation:' Princip les and Applicat ions of Imagi ng Radar. J rd Ed., Manual a/ Remote Sensing , NY: John Wile y. 733-768. Herold . M.. Gold ste in. N. C. and K. C. Clarke.. 200 3. "The Spatiotemporal form o f Urban Growth: Measurement. Anal ysis and Model ing," Remote Sensing ofEnvironment, 86:286-3 02. Herold . M., Roberts. D. A.. Gardner, M. E. and P. E. Denni son , 2004, "Spectrometry for Urban Area Remote Sen sing - Devel opme nt and Analysi s of a Spectral Library from 350 to 2400 om:' Rem ote Sensing of Environment, 91 :304-3 19. Herold. M.. Scepan. J. and K. C. Clarke. 2002. "The Use of Remote Sensing and Landscape Metrics to Describe Structures and Changes in Urban Land Uses," Environment and Planning A, 34: 1443-145H . Hodg son. M. E.. Jensen, J. R., Rabe r. G.. Tu llis. J.• Davis. B.• Th ompson, G. and K. Sc huc kman. 2005, "A n Eva luation of U DAR derived Eleva tion an d Terra in Slope in Leaf-off Co nditions: ' Photogrammettic Engineering & Remote Sensing. 71(7):H I7-823 . Holz, R. K., 1988, " Population Estimation of Colon ias in the Lower Rio Grande Valley Using Remote Sensing Techniques," Annu al Meeting of the Associat ion of Am erican Geographers. Phoenix, AZ. Imhoff M. L.. Bounoua, L. Def-rie s. R.. Lawrence. W. T., Stut zer, D., Tu cker, C. J. and T. Ricketts. 2005 , " The Conse quences o f Urban Land Transformations on Net Primary Product ivit y in the Uni ted States:' Rem ote Se nsing of Environment, 89 :434-443. Jadk owski. M. A.• P. Convery. R. J. Birk and S. Kuo . 1994. "Ae riallmage Datab ases for Pipeline Right s-o f-Way Man agement:' Phot og rammet ric Engineer ing & Rem ot e Se nsing. 60(3) :347-353. Jen sen . J. R.• 1995. " Issues Invo lving the Crea tion of Digital Eleva tion Mod els and Terrain Corr ected Orthoimage ry Usin g Soft-Copy Photo grammetr y," Geocarto Int/.. I O(1): 1-1 7. Jen sen. J. R.. 2005 . Introductory Digital Image Processin g : A Remote Se nsing Persp ecti ve. JTd Ed.. Upper Saddle River. Prentice-Ha ll, 525 p.
13
Rem ote Sensing the Urban Landscape
Jensen. J. R. and D. C. Cowen. 1999. "Remote Sensing of Urban /Suburban Infrastructure and Socio-Economic At· tributes." Photogrannnetric Eng ineering & Rem ote Sensing. 65:611--{'22 . Jen sen. J. R. and M. E. Hod gson. 2004 , " Chapter 6: Remote Sen sing of Selected Bioph ysical Variables and Urban/Subs ban Phenomena." in Geography and Techn ol ogy. S. Brunn. S. Cutter and J. Harrington. Jr. {Eds.}, Boston : Kluwer, I09- 15l Jen sen. J. R. and M. E. Hodg son. 2006. " Remo te Sensing ofNalural and Man-made Hazards and Disasters: ' in Manuol oft emot e Sensing : Settlements. M. K. Ridd (Ed .). Bethesda: AS P&RS .401-429. Jen sen. J_R.• Qiu. F. and K. Patt erson. 2001 . "A Neural Network Image Interpretation System to Extract Rural and Urban Land Use and Land Cov er Information from Remote Sensor Data." Geocarto Intt., 16( I) :19- 28. Jensen. J. R. and D. L. Tol l. 1983. " Detecting Residential LandUse Deve lopment at the Urba n Fringe." PhotogrammetricEngineering & Remote Sensing, 4S:629 -643 . Jensen, J, R., Botch way, K., Bren nan -Galvin . E., Johannsen, c.. Ju rna. c.. Mabogunj e. A .• Miller. R.. Price. K.. Reining.P.. Skole, D.. Stan cio ff, A. and D. R. P. Taylor, 2002. Downto Earth : Geographic Information f or Sustainable Development in Africa. Washi ngto n: Na tiona l Academy Press. 155 p. Jen sen . J. R.. Cowen. D.. Hall s. J.• Narum ala ni. S.. Schmidt. N.. Davi s, B. A. and B. Burgess. 1994 , "Improved Urban Infrastructu re Mappi ng: and Forecastin g for BellSouth Using Remote Sen sing and G IS Techno logy," Photogrammetric Engineer ing & Rem ote Se nsing, 60(3 ):339-346. Jen sen. J. R.. Hall s. J. and J. Mich el. 1998. "A Systems Approach to Environm en tal Sensitivity Index (ES I) Mapping for Oil Sp ill Contingen cy Plann ing an d Response:' Photogramme tric Eng ineer ing & Rem ot e Sensing. 64( 10 ): 1003-1014 . Jensen . J. R_. Huan g. X.. Grav es. D_and R_Hanning. 1996. "Cellular Phone Transceiver Site Selection." Rast er Imagery in Geograp hic In/ormation Systems, S. Morain and S. Baros. (Eds.). Sant a Fe: OnWard Press. 117-125. Jen sen. J. R.. Hodgson. M. E.. Tulli s. J. A. and G. T. Raber. 2005a. "Chapter 2: Remote Sen sing of Impervious Surfaces and Buildi ng Infrastru ctu re". in Ceo-Spat ial Techno logies in Urban Environments, Berlin : Spr inge r. 5- 2 1.
References
rt-
g.
Jensen. J. R.. Saal feld , A .. Broone. F., Cowen. D.. Price. K., Ramsey, D., Lapine. L. , and E. Lynn Usery, 2005b. "Chapter 2: Spat ial Data Acquisi tio n an d Integ ration" , in A Researc h Agenda f ur Geographic Informal ion Science, Boca Raton: CRe, 17-60.
te Jr-
Ji. M. and J. R. Jen sen . 1999, "Effectivene ss of Subpixel Anal-
S. 4.
ysis in Detecting and Q uan tifyin g Urban Impervio usness from Landsat Th em atic Map per Imagery." Geocarto 11111.. 14(4):39-49.
at ea:
rk nd
a: ' d-
l acy, R., 1992 , " So uth Carolina Finds Economical Way to Update Digital Road Data," GIS World, 5( I0) :58-60. Leachtenauer. J. c.. Daniel. K. and T. Vog i. 1998. "Digiti zing Sate lli te Imagery: Qu alit y and Cost Con siderat ion s." Pho togrammetric Eng inee ring & Remote Sensing. 64 :29-34.
Light D. L.. 1993 . "The National Ae ria l Phot ography Program as a Geo graphic Information System Reso urce," Photogrammetric Engineering & Remote Sensing. 59 ( 1):61-65.
1/ -
Li ght. D. L.. 1996. " Film Cameras o r Digi ta l Sensors? The Cha llenge Ahea d for Ae rial Imagi ng: ' Photogrammetrlc Engineering & Remote Sensing . 62(3):285-291 .
505
Logicon. 1997. Mnltispectral Lmag ery Ref erence Guide. Fairfax : Log icon Geodynamic s. 100 p. Lo we. A. S.. 2003. "T he Fed eral Emergency Management Age ncy's Multi -Hazard Floo d Map Modernization and The Nat ional Map:' Photog ramm etric Engineerin g & Remote Sensing. 69( 10): 1133-1 135. NAICS, 2006. North Ameri can Indus try Class ificatio n System, Washington : Bureau of th e Census. http c//www.census.go v/ epc dlwww/n aic s.html . N PIC. 1961 . Photographic Interpretation Keys : Major Industries , Washington: NPIC, 90 p. NCRST. 2006. National Conso rtium on Rem ote Sens ing fo r Transportation , Washington : Department of Tra nsportation. www.ncg ia.ucsb. edu /ncrst/. NOAA . 2006. Coastal National Land Cover Dataset Classtficotion Scheme. Ch arleston: NOAA Coastal Services Ce nter, www .csc .noaa.gov/crs/lc a/tech_cls.html . NOAA ROC. 2006 . Rada r Opera tions Center WSR 88D. Washington: NOAA. htt p://www.roc.noaa.gov/.
P., to
Light. D. L.. 1998. personal communi cati on . Emerge , Inc.
!ent
Lindgren. D. T.. 1985. Land-lise Planning an d Remote Sens ing. Boston . Martin us Nijhhoff raegi-
l o. C. P.. 1986. "The Hum an Popul ation ." Applied Remote Sens ing, N Y: Lon gm an. 40 -70.
Lo. C. P., 1995. " Auto mated Population and Dwellin g Unit Espor
timat ion from High-Resolutio n Sa te lli te Images: A Geograph ic Inform ati on System Approach: ' Int I. Journal of Remote Sens ing, 16(1 ): 17- 34 .
Olorunfemi . J . F.. 1984. " Land-use and Population: A Linkin g Model." Photogrammetric Eng ineering & Remote! Sens ing, 50 :22 1-227.
Phil ipson . W.. 1997. Manua l of Photographic Int erpret ation. Bethesda: ASP&RS . 830 p. Pike. 1.. 2006. Sp ace Policy Proje ct ofthe Federation ofAmerican Scientists , Wash ington : Fede ration of American Scientists. http ://www.fas.org lirplimint/niirs.htm. Source of the spa tia l resolut ions associated ,...-ith the National Ima ge Int erpretability Rating System (NIIRS) .
111-
e1-
Lo. C. P. and A. K. Yeung. 2002. Concepts and Techniques of Geographic l nformatlon Sy st ems. Upper Saddle River: Pren tice-H ail , 492 p.
in
os,
e r. es in
Lo, C. P. and B. J. Fa ber, 1998, " Integ ration of Landsat Th emat ic Mapper and Cen sus Data for Quali ty of Life Assess ment ," Remote Sensi ng 0/ Envi ronm ent. 62 (2) : 143- J 57. l.o, C. P.• Quattroch i, D. A . and J. C. Luval l, 1997. "Application of High-R esol ut ion The rma l Infrar ed Remote Se nsi ng an d GIS to Assess the Urban Heat Island Effect," Intl. Journal of Remote Se nsi ng. 18(2):287 -304.
Qui . F. and J . R. Jense n. 2004, "Open ing th e Ne ural Network Black Bo x and Breaking the Know ledge Acqui sition Bott leneck of Fuzzy Systems for Remote Sen sing Image Class ifica tion ," IntI. Journal of Remote Sensing, 25(9): 1749-1 768. Ri dd. M. K.. 1995, " Exploring a V-I-S (Vegetatio n-Impervious Surface-Soi l) Model for Urba n Ecosy stem s Anal ysis throu gh Remote Sen sin g : Comparat ive Anatomy for Cities," Intl, Journal of Remote Sensing. 16( 12):2 165-21 86. Sc hultz. G. A.. 1988. " Remo te Sen si ng in Hydr ol og y: ' Jo urnal of Hydrology; IOO( 1988) :239-265 .
506
C HA PTER
Schwei tze r. B. a nd B. Mc Leod , 1997, "Marketing Tec hno logy
that Is Changing at the Speed of Light," Earth Observation Magazine , (6):7 , 22-24.
13
Remote Sensing the Urban Landscape
Sutton, P. c., 2003, A Scale-adj usted Measure of "Urban sprawl" using Nighttime Sa tell ite Im agery," Remote Sensing
a/Environment, 86:353-369.
Skole, D. L., 1994 , "D ata on Global Land-Cover Cha nge: Acquisitio n, Assessment, and Ana lysis," Changes in Land-use and Land-cover: A Global Perspective, W. B. Meyer and B. L. Turner (Eds .), Cambr idge: Cambridge Univ. Press, 437-472.
Thiruma lai, F. K., 2003, Remote Sensing and Geospatiallnfor-
Sionecker, E. T., Shaw, D. M. and T. M. Lillesand, 1998,
Tull is, J. A. and J. R. Je nsen. 2003, "Expert System House De, tection in High Spatia l Resol uti on Imagery Usi ng Size. Shape, and Context," Geocarto Intl, 18(1 ):5- 15.
" Emerg ing Legal an d Eth ica l Issues in A dvanced Remot e Sensing Techno logy," Photogrammetric Engineering & Remole
motion Technologies Applicable to Multimodol Transponation, Washingt on: De pt. of Transportation, www.ncgia.ucsb.edu/nc rst/researc h/c ip/ncg ia. ht m l, 6 p.
Sensing. 64(6):589 -595.
Small, c., 200 1, "Mu ltireso lution Analysis of Ur ban Reflectance," Proceedings. IEEE I)SPRS Workshop on Remote Sens ing and Data Fusion over Urban Areas, Rome, Nov., 8, 1-6 . Small, c., 2002 , "M ult itemporal A nalysis of Ur ban Refl ectance," Remote Sensing of Environment, 81 :427- 442. Small, C, 2003 , " High Spatial Reso lut ion Spectra l M ixt ure Analysis of Urban Reflectance," Remote Sensing of Env iron-
menl,88:170- 186.
US GS , 2006, USGS National Land Cover Data, Sioux Falls: EROS Data Center. htt p:// lan dcover. usgs.gov/c1asses.asp. Venderhoe, A . P., 2005, Technical brief Evaluating Lidarfor Engineering and Design, Was h ing to n: U.S . Department of Trans portat io n Resear ch and Special Pro gr ams Administration , www.ncgia. ucsb.ed u/ncrstJresearc h. ht m l. 2 p. W ilso n, E. H., Hur d , J. D., Civco, D. L., Pri sloe, M . P. and C. Arno ld, 2003, "Developme nt of A G eospatial Mo de l to Quantify Describe and M ap Urban Growth," Remote Sensing of Em' i-
ronmen t, 86:275-285. Small, C., 2004 , "The Landsat ETM+ Spect ral Mix ing Space," Remote Sensing 0/ Environment, 93: 1-1 7. Sutton, P., Roberts , D. , Elvidge, C. and H, Meij, 1997, "A Co mparison of Nightt ime Satelli te Imager y and Population Den sity for the Continental United States," Photogrammetrlc Engineering & Remote Sensing, 63(1 1): 1303- 1313,
Wilson, J. S., Clay, M., Ma rt in, E., St uckey, D. and K. VedderR isch, 2003, "Evalua ting En vi ronmentallnfl uen ces ofloning in Urban Ecosyste ms wit h Remot e Sensi ng," Remote Sensing
ofEnvironment, 86:303-321.
rban sing
Remote Sensing of Soils, Minerals, and Geomorphology
14
riforrta-
·.nc-
De[ape,
a ils:
rItify nvi-
f erling
'ing
O
nly 26 percent of the Earth's surface is exposed land. The remaining 74 percent is covered by water (including inland seas. lakes, reservo irs, and rivers). Very few people actuall y live on boats or on structures located in water. Almost all of human ity lives on the terrestria l, solid Earth com prised of bedrock and the weathered bedrock we call so il. Humankind is able to obta in a relatively abundant harvest in certain parts of the world from this soi l. They arc also able to extract important minerals from the bedrock and deriva tive materials that we use in industrial/commercial proce sses, hopefu lly to improve the quality of life on Earth. It is importan t to have accurate info rmation about the location. qualit y, and abundance of soils, minerals, and rocks in order to conserve these often irreplaceable natural resource s.
Bedrock is continually weathered and eroded by the combined effects of water. wind. and/or ice. The sands tone monolithic dome Ayers Rock in Australia is a good examp le of tilted sedimentary bedrock being weathered and eroded (Figure 14-1). The once buried sandstone slab was exposed to surface erosion approxi mately 70 million years ago. The eroded materials have been moved to other locations via mass transport. These unconsolidated sedimentary materials are called surfic ial deposits. Remote sensing can playa role in the identification, inventory. and mapping of soils that are on the surface of the Earth. especially when surficial soils are not covered with dense vegetation. This chapter reviews the fundamental issues associated with remote sensing the spectral characteris tics of soils. The impact of soil grain size, organic matter, and water content on soil spectral reflectance are identified. Remote sensing may also assist in the modeling of soil erosion. provid ing biophy sical information for the Universal Soil Loss Equation and other hydro logic models (e.g., King et al., 2005). Remote sensing can provide information about the chemical composition of rocks and minerals that are on the Earth's surface and not completely covered by dense vegetation. Emphasis is placed on understand ing unique absorption bands associated with specific types of rocks and minerals. as recorded using imaging spectroscopy (Dalton et al., 2004; Hook et al., 2005). In certain instances. remote sensing can be used to identify geobotanical relationships and to identify soil geochemistry or rock type (e.g.. Rowan et al., 2000) . The chapter concludes with an overview of how general geologic info rmation may be extracted from remotely se nsed data, including information on lithology. structure, drainage patterns, and geomorp hology (landforms) (Walsh et aI., 1998; Boceo et aI., 2005). Remote sensing data arc generally of limited value for detecti ng deep subsurface geologic features unless they have a surface surrogate expression that can be extrapolated to depth .
507
CHAPTE R
508
14
Ayer s Rock (Uluru), Aust r alia
Remote Sensing of Soils , Mine ral s , and Geomorphology
Soi l is co mprised of so lid particles (mi nera ls and organic matter) of varying size an d composition that make up about 50 percent of the so il's vo lume. So ils also contain liquidaed gases. A soil is characterized by one or both of the follcwing: horizons, or layers, that are disting uishable from the ieitial material as a result of add itions. losses. transfers. and transformations ofenergy and matter or the ability to suppon rooted plants in a natural environment (USDA. 2003). The weathered. unconsol idated organic and inorganic mineral material that lies on top of the bedrock shown in Figure 142 varies greatly in composition and thickness throughout the Earth. In the heartland of continents such as North Amen" it may be 25 - 300 m deep. On steep mountain slopes orin deserts it may be almost completely absent. Permafrost soils may exist in arctic climates.
Soil Horizons
QuickBird image obtained February 4, 2002. Figure 14- 1
Ayers Rock (Ul uru in aborig ine) in Australia is a mono lithic slab of Arkose sandstone that rises more than 348 m (1,100 ft) above the desert. The once horizontal sedimentary slab was tilted (folded) so that it protrudes through the surface at an angle of approximately 85°, It con ti nues be low the ground for 5 to 6 kill. Some layers of Arkose sandstone are less resistant than othe rs and erode more rapid ly. This prod uces the para llel ribs or ridges. Ayers Rock has an area of 3.33 sq. km with a circumference of 9.4 krn and lies 1,395 km (538 mil south of Darwin (courtesy DigitalGlobe, Inc.).
Soil C ha racterist ics a nd Taxo n o my
Soil is unconsolidated material at the surface of the Earth that serves as a natural medium for growing plants. Plant roots reside within this material and extract water and nutrients. Soil is the weathered material between the atmosphere at the Earth's surface and the bedrock be low the surface to a maximum depth of approximately 200 em (USDA, 1998). A mature, fertile soil is the product of centuries of physica l and chemical wea thering of roc k. combined with the addit ion of decaying plants and other organic matter (Loynachan et al., 1999). Soi l is essential to the Eart h's life-support system o n the land . Agronom ists refer to th is as the solum,
Biological, chem ica l, and physical processes crea te vertical zonat ion w ith in the upp er 200 em o r so of so ils in which there is co mparative ly free mov eme nt of gravity water and gro undwa ter ca pillary moistu re . T his res ults in the creation of relat ively ho rizontal layers, or soil horizons. There are several sta ndard hori zon s in a typi cal so il profile situated abov e the bed rock. incl uding (F igure 14-2) 0, A, E, B, C. R, and It: that may be disting uishab le from one another based o n their co lor (hue, val ue, chroma), tex ture, and chemical properties (USDA, 1998; 2003). The epipedon (G reek epi, over, upon and pedon. soil) is a horizo n that forms at or near the surface and in wh ich most of the roc k structure has been destroyed (USDA, 2003). The humus-ric h topsoil, or 0 horizon , in the epipedon contains more than 20 percent partially decayed organic matter, Thus, it is a complex mixture of inorganic soil particles and decaying organic matter. 0 horizon soils typically have a dark brown or even black surface layer ranging in thickness from a few centimeters to several meters in areas where dense plant cover exists. This horizon is created by the interaction of water, other chemicals. heat. organic material. and air among the soil particles. Plant root systems extract much of their water and nutrients from within this "zone of life" (Marsh an d Dozier. 198 1). The A horizon is a zone ofelnviation or leaching formed at the sur face or be lov..' an 0 horizon. where water moving up an d down in the so il co lum n leaches out m inera ls in solution (ions) and clay co lloids from within the soi l and relocates them to other hor izons be low. A hori zons exh ibit ob literation of a ll or much of the or igina l rock structu re. In a humid (wet)
Soil Cha racte ris t ics and Taxonomy
nie
-'-- .:0 h'ori ~on -'-c• •
w-
nd o rt he ra l
4-
tion o r irrigation. Here the materials may be deposited in the
Soil Pro file
ut nd 01 -
509
Zoneof {
Eluviation c>
Zone of { Iliuviation
he
·A I : :':' ::A ' : , . . . ' - } .. .. .. :'f: -: B I '.;., co
~~
'00-'0(--
in
Humus-rich Fine-text ured humus Light -colored I
nineral particles
.~
0
-.
o.
Colloid accumulation; Transition to subsoil
D
0
<:>
'yIrk )m
se on
air f
at up on
:es on er)
unweathered bedrock (R) below and the deve loping so il
'..0 ; -:::.·..
~Q:.:,: -
the so il. The water ma y be permanently frozen (W/l or not permanently frozen ( IV).
Soil Grain Size and Texture
~I m
\'"T
I
Bedrock
A standard soil profile as defined by the U.S. Departmentof Agriculture. The major soil horizonsare 0, A, E. B. C. situated on top of bedrock, R. The 0 horizon contains partially decayed organic matter.
Subhorizonsare transitional to and between the horizons (U .S. Department of Agriculture. 1998).
a st he Ins us,
material is co mmonly subj ected to physical and chemica l
minerals weathered ';::...• . . : . ~ ~~ :'i-:.; ,~,,:. from bedrock
:.. :.: :";-n':i.'~}r .-::" ·~r !5--
Figure 14-2
The C horizon is simply weathered parent material. lying below the B horizon. Mo st are mineral layers. Th e parent
above. Sometimes there is a water layer within or beneath
c::J (/
are t ed R, ed al
interparti cle air spaces become clogged. cementing the par-
Sub soil; usua lly a depo sit but may be
C
IOn
can collect such a mass of colloids and minerals that the
weathering from frost action, roots, plant acids. and other agents. In some cases, the C horizon is transitional between
::'·"T-:-· ;:):7::' -'
ils
rich in clay an d is co lo red red or ye llow by iron o xide s (Loynachan et aI., 1999). Over tim e, the zo ne of illu viation
ticles together. This can lead to the development of an impervious hardpan .
~= B}~6 hardpan likely -C:::::-<;:""".:-i...::::.:.-:, cr--, _= . ~ B3
lea,
B horizon, the zone of illuviation. This layer is commonly
The average diameter of grains ofsoil in a soil horizon is one of the major variab les used to identify the taxon omy of a
soil. There are three universally recognized soil grain size cla sses : sand, silt, and clay. Figure 14-3 identi fies three different scales used to classify soil particles based on their d iam eters. The U.S. Department of Ag riculture sca le is (Loynac han et al ., 1999): Sand: a} so il particle between 0.05 and 2,0 mm in
diameter; b) soil composed ofa large fraction of sa nd-s ize climate, clay minerals, ironoxides, and dissolved calcite are usually moved downward. Th is leac hi ng may ca use the A horizon to be pale and sandy, but the uppermost part is ot\en darkened by humu s (decomposed plant material) that co llects at the top of the so il. The A hori zon so ils may be influ-
enced by cultivation or animal pasturing in agricultural environments.
particles. Si lt: a} soil part icle between 0.002 and 0.05 mm in dia meter; b} soil, composed of a large fraction of silt-s ize part icle s. Clay : a} soil particle < 0.002 mm in equ ivalent di am eter; b) so il that has propert ies dominated by cla y-size particl es.
Sometimes an E horizon exists between the zone of eluviation (A horizon) and the zone of illuviation (B horizon). E
Sand, silt, and cla y- si ze particles play different ro les in the
horizons have min era l layers in which the main feature is the loss of silicate clay, iron, aluminum, or some combination of these materials, leaving a concentration of sand and silt par-
soil formation process. Soil particles with sand-size diametersenhance soil dra inage because water can percolate freely in the large air spaces between the large soil particles. Conversely, silt and clay-size soil particles enhance the move-
ticles. All or much of the original rock structure is usually
obliterated in an E horizon.
ment and rete ntion of so il capillary water. The very sma ll cla y-si ze soil particle s carry electrical charges that attract and hold minute particles of dis solved m ineral s (ions) such
The downward movement of ions and colloids in the soil often terminates at a certain location in the soil column
as potassium and calcium. Because the ions are attached to
where the upward pressure of capillary groundwater offsets that of the perc olating g ra vity wa ter from surfac e precipita-
the clay particles , they are not readily wa shed awa y. Thus. some clay in a soi l hori zon helps to mainta in soi l fertil ity by
510
CHAPTE R
14"
.Remote Sensing of Soils, Minerals, and Geomorphology
a. So il Scien ce Society of Am erica a nd U.S. Department of Agr icul tu re Soil P a rticle Size Scale Sa nd
Silt
Clay 0.002
Grave l
0.05 0.1 0.25 0.5
.!.
..
2 mm Particle size re lative to a gra in of sand 0. 15 mm in diam et er
S ilt
Clay. -: •
76.2
Sand b. MIT and British Standa rds In st itu te Silt
C lay
coarse
fine
0.002
Sand
0.006
0.02
0.06
G rav e l
coarse
fin e
0.2
0.6
Stones
2 01m
c. International Society of Soil Science Clay
I
0.002 Figu re 14 -3
San d
Silt
fine
0.02
I 0.2
Grave l
coarse
2 mm
Th ree soil particle size scales: a) Soi l Sc ience Socie ty of Ame rica. b) Massac husetts Institute of Technology and British Standards Institute. and c) International Society of Sa il Science scale (after Marsh and Dozier, 1981; Loynachan et al.. 1999).
(tundra soils), Histosols (organic soils), Inceptisols (young soi ls). Mo llisols (pra irie soils). Oxisols (tropica l soils), Spodosols (forest soi ls). Ult iso ls (low- nutrient so ils), and Vertisols (swe lling-clay soils). Add itiona l dichotomous keys a llow the sc ient ist to classi fy the soil into Sub orders, Great Gro ups, Subg ro ups, Fami ly Level, and Soil Se ries.
retaining nutrient -ric h potassium, calci um, and other disso lved m ineral s (Marsh and Dozier. 198 1). Soi l horizo ns conta in various pro portion s of sand, silt, and clay-size particles. Soil texture is the relative proportion of sand, silt, and c lay in a soi l. A typical soi l's texture is the percentage in 'weight of part icles in various size classes. The USDA soil-texture tria ngle sho wn in f igure 14-4 ident ifies the pe rcentages of sand, silt, and clay, co mprising standard so il types. For exa mple, a loam soi l found in the lower center of the diagram consists of 40 pe rcent sand. 40 percent silt. and 20 percent clay. If a so il has a greater co ncentration of sand - say, 60 percent - and 10 percent clay and 30 percent silt, it is ca lled a san dy loa m so il, etc.
Soil Tax onomy
We no longer identify a "soil type." Rather, soil sc ientists dete rm ine the soil taxonomy (Petersen , 1999). Keys to Soil Taxonomy have bee n used by the USDA Na tural Resour ces Co nservat ion Service (US DA, 2003) since 1975 to qual itative ly and qu antitat ive ly differentiate between soil taxa. T he hig hest category of the U.S. Soi l Taxono my is Soil Order. Eac h order refl ects the dominan t soil-form ing processes and the degree of soil forma tion. Th e 12 domin ant U.S. So il Orders are: Alfiso ls (hig h-nutrie nt so ils). An d isols (vo lcan ic soils), Aridisols (desert soils), Entiso ls (new soils). Gelisols
..,
The So il Taxonom y is a re latively co mplex syste m based on the use of elimi nation dichoto mous keys that allow the soil sc ientist to eva luate various cha racte ristics in a soil profile, incl uding soil color (hu e, valu e. chroma), soil-texture class, moisture conten t, bulk density, poro sity. and ch em istry. For exa mple, the first entry into the Key to So il Ord ers is, Docs the so il have I) perma frost with in 100 cm of the soil surface, or 2) ge lic materi als wit hin 100 em of the so il surface and permafrost within 200 cm of the soil surface? If it does. it is a Gel isol. If it does not, the ana lyst then prog resses through the dichotom ous key until he or she find s that the soil meets a ll the co nditions identified.
Remote Sensing of Soil Properties
From the previo us discussion it is c lear tha t most of the inform ation used by so il sc ient ists to map a so il series in a
511
Rem ole S ensing of 5011 Propertie s
where.
100
Lp : Thi s is the porti on of the recorded radiance resu lting from the downwe lling solar (E"m) and sky (E,,,,,) radiation that neve r actually reache s the so il sur face. This is un want ed atm ospheric path rad iance no ise and sho uld idea lly be remo ved from the imagery pr ior to trying to ex tract inform at io n about surficia l soils or minerals.
30
L. Som e of the do wnw e lling so lar an d sky radiation reaches the air-so il interface (boundary! layer) and f
20Y-
penetrates it approximatel y 1/2 wavelen gth ( A) deep into the so il. If the major wavelength of light being inves tiga ted is green light . the dep th of penetrati on into the so il co lumn wo uld be approxi ma te ly 0.275 urn (i.e., 1/2 of 0.55 urn), The a mo unt of rad iant flux exi ting the soi l co lumn based on the reflectio n and scatteri ng taking place at th is depth is L.f • The characteristics of the so il o rganic matter (decomposed veget ation o r animal materi al) and ino rganic (mineral) con stituents and the amo unt o f so il moisture present have a signilicant im pact on the amount of energy ab sorbed , sca tte red. and/o r reflected from this surfic ia l port ion of the soil/rock matrix. Figure 14-5a depi ct s a so il with well-develop ed 0 and A hori zon s. It is likely that most of the energy rell ected fro m th is soil w ill be rep resen tative of the constituents of the 0 hor izon . As the amount of humu s (o rga nic matter) dimin ish es. the sur face reflectance will be more representative of the characteristics of the A hori zon (Figur e 14-5b). If both the and A hori zon s are almost non existent, as shown in Figure 14-5c, the surface re flectance may be a functio n of the weath ered subso il (regolith) or even the bedrock ifi t is co mple te ly ex posed. as on a stee p mountain slope .
-( sandy
loam
90
..
Fig ure 14-4
80
70
60
10
Sand (%)
Percentages of clay « 0.002 mm ), silt (0.002 - 0.05
an-
mm ), and sand (0.05 - 2.0 mm ) in the basic soil-tex tural ciasses (USDA, 1998).
ng
region is obtai ned by direct ob servation in the field. It is essential that subs ur face so il profiles be examined and ca reful bio logical, chemical, and ph ysica l me asur emenls be obtained with in each soi l hori zon. Thu s, it is not reali stic to expect rem ote se nsi ng to be a universal pana cea that can be used to perform soi l taxa mapping witho ut in situ data col lection. Rath er. we shou ld und erstand that under cert ain conditions it is po ssible for rem otel y sensed data to be of value 10 the soi l sc ientist as he or she collects a ll the pertinent materia l necessary to per form acc urate so il classifi cati on . In fact, man y soil sc ientists tind that remote ly sense d ima ges of the terrain und er investigation are essen tia l to the so il mapping proce ss (Petersen , 1999). Fortunately, so me soil property characteristics may be measured remotel y under idea l conditions.
0-
ISS.
'or es
ce, nd is gh ets
be
For examp le, opti cal remote sensing instrum ents such as aerial photograph y, multisp ectral scanners, and hyp erspectral remo te senso rs ca n reco rd the spe ct ral refle ctance characteristics of the surface properties of soils if they are not totally obscured by de nse multiple-story shrubs or tree s with their coal esc ing ca no pies . Th eo ret ically, the tota l up well ing radiance from an ex posed soi l reco rded by the sensor onboard the aircraft or sate llite. Lt. is a function of the electromag net ic energy from the sources ident ified in Figure 145 and summa rized as
a L =L+L +L 1 P s v
(14 -1)
:
o
L ~. :
~
Some of the incident do wn welling so lar and sky radiation ma y be abl e to penetrate perhaps a few mi llimeters or even a centimeter o r two into the soil column. This may be re ferred to as volume scattering , L\~ Unlike water (refer to Chapter 12), how eve r, there may be very litt le vo lumetri c visible, near- and mid dle- infrared rad iant Ilux exit ing the so il profi le fro m any appreciable depth . In fact, a lmost a ll the sp ec olar boundary layer rellec ta nce (L,) and volum etric scattering (L ,.) may take place in the firs t few millimeters of the soi l profile, The amou nt of vo lume tric rad iant flux scattered or reflected back into the atmosphere is a fun ct ion of the wavelength of incident energy (i.e., lo nger wa ve lengt h active microwave energy may penet rate fart her into the soil, as has been demon strated in the Sa hara), the rype and amount of o rga nic/ ino rga nic co nstitue nts. the shape and den sity of the minerals, the de gree of m inera l compac tion, and the amo unt of so il mo isture pr esent. Figures 14-5b ,c suggest
C'H \ I" It.R
512
Downwel ling Sun a nd Sky lrradrance
14
' ['o tal R ~ d j J1K'C
I., .. I p ... I.s +
A horizon
1' 1>
R florilon
a Soi l with w ell-de-..eloped () anc.! A horilllih.
b. Th in 0 oonlCln O\'eT less de vd llpo..'l.1 A an d B horizon s.
thai as the 0
horizon hcCOO1 t:S less \\ ct t-d ev e lo ped. perha ps more incident cnl"Il!Y interacts wi th the so il particl es in the A horizon ( Figure 14-5b) or even the subsoi l an d bed roc k (Fig ure 14-5e ). ,11e goal of mos t soil and mi neral re mote se nsin g is In ext ract the radiance of interest from all till: othe r ra di ance co mpo nents being recorded oy the sens or sys te m. For CX:1 mpie. the scicuusr interested in identify ing the orgamc a nd inorgan ic (mine ral] ccn-ritucnt- in th e very rep layers o f the soi l profile is most co nce rne d With measuring the int egrated spect ral response ofthe surface and subs urface radian ce. i.e., L, and i; =
"
L, -I./, .
( 14-2 )
T his inv olves carefu l radi om et ric correction o f the remote sensor data to rem ove urmosphcric uncnu ution (L r,). Ideally we could di senta ngl e the indi vidual contribu tion o f L, and L" to rhc re flected rad iant n ux. Un tortuna tcly. this is diffi cult. and usuall y we m ust be co nte nt ana lyzing an inte gration (summ ation) o f these two radiance consuruems. Nevenhcless. it is possible to make some gene-ral observations about ho w surficial soi ls appe ar in rem ot e se nsor data base d o n the ir spect ral re flectan ce properties .
The spectral reflectance characteristics of soi ls arc a fun ction of
c . Very thin 0 horizon OWl subsotl and weathered bedroc k,
So ils and rocks receive irradia nce from Ilk' Sun j£_' and atmosphere (E.. ,). Tbe [,lI.al radiance U p \\ c!ling from a soil'rod maIm. toward the I"C'fJU>!t' '<:l1sor is a funcuon of radiance (rolll unwanted all11<"'rM1C scauenng (L,. ). a substantial amounld rad iance (L.) relk ...'1,'d Of scattered from the upper surface ofthc !>Oil/rod .. matrix (arrmx;maldy 1/2 wavelengt h deep). a!i1ll3ll amount otsubsurtace \ olume rric radiance (L, •• and a \ ''''1') small amount (,fr6ltianc\' from ~Un...."qlk.'fll soi l fOCI. SUbStr1lle.
Figu re 14 -5
I., + L
Remole Sensi ng of Solis, Mineral s, and Geom orph ology
several nnp orram chara cteri stic s. includin g:
soute vture tpercenrage (If san d. silt. and cl ay ) • soil moistu re content Ic.g., d ry. mo ist. satu ra ted !
organic m atter comcm iron-o xide content soil salinuy surface roug hn ess.
Gene rally, a Ilry soilrhar contains al most no orga nic malta exhibits a rela tiv ely si m ple. less co mplex s pe ctral reflecta nce curve tha n those asso ci at ed wit h terrestrial vcgeiaiioe \Ch apl er I I ) or algae-laden water bodi es (Chapte r 12). Fot e xample. Figure 14- 6 depi ct s la b spcctroradiomctcr reflertauce of dry s ilt an d tlry sand so ils. T his dem o nstrates one nl the mo st consi stent characteristics of dry so ils : inclt'Il.llng
lI'ith I/lCl1'
How ev er. as a sol! ga ins mo is ture . and/or add itional organic co ntent or iron ox id e. its s pe ctral response may de part from the sim p le c urve. l'hcrefor e, it is useful to review how these parameters influence th e spccuul res punsc of' surflcial soils, A goal of remot e se ns ing is to d isentangle the spectral response record ed from a sur ficial soil and be able III identify the proporti ons and/or lnf'lucncc o f the charac teristics ""ithin the m stnntancouv field of view o f the sens or system.
$oil Texrure and Moisture Content
There is a re lations hip be tween the size of the so il panicles fo und in a m ass o t'soil Ie.g .• m ~l an d the a moun t of moisture that the soil ca n store. Figure 1-I-7a depic ts several theoreu-
513
Remote Se n s ing of S oli Prope rlles
'"
10
O'-!---+--+--+--+--+--io.s
06 lJ.1
0.11
f)Q
1,0
I I
dry
l -+--+---+-
1-1
U
1-1
soil
15
'" .,ek:'nl!tb llotml
'roc k
nt of
mall
alter fle eIlion For
nee-
1('
of
sill~
\'is-
FIgure 14 -6
I" <1m "f'«IJ1lI'3diomctl:f reflectance curves for dl) Mil and sand wlb. Reflectance ~~'llcrally increases Wi lh increas ing wan-length lhrol,l~houl the- \ isit>le. rk;ar- and r mddlc -mfrarcd portions of lh<.' spectrum.
cal grains of sand. Incid ent rad ian t n ux may be re flec ted from the surface of the sa nd grai ns y ielding specular reneeranee. o r the incident energy lIlay penetrate so me d istanc e Into the sand particle , T he enL'rgy may then be absorbed by the panicle and turne d into heat e nergy or exn the pa rticle and he scanercd or a bsorbe d by other part icles. The void between the soil part icles is called rhc iml'nlilia! a ir Sp llc{·. The tota l refle cta nce per wavel ength (e.g .. blue, gree n. red. rear-infrar ed light) for a givc u dr y soi l w ith no organ ic conlent and no iron ox ides is u func tion of the ave rage of both the soil specular I~P<'{'/('I/ I"WI~'V from the soil part icle su rraces and the .,,,il m /,/ lIIt' rctlectance laking place due to internal scnttcriug.
anic
hesc oil s. nral fensties
-
c lcs Me
reu-
interst itial mr "pace
TIle finer clay soils have pa rticles that arc pac ked very closely to on e another, TIll' interst itial air spaces between the soi l part icles are very smal l. tonv ersely, sand pa rticles arc very large and contain re lat ively large imcr stuia l air spaces. When p rec ipitation occurs o r ground werer rises into the soi l horizon. the indi vidunl panicles may become surrounded by a thin me mb rane of capillary water . w ater may also occupy the interstitial ai r spaces (Figure 14 -7h ), The densely packed clayey soil. "' ith each III' its small pa rtic les ho ld ing a mem brane o f water aro und it. ca n ho ld a m-mcudo us amount of ....ater, Conwrscly. "-lndy sorts with thei r significa ntly larger ~il pa rticle s an d large air spaces I ) d rain much mo re rapidl y than clayey so ils and 2 ) arc d ried out much more rap idly by evapora tion tha n the cl ayey so ils. So w h. ndoes th is hav e to do wit h the spec tral re flec tance ch aracte ristics of soils? Basically, the amount of moisture he ld in the surfici al soi l
- - ~ specu lar refl ectance
volume reflecta nce
specular refl ect an ce
~,
-,
, -,
h. Frgure 14-7
'1//1/ ,
10m
a.
a ) lncidem radian t ener gy may be reflec ted from the surfac e otthc dry soil, or it may penetrate inlo the ~"i1 particles. where nmay be absorbed or scatrcrcd. The 1,lt,rI reflectance leaving the soil is a
function nft he specular reflectance and the internal volu me rclketanee. b)
A~
soil mois ture Incre ases.
each part ide may he encapsulated with a thin membrane of capillary water, The intcrstuial spcccs may also lill with water. The greater the amount uf water in the soil. the greater the absorption of inci dent clectromagncnc energy and the lower the so il reIlcctancc.
layer is a fun ction ofthe sou te xture . Th e finer the soil re xlure. tho: g reater the so il's abilit y 10 ma intain a high mo isture con ten t in the presenc e of prec ipitat ion . The greater the so il
514
14
C1IAl'n:R
"'
Remote Sens ing 01Soils. Minerals . an d Geomo rpho logy
urn and deepens the ahsllrption around the watcr-ahsorpriee bands. \,jot ice. hOl\l" l'T, that the wa ter-ahsorpt jon bands appea r to he much more acnvc. This is becau se clay ey soils with their line soil te xture manage to hold mo re moisture in the upper portionofthe soi l horizon, which allows the moisture to ab sorh so me of the incident radian t flux, creating sig" mncam dip s in and arou nd the wate r-absorption hands.
Sand
22-J~
Exp..-ricnccd image analysts kno.... that remote sensor data of exposed sod surfaces ob tained attcr a major p recipil.uim 0. 7
0 .9
II
u
1.7
L'J
2. 1
2.3
2.5
L
~ o
50
~ , .lll
~
~ \11
~
e vent such as a thu nderstorm or prolonged fron tal al-1iut) w ill be noticeably '/
211
~ lfI
"t~+-+--+-+-':::+--+---.!\o:::::;:::::::;::::::F 0 5 0.7 'PI I I U 17 1.
1,\~, ,,kngl h'l! nl J
h
Rgure 14·8
Higher 1Il<11sl11 rt' content in sandy (a l and clayl."y soil (1.» resu lts in dec rease d r.:n ccl.;tncl: throughou t th... ns ihlt:' and nca r-in frared region. c spoxia lly in Illc wawr-absorpu on OOIHJ!o al 1.4, 1.'J. and 2.7 um
(I!c>fT.'r. I'm q,
moisture. the more incident radian t energy absorbed and the less reflec ted c:ncrgy.
T his is dcmonsr ratcd for sa ndy soils wim liule surfa ce vegetat ion in Figure 14-lo: a. T he dry slInd ) so il has a relat ively simple. incn:asing vpcci ral ft'spon sc lhrollgho ut the region from 0.5 ::U' um. However, us soil mo istu re incre ases. lhe water in the upper few ce nti mete rs o f the soil begins 10 selec tively absorh , igni fl cnnt ;1I1111U I11, o f incident e nergy in the wa ter-abso rption hands at 1.4, 1.9. a nd 2.7 um . The soi l mois ture a lso lIh~(lrhs more incident radiant energy in the spec tral regio ns aJj.l<.:cnt to these abs o rption bands. The resu lt is:l muc h more complex spe ctral response', wi th charactensric dips in the reflect ance curve at the I.... 1.9 , and 2.7 11 m atmospheric water-a bsorption bands . A lso lill ie that the amoun t of reflected green. red. nca r- a nd middle-i nfrared radia nt enC'rgy i~ dr amatically reduce d as the mois ture co ntent inc rea ses . Th is same rclatitln~h ill ho lds li,r c1a)ey "Oils as demon stra ted in Figu re 14·gb. where increased moisture in the uppcr few centimetc r.- (If the so il dampens the em ire spec tral rcspt'nsc thw ughout the I\a\ekngth internl from 0.5 - 2.0
If hig h spec tra l and radiome tric resohnion sensors are available. it may I'C possible to differentia te be tween soil s with different so il textures. Th ill is because almost all soils that have il modcr.ue to large proportion o f clay-s ize panicles nhihit strong h.n /m.\}-t uhsurpfioll funds at approximately 1.4 and 2.2 urn. The spectral response of the sandy soil m Figu re l.f-Sa was not influ enced by the hyd roxyl abso rption band at 2.2 11m .... boreas the spectral res po nse of the clayey soilm f-igure 14-Xh exhibited sip mflcn m absorption at both 1.-1 and 2.21J.1ll. or CI1Urse. it i ~ only possib le to d ifferentiate between the clayey und sill's:mdy soil te xture ch aracteristics i f the su ils arc almost dry and con tain very lill ie organic matrc r rh.n could mask the rel ationship. and the se nsor is sensitive to wry specific wavelength i ntervals (c .g.• centered at 1.4 and 2.2 11 m ). Ch abrillar et a1. (2002 ) mapped ex pansive da y soi ls {smectite, illite. and kaoli nite) a long. the Colorado fnuu ran ge using hypcrs pcc tral da ta and the inforrnauen found ill the: ab sorption hands in the 1(100 - 240n nm spectral reg ion. Okin anti Puinrcr (2004 ) used hyper-spectra l data III map the sp;lIia l di stribution o f sand gra in size ( from 1.010 0.2 m ill ) in ...... indhlown abnudoncd ag ricultu ral fie lds in a de sert envi ron ment. Th ey found tha t the larger the gra in size, the tower the short-wave infrared reflectance, especia lly in the Tcg i()n~ centered on 1.7 a nd 2.2 u rn, It is als o poss ible h I .11 ffe rennatc between some soil textures using active microw ave (1-li\D:\ R) backscatter cba racrcrslies. Fur exam ple. the 19ltl ~ i\S A Sh uttle Imag ing Radar miss ion (S IR-AI missinn revealed buried river channels beneath the: sand of the Sa ha ra t J\. IcC au lcy c t a l.. 19X2)(Fig· ur..: 9-2 1l. Riv..: r (' hann d !i appea red as dark. dendritic patte m ~ in L· ha nd t2.f em ) image-s, and sand-covered bedrock returned a bright radar s ig nal. Th e r.ltlar signa ls .... ere able to penetrate up to 1- 2 III Il l" ,"CI)- dT) sand to ret urn a sigo.al
515
Remote Sensing 01Soil Pro perties
R N ' d on these relano nvhips . Ch en cr a l. (2(105) developed a biological so il crust index ( HSC I ) usi ng. Land sat Enha nced T hematic :-'1apper Plus (El ~ ") ima gery :
tion mds
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wh en: RI/.... " and R""tl TC rcn..-cm ncc in ET~ I? han ds 2 and J and L is an 3llJusime nl factor to amplily the abso lute diffe rcncc between Rvn." and R""" If the numer ator g.'ISa negative valu e. L i... rcst ri.."led to a range fro m 2: to 4. Th c' denomi nat or IS the mean reflectance of green. red and the near- in frared refl ectance in ETM ' bands 2. J. and 4 .
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from buried bedroc k and calc ium carbonate-ce men ted nodules. Willia ms and G reeley 1200 4 J found that rel ati vely short """-\ .:Iengt h C-hanu (5. 1\ em ) signals were t>csl for identifying the exte nd of dry sa nd while lon ger wa velength L-ha nd signals penetrated thin ml,isl sund best.
In the so uthea-stern U.S .. So ulheas t As ia. and several o the r parts til' the \\ orld, iron oxides are pres en t in the soil. Th e ext-renee of iron o\ idc-, },':enera ll ~ causes an inc rease in re f lectance in the red port ion of the spectrum (600 - 700 nm I. and hence its reddish co lor ( Ptgure 1 4 ~ I I) . Th ere is also a noucea ble de crea se 10 the blue- an d gr ee n re fle ctance in the iron-oxide soil. The iron-oxide so il also ex hibits an absorp tion band in the X:"O - <)00 nm region w hen compared y, uh a '
Soil Salinity Soil Organic Matter and Biological Soil Crusts
Plants and auima h. decom pos e and become organic hu mus In the tippe r p...n ions o f the so il horizon, Thc amo unt of organic matter in the soi l ha s a signiti eant impact on the spectral reflectance ..: ha raet..: risll1.:s ex po se d soils. GC W..T+ ally, the greater the nmoum of org nnic corucm in the uppe r portions of the soi l. th..' greeter the ahSOT1' lillll of inc ide nt energy and 11K' lowe r the spectral re flec tan ce. Figure 1-1--9 summarizes the cur vilinear rckuions hip I'm soils with 0 to 100percen t organic runne r.
or
Sometimes soils hav e crusts of biological maile r ( Wass enaar er al.. 2( 0 5). UioloXinl1 .1011 c r /l,I'II' art' comm unities of moS'>CS. lich... ns. Iiverw \lrts, algae, fung i. cya nobac teria and bacteria. T hey C' IO survi "e des iccalio n a nd e:>;treme h:'l11pcralllTl~ lUI' to 7C1 "C ). high 1"11, a nd high :
So il salin uy is u major en viro nmcma t hazard . The g hlhal extcmof pr imary salt -alf..".:lt'lI soils is abou t 955 \-1 ha. whi le secondary sulimzauon ;llTcch sli me 77 M ha. with 58 percent of th ese in irrigurcd areas . Nearly 20 pe rce nt o f all irriga ted I,LIl d b salt-aff ec ted. and this proport ion is mcrousing despite land rcc tum.rnon e ff orts. Salis tend In concentrate on the soi! sur face in ar id ilml irrigated areas. Men..-rnichr a nd Zinck (lOll] ) provide an ove rview of the considc r.mou-, that m ust he made when trying til ex tract sahn it), information from remote se nsing sys tems. Fig ure 14 -12:1 depicts the spectra l charucrcns ucs o f saline versus non-sali ne crush for silly 1Il,1m soi ls in Bolivia, No te that sli me spectral confusion occ urs bc twcc"n SiJlty crusts and silt 10al11 hrig hl .:rusts in Ihe blue and g ll'Cn po n ions ofthe sflCetru m (4 50 - 55 0 linn Rdle elance gene rall) in..: reas t"'S w ith increasing sUrf"Cl" soi l salt eon.:e ntrations . Salt-atfe cted soils shll w rcl;lIi\ cly highe r s pe-c tra l f'l>s pllnse in th.: \' isihlc an d nca r-infrar ed regions of the spectrum tha n no ns.aline soils lin " and slrungl) SiJlinc--sodic soils e, h ihil h igho:r spectra l re... pnnses lhan I11 I.dcrat d~ '\3llne-">Odie soi ls ( Rao et al..
UIAI'TUt
516
14-
~
Rem ote Sen sing of Soils , Mine rals , and Geomorphology
Rcn cclam:e o r mu l u~ical So il C r u~ h. narc Suil. nil
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UIIO Shad Ul\
ETM4
EH I3
VcgclJ tnm
511
III
500
""
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11100
'>00
1100
Wavelength (11m)
Fig u re 14- 10 Spectral reflec tance of bIological sOli crusts compared "llh bare '>OIl, vegetation. an d vegetation ~had(l", rdlcctam:c (ChenC'l al., 2000; repri nted wuh p<...-m ission from Elsevier ).
Loam
1995). This grap h makes it clear why saline deJlOsits typ ically sho w up as bright w hite in colo r-infrared ae rial photography Of multispectral false-co lor com posites (due to relatively high proportions of green. red, and ncar-infrared reflectance). while vege l:llio n shows l ip as hright red t due to chlorop hyll absorpti on in the green and red portions of the spec trum and high reflec tance in the ncar-infrared}, Ind icators used to d isting uis h sa line/al ka line soils are spotty gro..... th of crop s. presence of dead trees. a blue-gree n tinge . and moisture stress condition. Spcctroradiomcter measurement s o f halite with variou s sa linity concentrations are sho wn in Fig ure 14412h ( Fur iftch cr al.. 200h).
Surface Roug hnes s
As we learned in Ch apte r q (Active M icro wav e Remo te So:nsing l, the smatter the local sur face roughness rela tive to the SilC (If the incident rad iati on, the greater the spec ular spect ral reflectance from the terrain . We may utilize this infcrrnarion to ma ke some ge nera l statements abou t the amount of spectral re flectance that .~h(lltldhe exiting certain soil textures. assumi ng they contain no moisture. orga nic content, or iron oxides. Dry. [inc-te xture clayey so il should
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....
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517
Remote Sens ing ot Soli pr operties
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Figure 14- 12 a l Spectral rcllcctaucc of saline and nun-saline s" il crusts (Mcncrnicln und Zinck. 1003; rcprhucd with pcmlbs iun from Els"'l irr ) versus ihc spc crral resp onse O f\cg~·l a li(ln . hI Spcctrorndromctcr reflectance measureme nts of halite (NaCl ) at varyin!:, salt conc entrations If-anftch cr al.. 2006; ~p rinled with permission Irom Elsevie r).
prod uce a h igher spectral res ponse throughou t the visible and ncar- in frared po rtion s of the s pec tru m due 10 the nea rspecular reflccuou tha i sho uld take place fro m its surface versus silt or sand surfaces. [Infortunatclj', this is oft en not the case because a ~ moisture. orgamc content. o r iron oxide tS adde d It) the d aye y soil, it begm s dr amatically to ab sorb incide nt radi ant nux. a nd quire possi bly to appear like silt or perhaps even sand on remote sensor data. Th is ca n ca use tnrcrpreraricn proble m s.
Con versely, lIt)· sand with its well -dra ined large grains should lhl l uscl y scalie r the incide nt wavelengths of v is ible and ncar- infr ared energy more than clayey and sill soi ls . Th erefore. it is commo n for more coarse-grained san d areas to he amo ng the brigfue st terra in in the landsc ape wh ile clayey soils are a mong the darke st. King et al. (2005 ) an d Zrihi et a1. (20(J) descri be ho w surfac e roughness can be measur ed using acnve micro.... ave remote sen sing systems.
518
14 Remote Sen sin g of Rocks and Mine rals
R,I("h arc assernblagc ~ o f IIIII/eral.• thai han' interloc kin g ~rJins OT arc bound toge ther by venou s rype-, Ill' cement (usu ally silica or calcium ca rbo nate ). Whe n there is min imal vegetauon and soi l pre-ern an d the rt'lC'k material is \ isilt1c directly by the rCIIlO!" M:nsint,: syswm. it rna) be possible 1\ 1 differen tiat e between seve ral roc k 1) p..' S and obtain inforruat il," about the ir characteristics. ~lo,,1 roc k surfac es consis t of several type s of min er als . Clark 119l)l} j sugg.e sls that it is possible to mod ... 1the reflec tance front a n CXptl SL'
Rem ol e Sens ing o f Soils. Minera ls , a nd Geomo rphology
I m31:i nl: Spec rrnmetcrv Imag ing spec tro me te rs m;IY bc, used in thelab. li eld.Of ina~ airborne rcrncte sensing mission. RelleCI;\I1Ce and cmiltanc~ spec troscopy o f natural sur face, arc sensi tive til xpecuk chemical bonds in nuncrinls. In the p,IS!, one o f the problem, a csociarcd with spt:et m'C(lPY was Ih;!1 it was 100 scnsiuve ~ s ma ll changes in the chemistI')' andor the structure (If ~ ma te r ial. This resuncd in the creat ion of \'Cf) complc:l. ~. ITal reflectanc e curves that we re o ttcn unimelhgible. Fortunatel y. significant strides have been mad... in I ) th e qualil) 0( the imaging spcctromct c·r sensors, and ~ ) our abilit) to und e rstand and d isenl,mg it" the info rmatio n con tent (If thr spectrorudiomcter infor mat io n. Thus, '01 hat was once a Jrav.· bac k ti.e. . wry complex spect ral reflectance curves ) isnOli an advantage as it a llows s..:ientists to extract IIlMe valuahle infon uutiou abou t the d w m i"lf) o f the natural c.nvironmem.
( 1"'.4 ) E n cr~)- .\ latlc r I rll l' n ll' lio ns ~ Refl ect iou a nd Ahsoqll inn I' r ncl."sw "S
where r~ is the re Ilectanc c at "aH' lenglh ..l.. 1-1.. is the (\ls in... of the ang le o f incide nt light on to the rock or mineral of mterest. Jl is the cosi ne oft he an gle of emIned light. g is the phase angk. ", ' is the uvc ruge smgtc scuncnng albedo Irom the rock or mineral of intere st, 1J~ is a backscatter function. PI{ is the ave rage single particle phase func tion. and If is a function fur isonupic scuucrcrs. Armed w ith this adva nced reflectance thc"f) and the kno wn optica l cons tants of the mine rals invo lved. it is possible hi com pute the theore tical rctl..reran..-e spectra fo r I ) pure m inerals that have a smg le grain size, ! l a pu re mi ner al w ith a \ariCI) o f grai n s i.ll~. and 3 ) minera l mixtures with \ a f) ing. grain si7cs (Clark, 1'11)<»). Thi s is im]l<.lrta nt 1x-c3usc il mcans that wc may h<: ab k to J'l rcd i..:t whatthc rc lkc ta n..:c cu r. es o f spcei li,,; typc s ofmincm ls or rocks should look like at var i()1I~ wavelengths. Th is can ne im portant when we ;lllcmpt tn inkrprct thc in fo rmatio n cOll!ent o f i m a ~ i n g spectroscopy r..' motc sc nsor d,Ha " f miucra lized terra in.
Imaging Spectros copy of Rocks and Minerals
Im ag ing spcelToml.'try instrulllc nts arc u~fu l lor ol:>tJin ing q oa nt itat ive infonnati(ln a bou t roc k type and min..'ral cumpos lli(ln. Chapter 7 r<.'v iew l.'d the fundamenta l charac t<.'Tlsti..,s of imaglll,!; Spl.'ctroscopy S,,'llsor syste ms suc h as the Airhom c Visi nlc Infrarl'd Imag ing Spec tromete r (AV IRIS ). This sl'cti" n reviews thl.' fun damenlal ehamcteristk s lh,ll illlp actl,u r ilbi lity to det crm illl.' rock typl.' altd mi nera l eomp
As p rcv io usly di sc ussed. photons or" light incid..nt on a min(If rock arc ' I reflected fro m gra in su rfaces omo otber grain surfaces. .:! I pavscd throug h the gra in onto ot her grairs, and'o r 3 ) absorbed w ithin a grain, The photons that arc re flected from the grain surfac es IIr refracted through a P
era!
If e\'t.'f)' mineral a b~lH bed ,Jlld sc'llll.' red thl.' incidl.'ll t plW\lI n, nf light in lin i(k-m ic;\1 malll1l'r. then th..' fl' I-\'(lul d he no ha~i ; fill' mirll.'ra !tlg iral rl.'l11Ull.' sl.' lhi ng, Thl.' amount til' enel)l~ Iea\ inl; l.'ach type o f m inl.'ral al l.'ae h spl.'cific wa\'l'll.'n~'th \lI ould h<: lue nt ical. f-'(lrtllmu e ly, certai n types of m iner:ll~ absmb and or scatter the IIIcidl.'nt l.' ncTg) d ilTe rl.'ntl). Therc arl.' 8 number of proc e sse s that d(·termine how a minerai will absorb or scaUn thl.' inc ident ..' nl.' rIlY. Abo . ths' process...s ah'i.(lrl:> and scatter light dilTcrcnt 1y d epend ing on the Wa\l.'k l\llth ( A) o f h~hl be ing investigated. The variel}' (If :lhsllI'Ptio ll proCl.'SSl.'S amI tht.'ir v.'avckllg th uepcndcnc~ a llow 1I ~ tn deriv", info rma tion ann ul the ("1I" lIIi.I/I")' of a min· era l r"TllIll its re n ...o.:tl.'d or ..' l11 iltl.'J elll.'rgy. The idea l sc.'nsor i, the imag ing sp..·': u om..·....r beca use it can reco rd much of the ah....rptlllll info rmat ion. mu ch like usi ng a h;lIIdhc1d S~1'l)-
519
Remote Sensing o f Rock s and Mine rals
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FIgure 14-13 Com parison of a lal\or.llOf)· spect ra of alunite (an aluminum , ulfale). a simulated Land....l Tbcmauc " appeT spectra [rcsampled from the lab spectrum ). aml spL'I;lr,1 obw inL-.i u,i n;! .lII airborne 63-dlalmd GeorhY'll1cal and Fn vrronmenral Resea rch Imaging Sp...'I;lroll1 c lcr IG r.RIS )al Cupritc.X 'v. Symbols and cha nnel num bers nn me l\1 and CrF.RIS spect ra identify band centers. ..lost charactcris tic absorption halld in formation is lost with lhe T\.1 spectrum Iwuh the eM:epiiuli uf 10.... re flec tance in T ..., band 7
at 2.1 u rm while much " t'lhL" spectral information is pre....n ed in the lil::IUS spectrum. The; spectra arc ot1~1 vertically for clarity (after Kruse e t al.. I ~lj( l l_
paright the the
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radiometer. For exa mp le. co nsider thc spectral ref ectance curves for alunite shown in Figure 14- 13, The most de tailed spectral re flectance mfurruauon is obta ined using a handheld ecctroradlomctcr. Airborne spectral re flecta nce data obtained us ing the 63-o,: halll1.:1 Geophysical and Enviro nmental Researc h Imaging Spo,:ctWl1Ictt:T (GER IS\ retains much of the spectra l inform ation . Unto rnmntcly. much 01" the Spccualubsnrption iuformarion is los t when thc spec tral data arc obtai ned I"WIIl six ba nds 01" s uuulur ....d Lands at Thematic Mapper duta (Kruse cr al., I ll901. All ma terials ha ve a com plex tndex of refraction. For cxample, the vac uum of I'ul er spac e. the atmosphere, qua rtz, and water all ha ve diffe rent ind exes of re fraction , [I' we illuminate a plane surface w ith photons of lig ht from di rect ly m erhead, the light R, will be refl ec ted fro m rbe surface according 10 the Fre snel equati on :
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Figure 14-14 a ) The inde x of re fraction and extinction coefficient of quartz for the .... av clcngt h interv al (> - I (> 11m. b) The ~pectru l re flectanc e charactceisucs uf powdered quartz obtained u~in g a epcct roradiometcr (after CIJrk, I'lY'J I,
coefficient o f qllan, are sho wn in Figu re 14- 143 (Clark, I')l)l)), Fro m thi s illustration it is clear that the optical COIlstnnts of I I and K tor quart z vary strong ly with' wavelength. Note tha t the inde x o f refraction (II) reaches a minimum just be fore 1l.5 u m and 12.6 am. The rela tive reflectance o f powdcrcd quart zmeasured by a spe ctrome ter for the wavelen gth mrcrvalf rom 6 - 16 11m is show n in Figure 14-14b (Cla rk. 1999 ). The reflectance spectra of quartz throughout the vis ihie and ncar-in frare d reg ion is c ffcc uv ely zero and is therefore not sho wn. IIowever. fro m K - 9.5 11 m and at 12.6 11rn there is a d ramat ic incrca sc in refl ect ance. If quartz is to be detected at all usi0 l:! imaging spectrometry . it may be necescary to sense in the region from Ii - 10 u rn as shown. But III ha t cause s Ill" re flectance spec tra of qu artz to appear as it does'.' Why arc ccnam p.1TB ofth c spe ctrum abso rbed mo re completely then Olhcf"'.' T he answ er ties at the heart o f using imaging spt'etw mctr)' for mi ne r31 ana lysis. II is beeause of
520
e-n \1' 1Fit
14'
uic specific types of ab sorp tion that take place wit hin the mine ra ls.
As demonstrated in til t' previous illu..trarion. a typical specrrel reflectance curve ob ta ined by an imaging spec trom eter exhibits var ious max ima and minima . Th e m ini ma ere ca u....."\! b} suong ahsurpt illn bands. For example. labo rato ry and AVIRIS remote sens ing derived spec tra lo r three mineral s. kaolinue d ay. aluminum sulfa te (alu rute ). and budd ingto nn e (an ammonium fd th par) aTC shown in Figure 14- 15 [Van d.... r "I..-CT. 1994 1_ Scientists have d(.....umcnrcd that specitic mmcrat s c.\ hihl1 relat ively unique absorpuon spectra. For exam ple. ke y absorption feat ures associated \\ ith kaol inite arc typicutly found ar :!.17. 2.21, 2.32. and ::?3lo! pm. If a spectra exhibus m inima at thes< locations. it may well be kao linite . It is important to point out here that only a hype rspectra l sensor wi th a s~(" t ral bandwidth resolution of approximately I() 11m could capture ..uch info nnauon . Spectrc radiometcrs with 10 nm bandwidths might miss the impo rtant minima or maxuna ent irely. This d iagram also sugge..ts that the differences in maxima. mi nima. and the slope between nraxima and min ima might allow these three mineral s 10 be di tfercmimcd nne from a nother usin g hype rsIX"(:tr31 remote sensor data. The abs o rption bands in these minerals an: ca used by electronic and \ ibrat io nal processes.
Rem ot e Sens ing of Soi ls, Minera ls . and Geomo rphology
.......... "......••. Kaolinite .wuus
Lab
•••••'. 1_32 '. 2.38 :. -, . . .;
"' .
".
..:
Aluni te •••••
-, '
... ...
2_17 2.21
.
,
'
"\"IRIS
».
..-.. '
.., .
-,
-,
..
-, -,
A\"I RIS
....
2.10
2.()(J
Buddin gtomte
2.:W
2.:'0
2..10
Wa\ d e ngth. lJm
Electrunic t' rocesws: 'lhc most common elec tron ic process revealed in the spectral reflectance curves of min erals is due to unfil led el ectron shells oftransnion elements such as 1'\ i. Cr. Co. Fe , etc , (Clark. 19( 9 ), This is culle d a crystalfield e ffect. Absorption band s can also he caused by d l
Figure 14 ·15 Spe.:lla \lft hre..: minerals dc rivcd from the ,\ irbom: Visible Infrared Imaging Spectrometer lAVIRISI using
J
lab ' 1)<,,·I:tr,l ladi.Hllch:r (aller \"an dct ~"'tf,
1'l'i4), The vcrncnl lines identity key ahw rptioo tc.nurcs useful fur ido;mifyi ll3 kaolinite. The discrcpancy N· lw .. en the lab and AVIRtS curves f(lf cadI miucral is d ue to I ) the lab spectra ale prednccd tr om pure samples wh ereas the AVIRIS dlta a rc ext racted Ihuu rcl.nivcly lal1:<: 1 0 x 20 III :1n:J \ thilt contain a mixture of mater ials within the IFOV "f the wns or systelll. 2 ) the AVIRIS data arc recordcd through an atmosphere. and 31 the lab samples arc dry ,.hel"'''s th", real-w orld te rrain may exhibit
slight differences in soil moisture. The spectra ere ,,1li.l·t vertically for cl.mty.
Th e U.S. (koltlgiea l Survey bas compiled a Digi tal Spectral Lib(31)' /lJS
52 1
Geology
crralhbrurics. One sho uld only usc spec tra llibraries thai -e been cre ated Ilsing rigorous imag mg spectroscopy callion stand ards .
.... e obtain high spectral resolu tion remote sensing spectra
br an unknown surficial rock material. remo v e the
atrno-
!plIeric e tfccts and \:OI1\en the brightness values to percent eilecranc.... (or exuancc]. then il may be possible 10 search a nral Iibrary and jdenufy the type of m inera l that has an tical or \ -c ry similar spectra. In this manner. imagi ng lpttIfOSCopy can he used to derive signitic:mt mineralogical formation .... ith link or no in si l /l field work . In certain lIstanees. mineralogical maps can be made.
fcor example. consider the tw 0 mineral maps sho wn in Color nale 1-1· 1 dcnv LoJ from low - and high-.dt itude " VIRIS data fkained over Cuprite, :,\V [Swayze ct al., 19QQ). USGS sci:/llists first remov cd atmospheric effects in the da ta and then lISCd a computer progrJ.m [ Tctracorder ] that compared the ahbrared spectra obtained fo r each pixel in the AVIRIS data o:ith th e spectra contained in a mineral spectral re flect anc e brary. Twenty-four min eral categories were found in the 2 - 2.5 pm region using Tetracorder. Note the detai l present in !Ik' 2.3 x 7 III low-alritude ,W IRIS data whe n compared with ie results fro m the coarse IX x I!o: III hig h-al nrudc " V IRIS ala (S", ayze et al.. 1')<1<),
o
om, RIS)
f cer.
.[Ion dis; for pro-
data
reas OV
cdpk-s ~ bi t
"
,1 of
,,1
,
S It ...
Rowan ct al. (::!IHlO ) conduct cd a geohotan ical study using J"V IRIS da ta in Nort h and South Carolina to identi fy hydro1hcmlully altered rocks based on the spectral re flect ance charaet~'ristics nfforcsr vegetation growing on th em . Sparse monoculturcs l It chestnut oak resul ted in lower apparent canopy density at the altered sites, wh ich wa s ex pressed in 111~' AVI RIS dala by lower ()·I I absnrpuon inte nsity. Galvao etal. (2 005 ) used wel l-defined 2200 11m hydro xyl absorption , features to idcuti Fy hydrothe rma lly altered minerals (kaoli nrte and muscovite ) using AST EK data . Tne y cam ion. how ever. that substantial veg eta tion eo\'er luwe rs Ih<: prob;lbility ofcorrecl iden tifi cation in trop ical env iro nlllents. Ellis ;md Scolt (2004) used Hy,\ -lap hyp...rspeet ra l da t:l and ah:iorp lion band Ic atures tu d iiTe rc ntiate het ween biot ite and topaL granne mineral units in the United Kingdom . Absorption bands asr,oc iated with rem,' te sensing sa lt-a lfe.. . t ~d s,)ils are ",ummariled in Fari fieh et ill. t2006l. -\STER R l' fl fi'llill n ' 1I 1ld AINl r pt ion C h a racte r i ' l ic ~ of ral ul' fur Ro ck a nd 'Iiner ;l) Dherim inal ioll "any ur the :-pcetrdl diagno..tie characteristics ,lfr'......k!> and minemls arc found in the thernlal illrrarcd po nil.ll1 of the
spec trum. The mo st impo rta nt sa tellite senso r tha t provid es such in form ation is AS II::K - the Advanced Spcccbcmc The rma l Emission and Rc tlccncn Radi ometer launched onboard EOS Tar" . Six AS TER bands (4 - 9) cover the short- wavelength infra red (S\\ 'I R) range. Hand (, is cen tered on a clay- ubso rpuou featu re otlcn assc......iated w ith hydro therma l altera tion and mineral potential. Hand X is ce ntered on a carbonate-absorption feature. allowing glo hal d iscri mina tio n o f hmcston cs and dolom ites from ot her roc ks. Five A STER hands (10 - 14) cover the the rma l infrared (T IR) range. Ha lld ~ 10. II. and 12 arc designed 10 de tect sulfates and silica spectra l features. Evaluaung reflectance in S W IR band 6 With the thermal infrared ba nd 10 allows discrimination bet ween common minerals such as alunite (a su lfate mineral importan t 10 precious meta l deposits) and anhydrite (an evaporative sulfate common in arid regions), Rand 14 is ce nt.... red on a carbonat...-absorption spectral featu re complemen ting the SW IR hand K tSAS.-\ ASTER. 2()()(,). Geo log y
The Ea rth i" nnt rock so lid. It ts con etanny cha ng ing, moving:. and being rearranged. Gt'Ulugy is the science of rocks. It reveals the im mense history of the Eart h and e xpla ins its geological formations. From a go:ologieal viewpoin t. humanity b a rel atively relen t arr ival. and il is one species am ong man)' m illions that sha re an Earthly he ritage.
fossils. the rem ains of ancient organism s IhOll ha n' bee n turned to stone. Will iam Smi th's (1 769 - I !'> .N) work marked the hcg muiug o r geo logy. He stud ied Engl ish coal m ines and obs erve d that the same layers 1' 1' sedimentary rocks were reveale d in cuttings o ver large geog raphic are as. I lc iden1ilkd and correlated the strata by thei r fossil content. l ie discove red rh.u Ihe on kr ill whic h roc k unils were depos ited d id not vary across t heir ge og raphic e \le nl. lie eon elulled that n .ek un i t ~ (It the b<.'ll olll we re o lder than thnse ahove.
! 'al e(//IIOloXI' is the study of
S,;ouish geolog ist James !l ulto n ( 1726 - 1797 ) bu ilt upo n Smith'!> find ings ;lllJ eOI1c1 lJd~'d tha t the history o f rocks o('cu rs in (I"C/",\' (Trdil anll Hal e ll. 1( 95 ). Rl...... ks are decom posed illto sedillwm by In 'lllln·r ing . The sedi mclII is otlcn mo\ cd hy torces o f \'ro.,irm an d 1II<1.U Irmuport t() a" cum ulat... in no: w III,;ali,)n". The M.oJ ime nt is (,ft<:n e'lTISl.llida l....d into a lIe\\ type ofrod, tlwi eu uld be buril..'t! unde r more roc k. unt il. he:l\ed to Its melting poi nt. it may flow hac k unde r pre~ ..ure h) Ihe surtiJ.. . e as e \lru~ive la\a Llr to somo: interio r locat ion as intru~ i\c magma. The la\a or magma coo ls into
14'
522
roc k. Weathe ring begins immediately on extruded lava. whereas it may lake mi llennia 10 e xpose the intrusive magma at the surface, ~ he re it may he weathered. In either case. the cycle begins aga in. Huuon raised the possibility that the Earth was milch o lde r than previously thoug ht. and was cont inually ch angi ng and recyc ling itself ISel by, 1 9~ 1J ).
gemote Sens ing 01 Soils . Minera ls . and Geomorphology
II1IfizomaJly bcddcd suara
a
Anticline
r ulds
C harles Lyell ( 171)7- 1875 1, the foun der of modern ge lllngy, introdu ced IIl1i{imnif
imentary rock was formed hy the sa me processes of sedime nt depos itio n and cementation. and at the same rate as those that can be observed 1003Y. He v. as thc first to suggest that the Eart h .... as minions o f years o ld .
Finally. A lfred Wegener (1880 - 1')30 1 proposed the theo ry o f connnental dnfr. Then, during the co ld .... ar o f the 19 50s . U,S. and Russian scientists set up sen sitive vibration o.k tcctors 10 mo nitor each other s atomic tes ts. Suc h instru ment s a lso a llowed the m 10 id... ntity the epic...me r u f thousands l l f earthquakes throug hout the wor ld. These epicenters usually occ urred along dist inct ive lines. It hccumc clear to geo logists that these I inc s we re edg es of enormous plates that covere d the Eart h 's surface and thur earthquakes were the res u lt of friction between the plates. Co ntinents nn the pla tes were slowly mov ing on the sur face of the Earth. The concept of pIalI.' tectonics is re lated but not idcmic a t to contine nta l drift. Tod ay. mos t geological phenomena can be explained hy these two concepts. Most of ou r geo logic in fonnation co mes from detailed ill in\ estigauon by geologists and palcull tlJlogisb. The} excav ate. bore hole s in the Earth to extract geo logic co re sa mples, and inte rpret fossi l rema ins . ln add ition . so me of these sc ientists us... airborne and satellite remote sensing technology to supple me nt the ir ill sitn invesngauons. Rem ote ly sensed image s a rc routinely iruc rprc ted I" ide n lil~' lithology. structur e. d rainage -pattern c1 mraelerist ies.· and land forms. In adduion. remote se nsi ng is often used in minera l and petroleum exploration.
J j tu
Uthology
GeologiSls usc remote sens ing in co nj unction w ith in .f llll observation to ide nti fy the IllhQloKY ofa reck t)PC. i.c .• ill. or igin , Th e d ifferent rock types arc formed by one of three processes: • igf/l'OlI,~
ree ks are formed fro m molten material;
c. ' - - -Figure 14· 16
~)
-
-
-
-
-
-
-
----
Iloriw l\lally bcdd..d strata. bj ltorizontally bed-
dcd strata Ih;11 has be...." COillpr",sl'd. creating fold! 10 the rud " includin g anticlines and synclines. cfAll l'x'lml'k of faulting \\. ht:r.:: a !lInd has bee dowmh mwn relauve 10 1\000 stable blocks of r'll:l Thi ~ i ~ referred 10 as rifling.
wdimt'lIlary roc ks are forme d from 111\: panicles of pre-
l·.\ i!>ting roc ks and pla nt and animal rema ins: or
metamorphic roc ks are form..d by ap plying heat and pressure to pre v ioudy cx isti ng roc k. Roc ks arc weathered fro m the parent material and Iran" parted !ly erosion and mass tran sport. T he- unconsolidated sedirncruary materia ls arc called .Iu,./i("io.ll deposits. Th... surficia l depos its may be transported an d eve ntually deposited hy water. in w hich case we call them all/lvial deposes. Examples include atluvia l fans . sandbars, sp its. and river tcrraees. If rhc unconsolidated mate rial is tran sported b} ice, we have g lacia l till , including es kers and dru mlins. WhctJ the un consolidated material is transported b} the wind, .. e en counter eolian land scapes. includ ing sand dunes and glacia ! loe ss dcpo-ats. Fina lly. the ma ss wasting of rocks by grin It)" ca n produc c talu s or sc ree deposits. Under certain favorable c ircumstances. a ll these materials may be visible on remote sensor data.
(
,
523
Geo logy
S!rUcrure
..
Tho: major mountain ranges of the "odd are o f \ olcanic or bided or igin . The mountains in the oc ean (i sland s) arc usu.lily volc anic. The \'3St majority (If mo untains found on thecon tinents were create d by folding . Bas ical ly. lI1lJS t o r the MJg('"f.'.• i.• (mountain bu ild ing) ta kes pla ce at the margins of d\( continents "here con tinenta l plates push against one lIIOIher and .... he re rock i:. compressed and forced to move IIp\\ ards. perhaps thousand s o f meters.
.l.
IllOnronl.llly b.:.J.kd
Rod. type dete rmines ho .... mu ch stress (or compress ion ) it
.:an withstand. when a roc k (Fi gure 14- 1(>31 is subjec ted to comprcvsion, it may experience I) d mtic de forma tion. in . hich case it may return to its o rig ina l shape and size after ibc stres s IS remov ed. 2 1r (m·tir deformation o f rock ca lled plJIlfj!. .... hieh is irreversible the com pressional stress ISbeyond the clastic limi t) (Fi gure: 14-1f.h ), o r 3 )fru cturil1g. •here the pla cnc limu is exectc-ded and the rock break s into piect's (the pieces ca n he e'ltremcly la~I:! ) (Figure 14- 16c). Basalt has an averag e compressive rup ture or fract ure srength (kg 'm l~ 1(If ap pmximately 2750, q uartzite (20 20 1. nanite ( 14 KU1, slate (14MO l, ma rble (1020). limesto ne (960), ;00 sands tone (740) . Thus. if more than 2 750 kg 1cm2 or rompre-ss i'l n is applied 10 a piece of basalt. it may fracture . Sandstone fractures under far k~s compressionalst ress.
u.e..
>l -
'''' A"
ecn ,k
rllldi n ~
re-
nd
v.
,n y
",
Figure 14-17 31 Hurii'lllllally bedded l..train. b l A gen tly slopmg rnnn"cli rll:. l·) " gl'ml) ,I,lping auuc hnc. dJ" syncline, .: . An ov.. rtum ..d Iilid.
FII/d il/g takes place when horizontally bed ded materia ls are
mmprcvccd. The comp ression re~\Ihs in wa velike undulauons imposed on till' strata . There arc fou r bas ic typ es of folds, A monociinr is a sing le told on horizontnlly bedded materia l. It is like a rounde d ramp ( f igure 14- 17b ), Monoclines arc uvuully asymmetr ical. Archlikc upfolds arc calle d Iinliclilw.I' t fig un- 14- 17c ), Anticlin es typ icall y have 3 con\~x upwa rd told with the u ldesl TOll s in the core or center. The beds of sedimen tary strata d ip in opposite directions alia)' from the central ax is " I" the anticli ne . Th e do wnward eou rncrpurt of all unuclinc is a svncline (a nuughlikc do wnfold) (Figu re 14- 17d I. Syn c lines h:1VC a co ncave dow nward fold Ihal typically has the yo ungest rocks in the center. A syncline is a fold in which the scdimcuuiry beds dip inward from both sides towa rd the :lxis. forming a sy ncli nal va lley.
:u lIid incs and syncl ines ca n he sym llldrlcJ I or asym metr i. ral. They CJn also plung.: hc lnw Ihe surface. cr...ating a plunging an ticline " r sync line. SUlIldi m<.'s Ihe compressive foret'S arc so great thai Ihe sedime ntary b..-ds arc u\ ·..rtu rm·J on top of ooc an otht'T U:igure 14- l7el . Anti c tin...s and syl1-
c hucs arc con unuously weathered. g iving rise III a var iety o f land l(1J111S such as hog backs, CIC . Exam ple s of folde d strata in remotely St'l1sl'd images arc found in the sec tio n on "L an dforms D.. . vclopcd 011 Folded Strata."
Rock frac tures may he div ided into II-H1 categor ies : joi nts ami tauns. .>\ joil/ I is a crack in rock along 1-\ hieh the re is no ap prcciublc d isplacement ( i.e.. sideways or vertical mo ver ucn t], A ) imlt i'\ n crack aloug wh ich d isp lace ment has occurred . b mlt ing invo lves the mo vement o f mass ive b loc ks o f rock and u,ually ge nerates earthquakes. It is only the fracturc s a long which rock bodie s actually move relat ive to one anot her that we call / '/IIIt.I . This d is placement ca n he local m nat ure or occur for hund reds of ki lometers, In ce l1Jin inSlanl'es . lht' d irt' clion and amount o fm o\"cmem (d isp lace me nt) all'"!? Iht'Se lillt'(//1/t'lJl.I can he measurl'd from pas"i\ e le.g., \\'on -In and Charusiri. 20t)J : Fernandes Oa Sil\a, 2(05) ;md acli\ (" r('motl'l) s.:nscd data l i looper et al .. 2no} \.
(, II A rn~ R
524
14
Remote Sens ing of Soli s, Minerals, and Geomorphology
FauJI ~
J.
!\ormal d ir-~li p faull
h. SmkC'-~lI r fault
Figu re 14 -18 a) A normal dip-slip fault, where the hanging " all is displaced (Will the !'lIutw, IIL Note Ihal th... ang le ofthe fault pla ne is called the dip and thatthe fault line trends aero's lite terrain in a certam azimuth direction ca lled the strike . The dbplaccmcm C3U>Oi a [ault scarp, b ) ,\ strike-slip fault. c) An obliq ue-slip fa ult.
There are three major types o f displ ace ment in fauns. inc lud ing: dip-slip, strike-slip, and oblique-slip . as shown in Figure 14-18. Displ acement occ urring up or down the faultplane walls prod uces a dip-slip fau lt (Fig ure 14-1Ka ). lfthe displacement OCCIIN parallel with the faunline . a strike-shp fault is created ( Figure 14. l!ib). Displacement up and down a nd along the fau lt line creates a hybrid nl>liq/le-.~ lip fault {Figu re 14-1Xc ). The diagra m also highlights ~\ eral param-
ctcrs that lIlay he idennflcd using a cornhination of field work and remote sensor data. Th... fi lllit scarp and the fa~11 line may be identi fiable. They may trend in a certain direclion on the terrain , called a stri ke dircctinn. The angle lhat!be surface i ~ tilted Irom a horizontal plane is the dip ang/rl81 11 i ~ me asured dow nwa rd from a horizon ta l plane and ranges between no and \,1(1" . The dip direction to" to 359"1 is rnasured orthogonal to thc ~I ri "c direction. There arc several
:.tology
525
'ar:w 14-1.
Draina ge morphometric parameters ladapl:cdhum Reddy C1 al., ~()()" ).
I Morphometric parameter
I
Algorithm
Drainag e den sity (D)
"
L:C,
JJd =
R• •
Totallength ILl of /I stream channels in a dramag... basin divided by the surfucc area (A I of the basin.
,. , ..J
v
' "
( .\'~ + I)
B. - h",... - h ...,,, R~e:Une,;s
Description
l{
Maximum vertical distance between
Inc lowest and
highe!.l points of a sub-basin. Product o f the hasin relief and its drainage density.
number ( R. )
F = ~
•
A
Texture ratio (n
Rallo between the tota l number of sueams and ltu: area of the basin. Rat io between the total number of first-o rder streams ;md perimeter ofthe basin.
Ratio between till: basin area and the square of Ille basin length.
Ratio be tween th... diamete r of thl: circle ha ving the same area (as lhat of the ha~inl and the maximum length nfthe: basm.
typeso f dip-slip faults. TII\:s.... are dis cu ssed in the sec tio n on "Fault-Controlled Landform s."
Drainage Morphometry and Patterns
led
held
River and stream basin sur face d rainage pur.uucwrs may he measu red us ing remote sensor data . Sornc {I f the most IKni ly used morphometric: parameters arc summarize d in fable 14-1 (Red dy et a., 2004). \\'e wi ll foc us here prim arily on drainage densitv. which i~ de fined as the tote! length of /I srea m cha nnels in a dra inage basi n d iv ided by the surface area of the basin, and how it relates 10 te xture vis ible in remote se nsor data. We will then loo k a t the ch..rac tcnstic of various dra inage pan....m s.
treephe ( M.
Dra i n a~('
ngcs nea-
The permeability o f a soi l o r rock (i.c .. how easi ly wa ter passes through the material} has a grc.u U<':
-cral
Denclry a nd Tt>lture
runoff Whcre pcrmcnhilitj- is low and runo ff is high. many guthes typic ally form . Conversel y. when permeability is high and runoffis low. m uch ofthe water infi ltrates into the gw uml and (I large r sur face area is req uired to pro vide suffi cic nt runoff for the creatio n and maintenance of a c han nel uributary ). Wea k. relatively impenncublc clays and shales produce the highest dr ninagc de nsi ty. Regions wit h extn,'ll1l,' ly hig h d ra i ll
nl.\ I'H~R
526
14'
has m..derate tril'o lll:lr) sp, u:ing and de nsity. It is prod u,..:.:J by moderate runotf from relatively perm eable soils \ JT bedrock.
Thin beds of sands tone can produce such a texture. A pattern hJS a IO\.~ dra inage de nsity ,\ uh \\ iddy spaced channels. It suggests the prese nce of hard. resistant rock types (e.g.. gra nite, gne iss) and/or \C'l) permeable SIJils. Sudllllaicr ials typic ally absorb a great de al of Will cr. and there is little runoff ,\ Iso. the bedrock may be fractun.. d. clltlrI't'-leXlItN:'d d rainage
D r a i n a ~l'
Pat tern
The drainage pattern developed thro ugh tim e on a landscape provides clues about the bedrock lithology [c.g.• igneous.
sedimentary, metamorphic]. lope'graph) (slope. aspecn. the texture of the soil and \IT bedrock ma terials, the permeability of the soil (h(1\O..... ell water pe rco lates through ill , and the type of land form prescru (c.g. . alluvial. eolian. glacial). \\'hi le ill vitu obsl'I"\3tions arc essential, physical scientists often esc the syn.\plic bird's-cye view provided by remote "t'nsing to appreciate a regi'llla l drainage- pattern. The-refore. it is important to be able to recognize the maj or d rainage palterns present in remote se nsor data. Somcumcs there may he a variety of drainage patterns w ith in a watershed or -egion. in whic h case it is called a mnt'd pa ltern. whene ver poss ible. it is better to slmtif) the m ixed patlern into multiple areas wi th unique dra inage pa tterns. II lso . it is importantto remember Ihat the drai nage palter n may be com posed u f wet and dry chan nels. especially in arid e nv iwn ments. Il endrilie : The mosl comlilon I)p<: o f drainage pattern is dend r;t i(' ( Figure 14· I')aj. It is characler i7t'd hy a treel ike or ft"mh ke palll.'m with orand ll.'s lhat interst:d pr ima rily at acu te ang les (i.e .. < Q(F ), Th ere ;Ire Ie'" abrupl bends in the , Irea m c!wnnL'!s. lk ndritil: dra inag.: pattt"m s ar.: tkw!f'l'cd by nm dotll h':'ld\!.a rd eH" ion of ins<:qu.:nl slr.:>lms on roc ks o f un iflmll rcsistanc.: wilh liu l... or no stru':lUra l COlllwl ca uscd hy fo lding or tilult ing. It i~ o ti.:n found o n l a n d t"'nn ~ composed of rcllltiv ...ly' hl'llltJ~ ...ncous. hor i:wll tally bcJd.:d SCJilll"'11I,Hy w d . (e.g" "hale). gl,ll' ial till (e.g., lo.:ss). vokanil' tull on sandy .:n:hla l pl ains, nn tidal marshes (Fi gure 1-414a ). •'r on g laciall::J out wash plai ns. l'inn:lIl': A pinmlle dr-linage palt.:nl is a \ ariat in n oft h.: (I.:n<.Iritic pat t...m where the slr.:ams or gullies hav.: a kalherli k.: branc hing paU"m th"t typ ica lly imersecls at acute :mgks. Th is pau"m indlciltes that the kind form has a high silt co nI.:nt usually consisting of lo.:ss. si lty a llu\i um. or \':f)' soli erodible s.:dimemaf)· materia ls.
Remote Sen sing of Soi ls , Minerals , and Geomorphology
Trdlis : Th... trellis drainage pattern is a modified uendritic pattern that resembles a \ inc on a garden trellis. It o!Ull " , hillits straig ht. pa ralle l pri mary tribu taries and shoncr secondaf) tribut aries that joi n the large r branc hes at rigfu ang les. This drainage puncrn oneo indica tes that the t>.,'\ln:(\ structure is tihcd. folded, l,r fault c<.I. [I is often found OIl inlcrbcddcd sedimentary rocks. Trellis dra inage is esp«iaIl:common in areas o f folded sl'(limentaf) beds of diffenfIE resistance such a.. the I(idg.... and Valley topography oftM Appalachian M ountains from S.:w York to Alabama, t"l as"lll.:iate-d wuh the hc>gt'lad :s of the Uinta Mountains oi L tah (Figure 14-19bl. The prima ry parallel channels folm the I.'S., resistant be ds . The shorter tributaries flow down tllc sides of the more resistan t uptu rned beds. 1{ N:"l a n ~u l a r : II rectangular dra inage palt.:m also exhibits! treelik e p,ttlt'm: \l<"..C\"'T. the ma in channels have ll'IOI't abrupt bends. Stre ams often join at approximately riglt angles, [I dc vclop... in areas " here joints or faults haw' deleloped in the bedrock. R l'~·ta n !(ul ar drainage is PI\.'S<.'nt wbere the bedrock is fractured. jointed.•tr foliated and i... Ii\;e1~ 10 occur on met amorphic ..tare. ,,('hi..t. or gnt'iss. It can al
Par:llit'l: A p:mt llc l d ra in:l!:!e patte rn co nsisls \,f tributaries th
527
GeOl09Y
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• se\"-
structurally controlled
;
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lrock d 0"
:iall y eriog ,f the 3. or
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ns of
I ndgc
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'0
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ngtu
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'e I ~-
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rand IminiJua l
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tancs tones • Par -
iform
roc" . 1 arc
lnage
.ion This is referred 10 as cen tripetal radial draina ge , In this ease. the huh of the 1\ hee l is loVo er than the qm kcs. A cinde r tone volcano may have l'clllrifugal rad ia l drainage \111 the exterior sides of the volcano and centripetal mdinl drai nage 1n the interior wa lls lll"thl' crater I Figure 14-2Vn l.
·W l11
prof netaway f
case. okes. arne
\n n ul:1r: An annular dra inage pattern is similar 10 the rad ial paucru e xcept thur ring.l ikl' tributari es inte rcept radia l streams .11 right an gles ( Rasher and v.,..ea vc r, 19( 0 ). These delelop when stream cours es a
)r o n
IT
llichu tumiv: r\ d ic hot omic drain age patte rn may be foun d alluvial fans or on alluvial dehas at the mo uth o f strcams « nverx ( Figure 14·2 1a ). The water and suspe nded sediment esually enter the alluvia l fan or deltaic area through a s ing.le dlannd _The 1111\\ is then red istribut ed througho ut the fa ll or
illI
area s
pres-
b.
Rgure 14-19 a) Top- Hypothcucal dendritic dramagc pattern. Bouom: Vc nil·;t1 aerial photograph of a ocm1ritic drainage pattern found Oil r i",uli r.; urth Bay ufthe IludSllJl River National Estuarin... Rcw,u",h Reserve in ," c" York. t-) lrelhs dnu nagc pattern found 011 lhl' hogbac k mlgl"s on the edge (If the Uinta Moumams in Utah (I ands,n I\ISS dua I c I Srructumlly controlled rectangular draina ge pattern of the Colorado Rivcr in the Grand Canyou (Thcma nc \ l .q'!x:r huml 4 data, courtesy Spa ce Imaging, lnc.).
dcha via a number (lfdi.l'lrihular!c _\', O n an alluvial fan, the coars e malcrillls (cobhlc s, gra ve l. etc.I arc deposited al the ape x 01" the fall while tbc smaller and lighter minera ls arc dcposucd toward the terminus o f th e tan In certain instances. the dichotomic drainage patte rn may co mpletely disappear ucur the te rm inus of'thc fan. i.c., the material is so porous rhmallofrbc wate r percola tes underground. Simi lar dichouunic d istributaries Ill'-l)" form un rive r deltas ( c.g.. the \-1ississi ppi aml N ile) . The dichotom ic d rainage patte r ns can only for m on ddw s when the sus pe nded sediment is very fine-gra ine d ,Il1U CJn be transported great dis tances. Knlid l'o : A braide d stream patte rn may de velop on t100dpla in" whe re strea m \ch>ei t) is not s uffi cient 10 move the suspended scdrmc mlood dm, nctre am. The re su lt is the dcposruon of ~u spc:ndeJ mate rial in inte rtwin ed channel.. that appear much like braid ed hair. For example . consider the braided stream p,IlII'm found at the mouth of the Betsiboka
528
(" II A1'1 t:I~
14
Remote Sens ing of Soils, Minerals, and Geomorphology
~J~ ---. "-:. +--...-::::.:-.
'lJ\'
Rad ia l and Cen tripet al
<. Figu re 14 ·20 81 SIR.{:" radar image of paraljcl an d rad ial drainage pauerns found on I~ volcanjc cone in \\ estern MallL HI (('OUT1ts) \.-,,,-, lei Propulsion Lahor~IOf) I. bl Lo .....ot>li'lU<: ae rial phol ugrap b c f Diam ond Head Crater on Oah u.. Ill. revealing boIh n'furiJll.1.a1 interior dra inage panerns. c) Space Shut1k ph{ltograph o f l~ a nnular d ram age pattern on the M anicoua gan Crm on the Canadian Shield in Quebec Province.Ca nada lcourtes~ I'\AS,\ Johnson Space C..-mer: STSI J(l'J..48..] 13'1).
radial_
River in Madaguscur ( Figure 14..2 1b ). The sands a nd grave ls that arc sys tem atic all y sorte d and deposi ted in a braid ed stream drainage netwo rk n11lY event ually have s igniflcmu ec onomic importance. ()t'ran~ l'd : A de ranged drai nage pancrn exhibits streams that wand er in d isorder in swamps and among water bod ies [n ot show n). It is mainly fo und on very young landsca pes that have al most le veltopog raphy and a h igh water tab le. It can occ ur in young glaci al ti ll p lains. moraines. low co as tal plains. and floodplains. Us uall y swa mps. ma rshes . bogs. a nd ta kes or pond s are prese nt.
A nas lo mn lic : An anasto motic d rainage pauem ma y be found 011 mature floodpla ins where there is ample hornogcncous sed iment a nd red uced stream fln w or vclocuy, Basical ly, the hydro logic sys te m docs not have su ffic ien t energy 10 rem ove the sedime nt from the area. Th e major stream
c hann el adjusts 10 the decrease in ene rgy by deposi ting Its sediment 1n;\I! and incr ea sing the length ofrhe stream channet. Typi ca l d iagn' lslic features include mcund cnng streams and re mnan t meander scars and/or oxbow lakes such a~ those fo und on the Missi ssippi Ri\ er ( Figure 1-l-2I c). S ink ho le (d nli ne) : A sinkho le dra inage pan crn consise cf isolated lakes o r po nd s lhat d,) nOI appear to he connected ~ any sys tem atic surface dra inag e. If sh..m stream Sl.1Jrnenu are present, Ihey ofte n end ab ruptly or disappear into karst topog raph y sinkholes or d~pTt:ssions. Tb rs dra inage p;tll:m dev elo ps o n sedi mentary li mestone (('aCO) where the sinkho les and dep ressions hav e formed by c hemical dissoluliOll (Tre fil and 1Ill/e n. I'N5 ). Somenmcs the subterranea n drainage network that is nu t visible in the imagery emerges to torm sprin gs lind lakes. An example ofsinkhole t('lp<)g:raph~ in Flor ida is shown in the section on karst to pography.
y
529
Geomo rp ho lo gy
meand...ring
'j-t-
nver saml bare
•
b.
roller
tits
F'9ure 14·21 a) .-\ST ER image ofan d ichotomic drainage pcuern onan a lh.
Geomorphology
haneams h
:IS
Is o f d by crus ~arsl
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lion
am-
". phy
c.
A kmdtiJrlI/ is a thrce- dimensi onu l fea ture on the Earth's surface formed by natural processes. Typicallandfo rms include volcanoes. plateaus. folded mountain ranges. stream cha nneb, etc . (jl'(J/IWlp"oloK~' is the science tha t studies the enure and history of la ndforms and the processes of weathering. erosio n. and depovitinn that crea ted them I H.)CI,.'t. ..."1 !!.. ::!OO51. At one lime il was know n a.. the science of phvsi()gruphy. T he study of geo morp hology involves an appreciation fo r Ih t' majo r pn.x:e.\.\t',~ at work thai constantly erode or d..'P'''it materials on the Earth's crus t. incl uding running water (fluvial). glacial ice (glacial I. wind teohanj. groun dwater. and wind-driven wate r waves. Geoillgists. phys ical geographers. lind other scie ntists routinely usc the synoptic
view associate d with remotely Sl'IISl'U data 10 identify and imem rct geo morp hic feat ures on the Furth's surtace. fn fact. idcruifyiug, understanding . and upprccluting the nature of landforms present on remotely sensed imllgl'fy is one of the great benefits 01' remote sl'nsing science. One should lake time to appr eciarc the treme ndous beauty and var iety (If landfor ms o n the Earth and h" w ecosystems associated with rhc \ anou, landfo rms interact .... ith one a nother. A wo rd o f caulion is in order. In th c lat... nineteenth and early twcmic th century . principks ofland form evolution were put forth such that any current landform could be interpreted as I'>t:ing in
530
C II ,\ I""H R
14
direct sequence of landforms tha t ca n be recognized as deve loping acco rding \0 a pa rticula r in variahle pattern (Wals h et a l.• 1998 ; Jam es. 200f» Fonuna re ly, ma ny landforms do exhi bit observable. r...peatable aunbu tcs such as size, shape , height . three-d ime ns iona l topogra phy. composition . slope. aspect. 1.'11.'. These attributes may he used to c1a~si fy landforms into the fo llowin g class...s:
ignc\\us land fo rms Iand forrns developed on hor izontal strata land fo rms dev elo ped o n folded strata fauh-cor urolle d land forms Iluviulland forms
Rem ole sensing of Soils, Minerals, a nd Geo morphology
sion . ,\ Isu , imagery obtained at a relatively low Sun angle o ften enhance s the an alyst's ability to id enti fy landtorrre. Finall y. one has 10 he VCl')' careful whe n interpreti ng images in the No rthe rn Ilcmispherc because shadows in images fall towar d the north. a\\ 3Y fro m the \ ie.... er, Therefore. e\peri· enccd ima ge analysts often rotate the Nort hern Hemisphere images so that so uth is towa rd tho: to p 10 pre vent pseudoscopic illu sion fro m taking place (i.c ., co n fusing mounne rid ges with valleys). Some of the illustratio ns in this ehaplCl" are oriented in thi s ma nner to facilitate interp retat ion,
It is beyond the scope of this ch apter to pro vide examples of all the possible geomorphic landscape s prese nt on the SUIface of the Earth. Therefo re. Hilly representative examples of so me o f the mo st impo rtant land fo rms are presented. Pkast refer to boo ks on geomo rphic ana lysis from aerial platforms such as Shelton ( 19(10). Short and Blair (19'-)9), Rasher and Weaver ( 1990), Strain a nd Engle ( 1993 ). uno Way and Everell (1997),
kars t lan dforms
Ign eous Landforms shor el ine land forms glac ial land forms eolian land forms.
The Soi l Conservauon Sc.'TVlcC produced a n excellent manual that summarized the major land forms and ho .... they ap pe:n on ae rial photograph y (Rashe r and Wea ver. ItNil ). Several o f thei r examples are used in this chapter. Short and Blair ( 1999) provided a tho roug h re view o f ho.... to pe rform geomorphological analys is from space especially for obtaining informuuon abou t large. regional landfo rms . T hey pro\ ide examples from arou nd the wo rld . One m ight ask. What is the idealtype of remote sensor data and'or image pr esen tatio n format to study. ap prec iate. and class ify the Earth's landforms? First. no sing le sensor is idea l for the stu dy of al l lnndt orms. Ae rial photograp hy may be ide al for studyi ng land forms in the re latively clo ud-frce arid wes tern United States, .... hi le radar data may be ide al lor studying landforms in cloud-shrouded enviro nments (e.g.. Lu et al.. ::!nU4 j. Many a nalysts ca n e xtract la ndform info rmat ion by \ ie\\ ing a single ae rial photog rap h or imag e. Howe ver, many scientists prefer to study lanJ fo nns while viewing the te rra in in a three-di me nsional presentation us ing I ) stereoscopic pho tograph y or imager} (e.g.. Baldi et al., ~OO5 ). 2) drap ing a monosco pic s ingle image o ver a digi ta l e levation model and then man ipu lating the o bse rve r 's \ ic.... ~ ing posi tio n to enhance topograp hy. and/or 3) ob taining obliq ue imagery that generally en hances the thi rd dimcn -
The Earth's upper mant le is pa rtly molten. with many minerals in it tha t were force d dee p by tectonic forces and eventual ly melted . tgncoes rocks arc produced from this molten fluid magm a. If the magma is e xtruded o nto the Earth's surface . extrusive igneous (vo lca nic ) rock is created. If the mag ma is ex truded into some subs urface portion of the Earth's crust, intrusive igneous roc k is formcd.Hthc molten lava Flo ws or is expl oded OUI of a central vent and produces a mound o r cone-shaped fea ture. we have a v olcano.
Cinder ('fl/lC' vo lcanoes arc built ent irely of pyrocl astic mate-rials that are ejected into the air and fall to Earth nearby,
Their accumulation ev entually bu ilds rhc cone. For example. conside r o ne ofrhc Menan Bulle volcanic craters ( Figure 1-1· 12). It .... a s created .... hen a dike of magma int ruded into a sha llow aquifer. Th e water in the aq uife r turned to steam and explosively fra gmented the basalt ic ma gm a into volcanic g las!>like pani cles called IUfr , The volcano was built up layCl by layer, hy ae rial deposi ts o f tuff and larger pyroclasrk (bom b ) mate rial. Th e two Menan Run e volcanoes also extruded lava onto the surface covering a larg e portion of eas tern Idaho. Diamond Head C rater on Oahu, I II. is also a turf co ne volcano.
un..,
do mC' (.~hidd) ,v/nJIIU('j arc crea ted when the Ian po urs ou t on to the: land scape. Generally this results in more gently slopin g volcanoes depend ing upon Lhe: viscosity of the lava the mor e high ly fluid the lavarhe mo re gentle the slope ; the more viscous the lava . lhe stee pe r the slope
u.e..
Go<
09'
lin (Ingle rdforms. ~ images. ages lall . experi-
53 1
Seomorpho logV
Menan Butte Ctndcr Cnnc vulca nn in Id ah o
nisphcre pseudo-
rounrain I chapte r n
n ples of the surn plcs of . Please
arforms he r and
rd Eve r-
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: mateeearby ample.
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re 14·22 Panchromatic ~t<;:T'l.-opair o f the wuth~'11l Menan Butte cinder COlle volca no in It1.Ihu obtamcd on J une ::-1. 1'>60. It is une o f the \\(lf ld's largest tu fTcone volca noes . wilh a volume ofOJl7 mil (U.~O c ubrc " m ') . The lu rf l~ made of volcanjc glass Ihal has teen altered b) 11M: adJ ition o f \\ 01l<:r. The cone is laic Pleistocene i n age. The ~lcnan il l/lie vo lcano al,;o c.\trudcd lav a on the surface 10 the west tbon om nf lhe photographs ) for many kilometers. There ISsllnghm (In Henr) 's f ork in the leli photograph as it 11\,,,, s into the Snake River Note the radial and parallel drainage on the l1.mks ofil le crater and the eL"'lltri[k1al drainage in the inter ior of the CIlIK'f.
uccd). Common extrusive rock s arc basalt, andesite, dacite, and rhyolne. Havalt is the most widely d istributed .olcanic roc k. It is also the mo st common rock on the Earth 's erfacc . It flows out from volcanic vents over other rock in pearlobes or thin sh eets ( L. t1 et al.. 2(l t~ J . II ca n trav el hundreds ufnnlc s. It is fine-grained. black, rich in silica uud thc erromag ncsian minerals . Basah normally ap pear's dark o n pmchrornaric li lm because it contains feldspar. hornblende . lnd miens. Dac ite and rhyolite appear in light tones on panchromatic images.
m a nd
Jeanie 1 layer
stasuc I a lso ion of
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lava more
ity of lemlc
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The Shutt le SIR-Cl X·$A R rada r image in Color Plate 1~ -2a reveal seve ra l componc ms o f the Kilauea shield vo lr nno located ou Hawa ii. T he massive volcano conti nues ro he erened by the ext rusion O( I WO types of lava : a'u is extremely rough and sp iny and w ill quick ly lear shot' s when walking OIl it, and ! /(, 'j",*,!wt' is a I\I[)C Y lava rhur look s like burned pancake bailer. The vo lcano is enlarged by the extrus ion of lava onto the surface. Numerous individualflows are easily seen in the three-dimensiona l radur-pcrspec nvc vie w in Colo r PI:lIe 1 ~· 2 b . Noll' especia lly rhc dark mate rials from the Kupaiauah a cra rer Kilauea ha s been crupnng almo...l constan tly since 19R3,
Figure 14-23 A threc-drmcnsional per-pecnve view of Isla lsabcla o r the {i;llapagvs !>Iauds. TIlis is a Space Shul!lc SIIot _1'/ X·SAI{ im;lge draped over a digital elevation mod e l. [{"ugh au la vu !lows produce a bright radarreturn on me srde..fthe dome volcano. Ash deposits an,1 relatively .' 11I<.0Ih11
I,-Ia lsa bela j, une of the G alapagos Istands loc ated off the coast o f Ecuador. South Am erica, It is a lso an ac tive lava dome (s hie ld) volcano. rigure 1 ~ - 2 3 depicts a Spa ce
" I,.'S t
CII AI"IER
532
14
Remote Sensing of Soils. Mineral s. and Geomorphology
I
~ Io u nl
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,
St. Helens
u. High oblique pho tog raph.
b. Stcrcopair.
Figu re 14-24 a ) High-oblique pl1\lhlgraph o r MUUIl! 51, Itcicns crupung nil May 1S. I <) ~O ( C" lUt c ~ > "f U .S. (ico]"gic;.tl Surv<;y). h) USGS lligh A lti tude' I' holography' (HA l') stcreopatr of Mount '-;1 I k I L'n ~ in Washinghln (>11 August fl . t cx I (I I,S. Geological SUf\e)' photos I (l'J ·~-l . 1l 5) _ The acti ve 1a\:1 dome in the center ofthc C'Hn..: i~ visible. Steam is rising fruTn wi thin the crater. A ,diml'lll cho ked radial dminage paucm has developed. North IS tothe lett. Please re fer In ('OIOT Pl.ne 14-...
Shunle S IR-C/ X-SA R image o r Isla lsabcla dra ped ove r a d igital elevation model. The brigh t are as arc very rou gh ]:1 ' a fl ows.
Lava flows on the wcstdchl Volcuno, Alas ka, wcrc, map ped using radar and Landsat Thematic Mapper imagery [ Lu er al.. 200"). Baldi ct al. {200S ) used a...rial photography and phorogra mmctry to map geo morphic changes on the Stromboli volcano in Italy, Thermal infrared AVHRR data were usc-d to map hot spots on .'viI. Etna and Strombo li volcanoes ( Pergola et at , 200-1).
Composite cone or s tru to volcanoes are created from both pyrocl astic mal...'r ials and extrud ed lava . The world 's most
impressivl.' volcanoes Me C11ll1fK'sitc cones. For example, :\1(IUl1t St. l ic k-us in w ashin gton (R,311O ft: 2,548 m) is J composite cone volcano ( Figure 14-24 and Co lor Plate 14· 31. lr erupted on May IX. [IJXO, at X:32 u.m. Pacific time. .l. se ries of moderate-to- severe ea rthquakes preceded the eruprion, sending th... north side ofrhe mountain cascading downwurd toward Spirit Lake. This avalanc he. the largest eHI observed in the wes tern Hemisphere. weakened the magma chambers .... uhm the volcano. causing a northwa rd lateral and vertica l explosion that destroyed over 270 m i ~ (7.000 km ~) of forest in live seconds and sent a billowing cloud of ash and smoke 7U.ono n (.21.0CIO m I into the atmosphere. A pumice plain \\a_~ produced. cons isting of'v olcanic mud. ash. and debris that buried the original Toutle River Valley to a
~I o gy
533
~m o rp ho logy
,\ I n u n l Taranaki.
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Z t'a la nd
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'ialional Pari.
Mgure 14-25 ASlfR image of ' lounl Taranaki tin :'>It" Zealand's North Island ooraincd on May 27. 2001. TIns cOI11 JlO'>l te cone volcano is madl' of amk,i lc lava and a mixture ofsolid pyroclastic rocks (tcphn ),and ash.Tbc unique shape ofthe Egmont National Park resuu, frum Il' pnuccuon in l ~~l. whic h specified thai a tllfeCo,l reserve would extend in a 'H ' km radius from the summit of ~ h'ul1l Taranaki. ,\ series of montane habnats oc cur in procession from the pasture farmlands up the Flanks of the votcanc-cfrom ram forest, ttl sbr ubs, to atpme. and fi nally snow cover (eourt."~y of NASA etSFClMETIE RSDAO JAROS and U,S} h J'dll ASTER Science Team}, depth (If 1.000 Ii (WIl m) . The stereoscopic phot ograph y obtained on All~ust 6, I\)XI , OIlie r the eruption re vealed another lava dome {Ie \'dopi ng in the ce nter (If the cra ter.
'Set s trvcy 111111
pte. h a 4A up-
s n. kr
." tal 00 f
xtouru Turanaki in l-gmont National Park on New Zeala nd's North Island is a composite cone volcano made o f andesi te lava (F igure 14·25 ), The fOcb arc a mixture of so lid p}rnclastic rocks lt e:phra l, a sh c.~ . and lava Flows. which lack cohe sion and arc easil y carved by eros io n. 1vloun t Ta ranaki stands at 251 X m. The volca no ~ga n fnm li ng 711,OOO yea rs ago. a nd las t e rupte d in 1755. Intrusive igneous rock i ~ for med when the molten magm a cools and c!") stJl1 ilt: s .... ithin tho: Earth's crust. The material lying abov e this pluto nic roc k may eventually he eroded. Large igneous intrusive ruc k hlluil's. or nll/hl//ith." oft en fonn the foundauon fo r entire mo unta in systems such as the: Sierra Nev ada in the weste rn L'nilcd Slates or the Andes In South America . Sma ller u{lme-sh'lped intrusive flick bod ies arc c a iled l
ous rock . rich in q uartz and fe ldspa r hut poo r in the fe rroma gnesia n ( iron and magnes ium I minerals. G ran ite usuall y ap pears in light tones o n panch rom atic image!")', whereas diaba se an d gabbro are dark. Granite cools for an exceptiona lly long time unde rgroun d : therefo re . it has large crystals that a rc visible 10 the naked eye. Whe:n granite is exposed at the sur face, ex fofiancn may ta ke place where co ncent r ic shells o f rock material break o JT du e 10 chcmicu l or thermal wealhering and from the release o f interna l stress w hen ovcrburdcn is removed. For exa mple, Figure 14-26a depicts Stone Muuntu in in Ge orgia, which is a rel atively sma ll intrusive stn c-k. It is approximately 360 m h igh and I I km in c ircumfcrcncc. An imagc the top of the do me revea ls linea r slr i at jon~ uuu radiate a..... ;L)' from the apex ( Figure 14-:::6b). Anot her excelle nt example is the Bra ndbcrg Massif in Namibia ( Figu re 1 ~- 2 7 ). Th is massiv e granite intrus ion is exposed at the surface and CU \eTS approximately 650 sq. km (25U sq. nu) an d rises 2573 r u(I ,h m il above the des ert .
or
Somcurncs the tess rcsisram ma terial su rro undi ng the intru -
sive volcanic neck ((IT plug) of a volcano erodes, exposing The mos t common intrusive (plu tonic ] rocks incl ude granite. diorite, diabase. and gabbro. Granite: is a lighr -colorcd igne-
the more res istan t vo lcanic neck materials. For exam ple ,
Dcvil's To.... e r in Wy(lming is an intrusive volca nic nec k
• 534
14'
Remote Sensi ng of Soils, Mine rals , and Geomorp hology
Stone Mountain, C;,\
,
b. Figure 14 · 26 al Pan<'hmmalic aerial pltoloparh of Slone Mountain. 00\. II 1$ a gran ite exfol iation dum e (re3100 oy intrusive magma!iOiidif) ing .Ill.m:.al depth. It is lxli.:\<-..1 that more than 10.000 ft. ofk-,;s n.." i5l.;m l material "iUO cr ..>lk...J to expose the inl1U'il\'crocl l>' Large-scale photograph of the 1111' o f Stone \ loll nl3;n . I'\l'le the gllndnla. facI lity. linear striations in tbe rock, and thc:-p.nIld and annular dr. nnagc pattern pr..·"c nt.
(f-'igure 1-1-·21\) . Occasiona lly the mag ma is ex truded away [Will the main body via cracks and fissu res in the Earth 's crust 10 fo rm d ikes and s ills, Later the mate ria l a bove these dikes and l>ills may be eroded. e xpo sing wall-like res!..tan t Jikl-".
Brandbcrg :\Iassif. Xamibla, Africa
If the g ranite at the surf ace is largely unfr acrur..-d. a dendri t ic drainage pa tte rn will res ult on the domelike h ills. Co nvers ely, ifthe gra nite has been exte nsively fractured , this can result in a rec tangular nr I rd1i ~ dra inage pattern.
Landforms Developed on Horizontal Strata
Many landforms haw de veloped o n tlar, hor i70ntally layered strata. A layer is co ns idered to be horizonta l when the dip (inc linat ion from i1 hor izonta l plane) ofthe strata has not sign ili cam ly ,, 11~(1~1I the developmen t of the topograph y. The type o f roc". its crud ubility, amount of prec ipitat ion ava ilable to the regio n. and loca l stream grad ient control landform dc\ elopmcru. Hori zontally bedded sedime ntary rocks arc formed by ce men ting the loose pan icles produ ced by weat hering . T he most co mmon ce menti ng agen ts an: quartz. calcite, and iron oxide. ;<, lost sed ime nts scutc in wa ter in re lati vely horizontal layers called .' /n ll,l. Sedime nts can collect in slo .... -moving streams. in swamps. lakes. a nd shallow seas. Se dime nts als o collect in oc eans. where they are deposited on contmenta l shelves o r Ilood down submarine cany uns and nrc depo site d.
Figu re 14-27 The Ilr;uult-.: rg \ lassir in Namibia is a dome-shaped grllllltc intrusion cove ring 650 sq. km (150 sq. mit It n ...:s 151.' III ( 1,(, mi) above the desert. Thisimage was recorded hy the Landsat 7 ET\ l+ on Sq,temb.:r In, 2lN1l lcuuncsy uf t"AS .\ l.
The 11" w s ti"'t dcros i t t.·mu~ sand. then finer clays a nd slits. dcpcndmg upon grain SiIC. The most common rock outcrop formations on the coruincms arc co m posed o f mudstone.
537
Geomo rp ho lo gy
.thcrstone T he
Sh~lc . ~l\at,' ·
,
end) '1 the
o.
--
Limestone - Kaibab - TOl'(l\\e:lp Sand- tone - CIl•ro nino Lime~lone
G ~(l l n ~ic
C ross-section or the G ra nd Ca nyo n in Arizona
V~
Shi,...ru"'I'
M,,,,,,k,'r' ik"7: --
nd a I the
j hy ired
m a-
'4-
Li 1Tll'~l
oJ" lent 'c ry
- vtua v
S ha le - Hn ghl Ange l Sandstone - Tapc ais,
eof
he r , of
.......
t he j cs
......01 11
e.
'm
epe
;he jO(
So uth
Rim
"" ill ru
,.
n· , oJ
ic
•
d
b. Stcrropair o f the Gram ! (" ,In)OI\. Figure 14·29 a ) Geulogie eruss-),,;eliun uf the Gra nd Ca nyon in Arizona . h I Panch ro matic slcreupai r of the 0 1',111<1 Canyon . Viewi ng and cam ping fac ilities an.' located 1I1l 1he sandston e cap rock ti l' the <. 'ue uninu Plateau on the Sou th RIm.! he Imag es were rotated so (hilt :;,'uth is to the Icn to avoid pscudoscopic illusion TIle r"s i.slant sandstone ,mJ Iimcstone f"on M.·C p cliffs. The klo.~ I'l."'ii~t;mt shale is easily eroded, causing more gradual slopes I II form . 1he Iiright A"go:! buue is locat.:J at "rr",
Landforms Developed on Folded Strata
~u i kling) can ev entua lly lilt or fold the honzomal scduncm ary or me tamorphic roc k la ye rs. The fold ed te rra in ma y pr od uce: monocline domes suc h as Aye rs
lJiaYlrophl_,m I mo untain
535
Geo mo rp ho logy
a
,
511Ull It.
d-
( ;"n l,,!!if ( 'n,ss-scctiU II
lel
Talus
45un
'000
b.
I
Tdills
I lsI
hh Jp
"h Tas
FlQure 14-28 a) Panchromatic stcrecpair of the Devil's Towe r. WY, volcanic l1I:d. obtained on September 15, 1953. with SC'IUth al the top. Venleal j
sandstone. sha le, and limestone. Greater water force is required to mow larger pebble-size particles that are d cpo.... ired as conglomerate. Mu.bIU/It' has no vis ible gr ains, being composed of extremely tine sediments deposited on ~ u iet flood plains, in
lakes. o r deep oce ans . Thi ck depo sits of mud stone are present in most deltas, where rive rs en ter still water. Layer. ing occurs in thick m ud deposits becau se the clay panicles. being flat. align themselves horizonta lly, They are usu ally gray to shades of red in co lo r. Th e Miss i<;sippi delt a coma ins mudstone.
ihs,
"p one.
Sandstone has vi sib le grai ns like coarse sugar" up til a lmost 1/12 in. (2 mm ) in diameter. Mo st sandstone is co mposed
often appear in light tone s lIli black-and-white phorogruph y unle ss cove red by dl"SC11 varni sh, in wh ich case they may have dark tones. Sand -tone in ari d a nd semiarid en v iron me nts often produces phJ/ l'
536
( 'II AI ' I EK
14'
d issolv ed. In humid environ me nts. "hen: there is plenty o f .... atcr; we may lind karst topograph y, named after the Karst region 1)1' the former Yugo slavia. created by lime stone d isso lution . Th e undulating 10 hu mm ock y terrain o ften contai ns lin ,-isihk' su rface dra inage pattern but instead may e xhibit oval sink hole.. called dolincs. Limestone in and environ mcms behaves quite diffe rently. Bec au se there is litt le water for divsofuuon. limeston e may Ill' \ cry resista nt to weathe ring. III fact.l iL.e sandstone. it may fon n cap rock s with venical faces when underlain hy less resi stant sedimentary roc k such as sha le.
Shale sed imentary rock is prod uced by the depos ition an d compaction uf !oill and cia) particles. It is relatively impervious to w ate r moving throug h it; ther efore, mor e wa ter is available for surface erosion. In ari d en viron ments the soft imperv ious shale is ~asi l)' eroded. It gen erally doe s not produce as steep r.lopes as sandstone or lim...'Slone. When no ca prock is prese nt, il ...' an y ield a n lgg ed had lands topo graph) consist ing ofa fine-text ured p innate dend ritic dra inag e: pa tte rn \lo irh sharp ridgclince and steepe r slopes. Generally, shale is mo re pliable: Ihan sandstone a nd.therefore. is no t as a ff...-ctc d by gc-clcgic stress. T his results in a greate r numbe r of fine - 10 med ium-te xtured den dritic dra inage patterns . Shale ge n~rally Ol pp..-ars in ligh t tones o n panchromat ic Imagery. The G rand Ca nyo n in An /OIlOl is a good example o f vario us land forms developed I ll! hllri/ o nla lly bc-ddcd sedi me nta ry rock. A di ag ram ofthe tx'dd ing srrucnrrc is found in Figure 14-1 9a. This reg ion comams a nCOl rJy ...-ontinu ous sedimentary r..."Cord ofthe Ea l1h's histlll)', w ith approx imately 5,000 n, ( 1,500 m) of h...·dded hnn lonta l laye rs. all stac ked in S~4 Lle n.:e v. ith th.: (llde sl at th.: boltolll. Oll~ o f thc tl' P laycrs. the Ka ihah linK'stolle. lilrn1l'11 from the re ma ins l,f corals. ~ p()n gcs, and (lth...r Illnrin l" anim als and is nne o f the youngeM in the seq u~ne~ - ahoul 241l milliun yea rs old. AI tli.: hottom Of lhc canyon Ik s lhe Vishnu Sc hist wh ich is abou t 1.7 h illion yea r~ old . so mt' o f the p land 's ollkst me k. Thl' in' P<::lwee n layers o f roc k reveal a turbulent hislOry o f mOlln~ tain uph eaval , l(1va de posits, erosi on hy w ind and wat"",r. and pa st en vironmental e h i\nl!e~ as , k sens we re repl!!c.:d hy rivers, t h~n I;lkc s and ",hall"," inla nd se' lS. finall y. lh~ land was uphlll·d. forming the Colorado Platl"au , Five 10 six m illion years ago . Ihe you n~ Co lor.ldo River began to cut into the by'l:T5 I,f ro.:k. ;snd Ih.: G rand Canyon was o.'T ealed. A pallc hronw lic st.:rco pa ir " I' Ihe ar~a n~ar the So uth Rim of the G rand Ca nyon and Brigh t A ngel sha k hutt e is fou nd in Figurt" 14-24h. The Sou th Rim is com posed o f sandsto ne
Remote Sensing 01 Sal ls , Mine rals, and Geomorp hology
caproc k ",r the Coc onino Platea u and is res istant to lI'cather· mg, forming a tlat dissected plateau (m esa ). Roth sandsrore and limestone form stee p el i 11-.. in ari d envi ronments. Tbe less resis tant sha le is e;bily eroded. c rcOlling more ~('Iltly sloping erod ed surfaces ( Figure 14-2 %). AI"'., present in tilt stc reopair is the crurcnc hcd Colorado River with its deep. \. shaped inne r gorge and rapids. Anothe r example of borizomally bedded strata is found a few hundred mi les do wnstream. Figu re I4- JOa depicts the Colorado as il di sSl."CIS the Sh ivwits Pla teau as recorded tr, the Landsat Thematic Mapper. Th is band 4 ncar-infrared image pro\ ides sig nitkan t det ai l hut not near ly the inllJrtnl. lion co ntent of the color composites found in Color Plate I'" -rab. wh ere the more resi sta nt sandstone caprock and L~ more gc ntly sloping "hale sedimentary rocks are e\'idenl from their vib rant colors. Image ana lysts ort en lind it \et) uscfu! III have information abo ut the elevatio n and slope of an area when intcrprcnng landlonns. Fig ure 14-J Ob is a represcmarnm of USGS d illital elc vauon da ta. Note the higbeJ c' k valiu n of the Shiv w ils Plateau and th... lower elevation of th c Colorado Ri\ cr. An analyt ical shaded relief image of the d igita l ele vation data is shown in Figure 1....3Oc. It provides add itional informat ion of value to the image analyst about the three-di mens io na l na ture of the rerram. Fina lly. the slope ma p (F igu re 1 -l-J Odl ma k l-~ il clear that th c tcrrain with the gre atest slop..: occurs :Idj an'nl to the Co lorado a nd ill; msjor tributa ries . Pla teau s and me sas arc nat . hav ing litt le slope: there fore, they appear dark in the s tope image. Another e xccllcm ex ampk of a pla teau ..ir mes a is found in thc rh ,l n~ I loei Range of no rth cClllni l T hailand aoo ul40 km nonhe:lst o f the ...' ily o f I.om Sak ( Figure 14-3 1). The resis· tOlllt pliltcau ris.:s maj.:stic'llly ahovc the sUTro unding countrysid...• in this Shunk Imag ing Radar C-band BV pnla rizcd Image ,
Somd inK's we enco unter horizolllally bedde d metamorphic T(>"k~ th,ll w\'re rreatt'd hy e~ ptls ll re to he,lt Hlld pressure, Th is 1//<'1<111101])/11.\'/11 ea us~s sandst une to become qUJrtlile. whil:h is wry rcsislalll tll wl"athering a nd can fonn sharp. e rcst~d ridges in ,lll c limates. Simi larly. metamorphosed shale h..:...·Ol11CS \ e l) ' resistant slate. Orthogneiss is mel:lmor· rhoscd gr.mit" :md has a simi lar aplll'ar:mcc. A variety of pJ rag lleiss ro~k s may h<: d~\ e1 ofl'C d from meta morphmed sall,\sIOIle:. shOl k and Illhc r s.:di lll~n ls. Sch isls arc medium· grai ned cryst:d tinl" rnc ks d...' ri\'ed from sed imen tary rocks. I he) a re easi ly v.eath...rcd III humid c1 imaks hut resistant in ar id Cl1VirOlimen b.
538
( ll '\ I' I 'U~
14
Rem ot e sensin g o f Solis, Minerals, and Geomorphology
Grand C a nyon in ,\ r izo n a ..
3. landsal Thematic Ma pper band 4.
-
e. Shaded re lief map uf DEM.
Sluvwrts Plateau
b. Digital elevation model.
d . Slope map derived from DEM ,
Figure 14-30 :II Another secnon of the (Irnnd Canyo n on the Colorado River in Arizona. as recorded by the Landsat Tb..-rnatic Mappcr fhand 4; 30 x JO on. North is ro the kn to improve intcrpretahilu y. Color Plate 14. 4 provides additional information. h) Digital eleva rion model derived tr om 30 x 30 rn US(iS data (d isp l a~Td as 3 'Ire second, <,lJ )( 93 m cells) Note the higher elevation Shivwits Platl·all. c) Shaded relief map. d} Slope map where the brighter 1111: pixel. the steeper the slope tan e r Moja ve Desert Ecosystem Program. l '19 ~; Landsa t imagery courtesy of Space lmaginj!. tnc.).
Rock in Figu re 1-1·1. anticlines. ami synclines. as previously illustrated in Figure 1-1· 17. T he fo lded strata are eroded diffcrentially, depend ing upon the typr: of sedimentary rod. present. For interbedded sandsto n" and shale in arid en vironmcms. the more resistent sa ndstone forms nnnctinot ridg es, whereas the shales arc eroded to sym'!inal vattevs, This ca n form nearly parallel systems o f resist ant ridges separated by eroded valleys. T he res istance of carbonate rocks such as limes tone and dolomite depends on the climatic cond iuon s. In arid reg io ns with lillie water. limestone is resistant to weathering and tends to create ridges. Conversely. in humi d
reg ions limestone may be dissol ved and therefo re is more easi ly erode d. forming valleys or lowlands. Depending upon the stee pness of the d ipping terrain, the ridgcs may he asymmcmcal or symmetrical. A hoghack is a sha rp-creste d ridge for med by d iff crcnual erosion of a resistar nbed of steeply dippi ng rock. For exa mple. a folded land, scapc ncar Ma veric k Spring, WY. is shown in Fig ure 14-32a. It is a dissected asymmetrical dome with a se ries of res istant hogback ridges surrounding the structure . Figure 1-'-32b depic ts an App alach ian Mountain range syncli nal valley bounded by the Brush ~ I\'unta i n ridgdi ne to the wes t and the
539
Geomo rp ho logy
sin (".ha n d
J{,\ U.\ I~ I m :ll:t' o f Ih (' I'h an l: Hnei f{an gt> in ·I h a ila nd
Figu re 14-31 Shunk ImJl,! lng ltJd.l r C· l:>md imago: of the Ph
Canoe MountJ in ridgeline to the cast ncar Tyrone , PA. In this environm ent. the sandstone is more recistam to erosion than the solub le limestone. f igure 14-3 ) dep icts the San Rafael swe ll in southern Utah . This is a flat-topped upwa rped mo noc line that slopes to the east-sou theast. The more resisuuu sandstone ridg es fonn hogba cks on the so uthern and eastern fl ank s o f the monocline . Sometimes rh c fold ing is so sc vcrc th at th c lay ers are nearl y vertical. For examp le, Figure 14· )4 depicts th... Ugab River in Nami h ia in ..a frica w hich Ilnw s throu gh nearly vertical folded laye rs of thinly bedded limestone. sandstone , and silt· stone (Color Plate 14- 5).
wd el-
:iO Il
"" )fL'
The a ng le of dip ofu resis tantbed such as a hogbac k may he calculated usin g phlllogrmnnll'tric me asurem ent tech niques and the formula:
""
tllnO '" -
( 14 -0)
where e is the dip angle, 11 is the vertical distance. and d is the horizurual distance. as sho wn in figure 14· 35,
Fault·Controlled Landforms :11...
sa is -
od-
". om 2b oy b<
Therc arc th ree ma jor Iype s o f d isplac eme nt in fau lts. including: dip-slip, strike-s lip, and obl ique-slip. as pre\ iouslv shown in Figure 14- IM. The dip-slip faults rna)' he further subdivided uno normal, revcrsc.mrust. graben. and ho rsr. as shown in Figure 14-36a -c l. In a lIorm,,1fonh, the hanging wall is moved (displaced) do wnwa rd from the footwall. e\ pos ing aj"lJII scarp on the foot wal l l Figurc 14-3(01), The
Wasatch fau lt a long the Wasat ch vt ountains 10 Lt ah is a good exa mple I Figure 14-37 ). 111c wasatch Mounta in Ra nge of the Rock)' Mountains is the uprhrown block , an d the dowm hrown bloc k is the valley floor. Faun scarps at the base o f the Wa sat ch Range gene rally face west. A n'w rsC' fau lt is cre ated when the displacement take s pla ce in the oppos ite direction (Figure 14-36b ). If the reverse faulting. causes the slab o f strata to m ove hor izontally on top of the la ndscape as shown in Figure 14-36c. we hav e a thrus t or Ol ·I.'I"-/ I,,·IIM fau lt . " fau lt ca ll also inv olve Iwl.' fault p lanes. .-\ grah,·11 is produced w hen a b loc k of material ge ls displaced dow nward between IW(l norma l faults (F igure 14J 6dl. Thcs... often produce rift valleys, such as thc grcar East African rin syste m. "lIor,, ' is created w hen a block of rnateria l is thrus t upward between parallel fault p lane s (F igure 14 -36e). When the d isplaced roc k marcria l occurs paralle l with the faultline . a .\ Ir ih·-.\'Ii" fault is crcmcd (Figure 14-IKh). For example, the San Andreas Faull in CalifllOlin is a classic ~t ri ke-slip fault. It passes through southern California cast of Los i\ngdl.'s.lhrough tho: southern portion of tho: great Ccn tra l valley. runs through S:ln Francisco. and then o ut to sea . A portion orthe faultline in so uthern Ca lifo rn ia is show n in Figu re 14 -3ft The we st s ide o f rhc San Andreas Fau lt is mov mg nonhwcsr. \\ hill.' the Cll·U side ofthe la u lt is movin g so utheas t. hence the 0 11 4 uuted observation tha t Los A ngeles and pans of San Fra ncisco. because they arc on the we ste rn side of the fault. are moving Ollt III sea a lbeit eve r so slow ly. Figure 1 4-J ~ also ide ntifies the Garlock normal fau lt. The imcrscc uo n ofth e Ga rlock and San Andrea.. fau lts is a \ cry mtc resung place to live with minor trem ors occurrin g almost e\cry daj , ~ulic e that the San Andreas Fault has created a
r
p
540
( 'IIt\ I'l'n~
14'
Remote Sens ing of Soils, Minerals, and Geomorphology
\
I
.. S~" ncl i nal
, 'a ile)' in t he .\ p p lll.:tc hia n
_' I " u ll i ll i n ~
nea r T) ru nc. P..\
b.
Fig ure 14-32 a) USGS High Altitude PhoMgmph y ( HA PI oran eroded folded la ndsca p e ncar Ma veri ck Spring, WY, It is a dissected esrmmetric dom e . " luc h is an crustona l remnant cfu plUlllolil1j; unuchuc . 1"\11<.. the fine- te xtured hJpl'l;rilphy. the strike ofth .. ridges and valleys. a nd th e radial an d trellis drai nage controlled h~ the anuclina l stnlcm rc (lHlrth is In the righl). Also note the pWIIl'
incm hogback ridges. b) 1I:\l' of a synclinal valley in llie Apl'a lachi:!11 MOUlllains ncar Tyrone. I'A. uluained on May-l.
I ~S L
The ridge lines of Hrus h MOUlltain on the west and Canoe ~ 1""n l ;l in l'l1 till.' ca st arc ~llll1 pu,~d " I' more resista nt sandstone. .... hile thc Ics, resistant. soluble lime stone sedimentary rock has been eroded. I'lw lI11e rhcdd ing " rl hc s;llldslune and limestone
results in hogbacks at the periphe ry of the syncline with a lr<.'1Ii , l!raill.1gl' ratt <.'nl reouncsy U.s, Gculog ic,1I Survey ].
sma ll rill ...'alley thut is relatively llal whe n com pared with th e te rra in on ei ther si de ofthe fa ult line Th is is most e vide nt w hen v iew ing th e s ha ded relief version of the dig ital elevatio n model (F ig ure 14· 3Sd j. Nat ural la kes ofte n oc cur in these rill valleys w here lhe dra inage pattern has bee n d isrup ted .
Ffuvial processes create eros iu nal alld depositional landlimn s in virtually every region o f the globe. Consequently. there tire a tremendous \ar iel) o f IlU\ lullandforms.
Fluvial Landforms
It is im po rta nt " hen mtcrp rc ung tl uv ia l land forms In an 10 understand the cha rac te ristics o f the rock types with in the drainage ba si n. the drainage pancm. its density, and the gradie nt (s lo rl' ) ofthe w a tershed. St ream s o r rivers
Fluvia l la nd fo rm s are c reated by the weathe ring . erosion, transporta tion , and deposition materials by flowing wate r.
ity (e nergy) a nd hence g reate r bedload and su spended sedimen! ca rrym g capacity, They can even entrain pebbles, cobbles, and bou lde rs in the 110 w. Conversely. when !he
Image
I1l1\\ing over te rra in with steep gradicrns have grea ter veloc-
or
541
Geomorphology
San H. a facl S.... ...II in Sout hern Ut a h
Figure 14·33 Lllldsal Th cmanc M.lppc r band .. image of the San Rafael S", ...11 In southern Utah. II is a large tlat-toppcd monoclmal UplOo arp bou nded b)' hogback ridges on the !Mlulhern and eas r...m flanks. Tbe more res ista nt hogback ridges are composed o f sands tone. '" h ile the less rer-istanl shalt beds ha, el:>eefl eroded (f;('IU r1..-sy Doug Ram~·. Utah Sta te L'n i" a nd Space: Imaging. 11K.),
l!~ ll h Ri ve r; :'i amih ia
tym-
dges
"Om\t~ J.
one. tone
md-
nl y,
I
Figu re 14.34 ASTI-R image of N ami hi'I·~ Ugah River obtained on December 25. 200(1 (h'lIld .'). This river only flows aboveground for a few d:IYS each yea r. [,hl' river pnssl'Sthrough nearly vcrnca l folded layers ofiluuly hcddeu limes tone, sandstone, and s iltsto ne. Sec Color I' lale 1-1 ·5 for a ellIOT vcr«illn ofthis image (w urtt'sy (It"NASA'( iSFC/ \1 ETI+ RSf)An J ARI lS and U.S .lJapan AS-
rD{ Science Ieaml.
an
"''' sity, vers 10<.:edi-
rles. 'he
Figu re 14-35 The angle of dip. 8. of a monochnal ridge \u t;h as a hogback may he calculated from stereoscopic imagery uSing Equa tion 1"·6.
O IA i' I EI{
542
:I .
14'
Rem ote Sens ing 01 Salls, Min erals, and Geom orph ology
Norma l fault
c. 1I,.rsl
Figure 14 ·36 111<' majo r types uf dip-slip fuuhs: al Normal Iauh. b] Reve rse fault. c) Thru st fault. J I Gruben associa ted wnh a di," nlhmy, n block between two normal lauh s. e j Horsr associated with an \Il'lhw\\ n raul! hind,.
stream gr.ulicru dec rease s. sln:;II11S or rivers may no longer h~' able 10 hold uw sediment In suspension and then depos it Ihe material in the c hannel bouom ur ll~ bars. spits. de ltas . ur alluvial tans. In eff...ct. the vel oc ity o f the stream determ ines what kind of m.ncrials (sand. si ll. clay. gravel. cobble s} can be mo ved a lon g by th.: strea m. Even in dese rts. where storms arc infreq uent. shee t-was h CUll induce massive erosion beca use of its inte nse velo city and transport the eroded mate rials gre al d istances. It is important to also po int out thdl the greate r the velocity, the grc.ucr the amoun t o f in-s tream or rive r ab rasion, co rrosion . and quarrying that will lake place. Th us. strcams an d ri\ crs arc active agen ts of geomor ph ic cha nge that produce both erOSi{lIMI and depos itiona l landforms. So me: o f the rnore impU!1ilnt landforms inc lude stream-c ut valleys. Iloodplaius. terraces. deltas, allu vial fans . pc dimcn tc, and p layas .
Str eam
\'ll lll'~S.
Fluud p illin'i. an d I(die Terra ces
Uplift ed terrain ruuy he ero de d b)' sheet erosion. creating gu llies . O ver lime and gi ve n conuu ucd precipitation. these g ullies 111;1;.' tum into smalltributary ch annel s or streams that have grea ter crosinnal powe r. espe c ially if the tCIT'J in has suhvtanrinl gradient (, I(lpe ). If the so urce of wate r continues unabated. the stream or river mOJY inc ise am i erode both the base and wa lls the ruck material creat ing dee p. steeps ided V-s hared valleys w ith minimal fl oodplains and fairly slntight wate r courses.
"r
lf thl' gradi ent is sufficicm. fhe strea m o r river may contin ue to deepen and wide n the rive r channel. However. at some poi nt the river may e rode the river bo tto m to the point thaI the river gra die nt is substanually redu ced . If this occurs. the river IO~l'S veloc iry an d bl'gllls to depos it so me: o f its suspcndcd se diment load. Th is ca n be the beginning of a river
543
Geomorphology
Wa~iHc h
Moumains
Hobb le Cm:k
Maple Sr~ nish
Creek
fork
" Figure 14· 3 7 landsat Thematic Mapper hand ", image o f the Wa.-.alch fault a long Ihe Wasatch ~oumains to the ca...t ofS pringvmc and Spanish Fork, UT. This is a cluwic norma l fault. with the dowmbrown hloek being the valley 110m and the upthrown block ~ ing
g c
s
cc
", ,r
the Wasatch Mountain Range. There are numerous fault escarpments all along the fault line (courtesy Space Imaging, tnc.).
valley with flood plains. .....ide mea nders, and occasiona l 0:0;00'" lakes. There arc a number of factors that can cause the river or strea m 10 hal e a red uced gradie nt including land subsidence. Sometimes a stream or river loses a subs tantial amoun t o f its source .... atc r or its gradient is d iminis hed greatl y. when this occ urs. even more sediment may be deposited . This can
result in extremely broad a nd shallow valley s that have meanders. meander scars. cur-off meande rs. point bars , numerous o xbow lak es , and naturallevees. II is important 10 point 0111. however, that this proces s does not alwa ys happen . Unusual climatic eve nts and man-ind uced impacts can inter-
vcne and dramatically alter" hat "as once thoug ht of 3.<; the vouth- maumry-otd-age srrea rn-valley e rosion cycle (Selby. 19IN). w ay and Ev erett ( I Q97) sugges t that there an: thr ee type .. o f river floodplains: mean der, covered. lind com posite. Mean der jhlfldp/aill s arc caused by a low stream or river g radient and the deposition of some of the suspended sediment load. Thus. il is a low-ene rgy hydrologic system. Moreo ver. most of the sediment load in a meander floodplain stays w ithin the co nfines of the riverbanks . even during flood stage. The greatest erosio n in the floodplain takes place at the outer edges of the meand ers , The greatest depos ition take.. place
14
544
~
Re m ote Sensing of Soli s, Mineral s , and Geo morphology
Sa n Andn.'ns :w d (;nrlock Fa ults in Cali fornia ~
-.
... (-
-.:.;
, J
a . Landsa t Thematic Map per [land 4.
b. Shaded-rel ief display of a digi tal el eva tion model .
c. Entargcmem.
d . Enlargeme nt.
Figure 14-38 aj Jnterscc non ,If lhe San A ndrca~ a nd Garlock hlUlls 111 southern Calitllffiiarecorded on a mosaic of Landsat Fhcmnic Mapp:!' hand 4 im...g<:s. The San Andreas h uh is a nonhwcsr-sout beast 11\.'!ldll1g :;trile-slip fault. hi Shaded-rcbe f displ a~ (lfa Ll'GS digital elev ation mod el (3 arc second. 93.3 m cell). Cl Enlargement of the Larn1<;a1 data hl ghli ghling a portion o f Ihe San Andreas 0 1\ vonc In the lower right portion 01'('1 l. d ] The rclathdy narrow rift ,-"nc us poruuycd by the shaded-rclref moMl (atlCI the Moja\'C Ol'scrt Ewsys lcllI Program. 1')'):-:: w unt"sy SI'Mc<'lm<1J;lI1g. lne.l .
alo ng inside edges of'thc rucuudcrs . Th is proc e ss call lead 11' the creation o f sand and gravel pobu burs in the river. Crll't,rt',I j1UUling: o r coarse sediments (usual ly sand] which arc formed adjacent 10 th e o riginal strea m channel. 0\ er time, the nat ural levee, arc built up by cemin ued acc ret ion. ,·\ ny wa ter flowi ng over tho: naturallevees IUI\ Ic~s velocit y and can usually on ly eruram tine part ide silts and cl ays that arc the n tran sported to d istant sla ckwater loc ations beyond the natu ral rive r lcH'CS. Hopefully. these scdim..nts imprtJ\e the fertility of the soil . A co mp o" i l., jlo"dplaill cont ai ns features commonto both meander and covered llood plain". Composite floodpla ins arc the most common t) pc o f tloodplain .
A small secti on o ft he M issi., sip pi Riv e r show n in Figu re l4· 39 p rovides exam ples of several com posite floodplain fcaturcs. Both n;JIlIrJ,] and man -made levees are present. 11k' la ndsat T\l near- and middle-infr ared bands arc ideal for iJ enti!Ying. tho: \lxho w lakes and till' more geo logically recent flood ed meander scars..... luch arc barely d iscernible in the green and red band image!'>. The sand and po int bars arc \ isi blc 1)1\ all ima ges The middle-infra red hand 5 provilll'" mo re detailed soi l mo isture infor mat ion than any nf the ' II he r hands. As ex pec ted. vegetated are as are dark in the green and red bands end much bri ghter in hoth the near- and mrddlc-in fmred hands. A colo r-com posite ofTM bands i . 3, an d 2 (Rrin ) i~ found in ('(1 I,)r Plate I ~ - 6 .
Floodplains sometimes ha ve relic terr aces associated .... ilh them. A terrace is a gt'n lly inclined. elev 11100 bcnchlikc rem-
545
Geomorphology
-r is
.er
14 -
rl l hematic \tlpper B"n,151mid- inrra'"o1 )
b -
h, for J J}
Figu re 14 ·3 9 f'l" ...dplain lam lfonns on thc Mi1>si';"'; lppi River recorded b) the L lIlJoa l Thematic Map per o n January 13. 1q~3 (SI.'(' Color Plate 1~-6 1 (images courtesy of ~ A SA ( Jbserv atortum and :-pac'l.' Imaging:. lnc.]
DIe .~
ro-
uf
h, ,d
th
n-
nant flood plain tha i lies at a higher e lev arion than the pre sent Jay flood plain. TCrT,ICeS may parallel the ex isting l100dp lain on bo th sid.:-.. although [hi1> is nu t always th..: case. A terrace typica lly has an escarpment on the side f3l'ing the prc-scntday floodplain. Terraces may be prod uced by glac-ia l activ ity or b} dramatic cha nges in clim ate whe re more water a nd energy is mad c availa ble [0 cut through the e xisting floodpla in. Se vera l layers o f terrace" prese nt in a region indicate that d ramat ic cros ronul-d cposuicnal changes have occurred throug h time.
When a st rea m or n ver with a substantial sediment load cntc....a stand ing body of wa ter suc h as a lake, resen..oir. sea, or ocea n. its ' d t,,;ity b slo.... ed drama tical ly, Th is causes the stream or rive r to deposi t ils base and sus pended sed iment load. with the more coarse materials depos ited at the upex a nd the s ilt lind clilY particles moving farther out into the water body, TI1l' continued dep osition of'rhcsc ma terials o ver lime may c re ate ,I delta. T hese tend [0 have triangular s hapes
546
C IIAP'TUI.
14'
plan imetric view somewhat sim ilar 10 the G reek letter Delta (a I, but many other shapes also occur. Th...re are five co mmo n delta form s. In
I::JOIIX"fed or "i~ilafe deltas an: created when the system is dominated hy the cont inuo us input of a large volume of water and sedimen t tha t is "01 impacted severely by waves Th is ca n produce ....hat is called a birds-foot del ta. such as the Mississippi River delta as it enters the Gulf of ~k,ico near :-.Jey, Orleans. LA ( Figure 1-4-40a). Continued input of sedi me nt causes the deltaic stream channels to migrate ba ck
and forth across the delta . Sometimes, however, the scdime nt dcposued on the bank s of the inp ut channel create natural levees sim ilar to that Oil the C\l\ Cn.:J Floodplain previou sly discussed Intense tlond ing may cause the input stream to break free from its confi nement .... ithin the na tura l levee and migr ate to a n curby location. This process can lead to the creation of an ent irely new lobe of sediment depo sition in the: della . Th ere may be se v...ral main input distrihutary cha nnels prese nt in a bird's-foot delta .
On a lohule dcha the river builds into the sea, but relativ ely intense wa ve action redis tributes much of the sedimen t along coastal barriers. cau sing it to have a convex edge o r fan shape facing the water body. It is a wave-dominated systern. T he Nige r River em ptying into the Gu lf of Gui nea in Africa has crcured a class ic lobate delta (Figu re 14-40b). The Nile River emp tying imo the Mcducrraucan Scu is also a lobat e delta (figure 14-4Oc). A cremdate de lta form s .... here tida l currents help creat e
numerous sa ndy islands se parated by tidal channels along the della from. It is a tide-dominated system. The Irrawadd y Ri ve r delta in Burmah is a good example (Figure 14-4Od). Note the extens ive man groves visible as bri ght areas on the Irrawaddy delta . l fth c wave s or along-shore CUITl'I1f.~ are extremely strong , thc y may move the sediment away from the mouth of the river. and only cuspate sand rid ges will be formed that parollel the beac h. Thi ~ creates a cuspate della .
Strea ms enteri ng coasta l estuaries also experience a redu ced gradient. nu!>ing Ihem to dl'posit much of the ir suspended sl-dimem load. An t'slll<1r;ne ddta .....ill fonn if thcs.... deposits a re nOI remo ved hy curre nts in the estuary or by diurn al tidal flushing.
Remote Sensing 01 Soils. Mine rals. and Geomorpho logy
dcpo su malcrial in order to ma intain an adequate gradient. An oll" I'j"l.lim is a low. conic al-shaped depos it with the apex uf thc co ne ut thc mouth ufrhe valle y from which ihe fan-building srrcum issue s. The mo re coarse materials such as gravel. cobbles. and even boulders are depo sited ncar the apex while the sand , s ilt. and d ay part icles arc transported10 more distant parts of the fan. These mat erials arc collectively called alluviu m. he nce the term alluv ial fan , The conical mound of material is deposi ted as distributary streams swing bac k and forth across the fan , l bi~ can crcae d ic hotcmic or braided draina ge pattern s. Multiple alluvial fans that coa lesce at the base of a moun tain range create a haiada. A Landsat Thematic Map per band 4 image ofan alluvial fan adjacent III the: Salton Sea in California is shown in Figure
14-4 1a. Note the input stream channel in the upper right.md the conical-shaped alluvial fa n that has resu lted due 10 millions of years of suspended sediment tkposi tion frum \~' sporadic rain fall events. It is clear that the bright- lone materials depcsued o n this fan had thei r origi n in a d rff erem localion when compared .... ith the darker ma te rials fou nd at the base oft he nearby moun tain range. A lso note the dicho romie drainage pattern . Another largl' alluvial fan in the While Mountains is shown in Figure 14-4 1b. An ASTER image of the Taklimakan alluvialfan in the 13klirnaka n Desert in C hina's XinJiang Province is shown in Figure 1.$--12. This fan is tocutc d in the Iandsca pe bcr.... een the Kunlun and Ahun mountain ranges. Peclimenl '" A P{'IIiIll..nr is .. gentl y inclined erosion..l s urface carv ed in bedrock, thinly veneered with grav el. and developed al the base of mountains. Pediments arc most prevalent in very arid environments, i\ pcdim cnl may look like an alluvial fan on an image . hut it is dram aticall y different . A pcdimern is an erosional surface, while an alluv ial fan is a depositional surface. In fac r. many of the conical featu res in the G rear Basin of North Ame rica. in southern Africa . and in Austra ha art actually pediments and not alluvial fans. Examples of pedimenrs at the base of the White ~l ounla ins in Ca lifornia arc shm~ n in fi gure 14--1 1b. The head.... ard erosi on {If the bedrock st rews sortl'd material d uwnslup c. The mountain may eventually
Allu\ ial F:lns :lncl Ih j :l cI:l s Streams l'merg ing from a mou ntain valley inw a lowla nd area often enco unter reducl'
Pla)as arc shullo.... lake basins funnl"d in arid desert regi,,1lS Ihal arc intcnniuellt ly filled .... ilh water that e\ aporn les rela-
547
Geomorp ho logy
ient. the
Mississ ippi River Delta. United Slates
--
Ih< uch the
Niger River Delta. Africa;..._ _
••
ro '\ c ly
Ia')
all'
vial Il' a
lim
~ure and m ilIfcry
,.
sate-
cca-
Nile River Della, Egypt
h.
Irrawaddy Ri\ cr Delta, Bumlah
. the
tnic ite
ra km en
~
in :thc arid on
• an
W T-
Ism
'ce ~i -
'" ed-
"l
c.
d_
FIQure 14 -4 0 a) Space Shutt! c photpgraphy o f tho: \ol issis..sippi River " lml~.'1<'llhl rd 's-fOOl delta. C'oosisting ofseveral otllklS and W iTa.... socillh:'l1 nat ural k\ccs ( ~"Im...~y K. Lulla, :"ASA John son Space Ccnlctl. b) Spa(.: Shunlc photOgrolph of the :\igl"'f River lo1>." .. ...... lta cmpl)·in b into the Gulf ofGu ino:a in Afri ca I l\ AS . \ Joh nst>nS['3Ct" ( 'cmer; STSt>IC- 1::-0 0721.ct MI)l) IS ima ge o f lhe Nile R,ver lobate dell .. in t~ypl ( c.lUnl~y '\lASA Goodard S p.,~C' Flighl Ccmerl. d I Iffil\\ aJ.J) Ri\ cr . fl·,,,,/nl,· delta in Burmah. recorded on il Thcm mc ' Iar pc'l" rood " nea r-infrared imag e \counc-sy '-;pat:e Imaging. lnc.j.
548
('"IIA F I ER
14
Utile Sa n Bernadino :\llIunta ins. CA
Remote Sens ing of Solis, Mine rals, and Geomorphology
White 'tountains near Death \'all l'y. C A
California Aqueduct
b. Figure 14- 4 1 a) Alluvial fan i~~u lJlg from between the Little San fkmaJIRO \1 ou nLilfn) 01110.1 Cbocolare \1ounLain n
Ftgure 14-42 Tbe Taklirnakan alluvial fan ex tends across the ok-so lal': landscape between the Kunlun and Ahun mountam ran j!:C!i thaI roen the socrhcm bonkr or the Taklima k.m Desert in Chin a's Xinl iang Province. Note the intricate dichntomic drainage pattern. ·111 is AS TE R (magt: was ubramed on May 2, ~uo2 . Nonh IS at the bonorn of the illustration 10 aid \is"a1 intcrprctauon (l'OUnL"S)· o(NASA GSrf ~t ETll f: R Sl)AC JAROS and U.S J J.tpan "~ sTE R SCiL....cc Team).
tiv ely quic k ly. leaving a resi due of fine-textu red sur face materials . .Man y pla yas arc sa line a nd ex hib it bright tones in imagery. MO"t playas are barren with hn le vegetation. A
p laya is present at the base o f the a lluvial fa n in th e While Mo unt a in s of Cehfomia [ Figure 1 4~ Ihi.
549
Geomorp hology
Kars t Landforms
Landforms crea ted in lim eston e a re gene rally re ferred to as l(lr.~t topography. To be a true limestone at lea st half o f the rock co nsis ts of car bonate m iner als o f whi ch calcite (CaeO J ) is the must common (Selby. 1989\. Dolomite (CaMg )CO_I • anot he r ca rbona te roc k. is also suscepti ble to dissolution but is nut
'ea. • in-
Surface water derived from precipitation is ac tually someII.hat acid ic. Wh en acidic surface water percolates dow n.....ard through limestone. rhe chemical proce ss o f carbonari..m takes place ailing joints a nd bedding pla nes, graduall y enlarging the openings by dissol ution . un til subsurface cave rns. C;l\CS. a nd subterranean chann els are created. Collap se o f thc roof o f a subsurface cavern o r do ~~ nwnrd d isso lut ion o f limestone from the surfac e pro duces dep ressi ons at tilt' sur face commonly re ferred to as dolincs (th e English term is .linkJwl<'). Dolincs
Figure 14-43 L'ahbrared Airborne Multi-pcx-tral Scanner (CAMS) ncar-infrared J)( J III data of ~arsl dclin c [sink hole) topography north of Orlando. FL. The depre~siCl IlS arc l:leateu hy d issolution o f limes tone roc k. Ther e is no surface drainage patte rn in this area bcca u..... al l drainage is subterranean. TIle darkest arcus arc dcep water Th... llrighl are a IS sand. Many of these dolmes arc bcavily vege tated.
ka rst topogra phy. Conversely. dolomiuc limestone such as lnal found in pans o f Kent ucky is less susce ptible to erosion Consequently. il develops a hi ll and va lley topography along with a surfac e drai nage pattern.
th' tun
of
,.
,.
er-
'0
"C!
;"
Limes to ne with > 4U percent calcium carbonate is w ry suscepubte 10 weathe ring in humid climates and may result in the ..lcvclo prncn t o f an cxrcnslve network o f dol inc features . For examp le. cons ider the blac k-and- white infrared photograph o f karst topograp hy fou nd nca r Orlando. FL sho wn in Figure 1-l.4 3 These dolincs (si nkho les) were produ ced by dissol ution occurring ur fav ora ble sues suc h as the ime rsection o f major joints in the limest one. The lim esto ne is disSOI\L'Cl and the solution an d residue mow downward, con ..tamly w idening rbe fissures unnl a surface depress ion is created. Tbis permits the collccuon of more o f the surface wate r runoff and therefore the prog ress ive enlargement o f the do bne. Sometimes. the dolines collapse. leaving large surface de pressions. In th is ex ample, there arc few su rface drain age channels. only subterranea n one s. In are as o f high loca l relie f and abundant trop ical prccipira tion such as in Puert o Rico . Inc we atherin g is g reatly acce lcrated. causing the sin kholes III coalesce. c reating haystack
Limestone is especially d ifii cult to idc nt ify in ex tremely arid desert s or co ld Arctic environ ments because the small amo unt o f pre c ipitation doe s not prod uce the weathering features disc ussed ab ove . Instead. limestone IS likel y the resistant caprock on escarpments or pl atea us.
Shoreline Landforms
More than two-thirds o f the wo rld's po pulation lives w ithi n 100 m iles o f the coast. Scientists arc interested in understanding: coasta l processes associat ed VI uh the: dy namic coastal plain. beac hes. spits. ba rs. terraces. est ua ries, etc. Th ree major agents arc re sponsible tor the crea tion of specifi c types o f lan..t form s in the coastalzone: 1) energy from the Sun. wh ich produc es wave s and ocean curre nts. 2) thc· gravi tatillna l pu ll of the moon and the Sun co mbine to c reate tide s. and J } man is a very active geomorphic agent.
550
C I!AI'T ER
14
Remote Sensing 01Solis, Minerals, and Geomo rpho logy
KU l'l ait ( 'if)'. t\ lHUh
Figure 14-44 SI't n panchromatic 10 x 10 m image of Ku\\ ail City. Several man-ma de gloms lIcn icsl influence the deposition (Or ercsce ,,( sed iment carried hy the kmgs hore C"lllTt"nl . \\ hreh g..nerally flows tro m sou lhc3S1 t(l nort hwest. A 13rg.. Splt or hook il pre -em ... the no rthe rnmost pari o fthe <:11)'. T his is a good .:x..nnplc of hl' " lIwnlo.. ind IS .ln ac tive agcr uo f geomorphic chan~c in t h~' coastal W ill." t c SI'
Rad iant energy from the Sun d ifferent ially heals the Earth's surface. creating variations in air p ressure, w hich produce wea ther dis tu rbances. Wind-generated surfac e waves are the main source o f energy along a coast and arc respons ible fo r man y o f the erosiona l landfo rms a long the co ast. Converscly. ..... a ves also ge nerate coast al cu rrents that arc respo nsible fo r the l (l ng ~ lltl re move me nt o f sed imc nt a long bcac hcs (Sel by, 19X'J). A wave of he ight (II) is produced by a sustai ned wind blo wing me r a wa tcrbody for a cert ainktdl distance I F) where It =- O.J6JF , wave height may also be estimated if only the sus taine d w ind vclu...· ity (f) is known using the rel atio nship Ii • 0,002 4 · Sus tained prev ailing winds hlow ing o ver grea t ex panses ofwat...-r may create oc ean currents that arc a lso influenced by varia tions in water tempe ratu re and sa lin ity. TII..:s... oceanic currents suc h as the Gulf Stre am ca n impac t shoreline landform development becau se they influe nce the Ic mperat ure and am ount o f suspc nd cd sediment in the WOl ter, which in tu m C;l1I impact the de velo pme nt of co ra l ree f a nd ma ngrove ecosystems.
r.
Th e gravuarional pull o f both the moon and thc Sun o n the Eart h c rea tes tides defi ned as tho: periodic rise and tal l ofsea leve l that occ urs in mu~t seOlS twice da ily. Tides arc impo r-
ram
I- ":":::I U''':
Ihe) inc re as e rhc vertica l heigh t over which
wave act ion ":.1 11 ntfcct thc coas t. Cu rrents produced by tidal ebb and How cun en ...k as \\ ell as trans port sed iment. The tides also l1ush much of the nutrie nt-laden dct ritis from
with in es tuar ies and lagoo ns into the o pen ocea n, The dcrritis is very important in the aquatic food chain. Fina lly. mankiml is an active geo morph ic ugem constantly cllj.:incering and rccugin...... rillj.: the coas tal zunc . He rouunely d iverts majo r streams. rivers, and long shore currents from th... ir norm a 1 cour ses. significantly impact ing their rradrlil'n:i1 suspended scdimcm loads. 11c dredges r ivers ;lnd streams. chang ing th...· ir gradie nt: fills werlands: builds jetties . re\ ctmcms. and se awalls that red irec t W3V1." energy; and builds rn.m-madc struct ures un top o f fragi le coastal landloons such as dunce. Figure 14.44 d epi,·ts groins (jellies) rcv cunc nrs. -cawatls. and ma rinas present on the Kuwan C it) sho reline tlMt impa...·t the dcposuion and erosion ofsusponded .....x trmcnt carricd by the lo ngsho re CUlTC nt . Th...
CO
i~
f'lmla l1) dcfincd as the g...-ographical upland
n: g1l111 adja ccn t to a sea. The .• horeline (o r com tli",' ) separares the coa..1 from th c sea. and is the geograph ical area
55 1
Geomo rp hology
"'ar('l\l'Il Spit. So u t h h la nd. ;\ ('1 \ Zl' alan d
Rgure 14 -45 F~d l Spit at the northwestern point ofSouth Island. ~ew Zealand. stretches, for .'0 km east from Cape Farewell. This AST ER image "'as obtained on February 13. 200 1. Tho: north sid... rof!hl: ~pi l is composed of sand dunl"S, while thl.· south sid e facmg Golden Hay is wet soil. Submerged uda l mud flats are \'i~i t- It' sout h ofthe SPit (courtesy of ~ .\SA/(iSfC MI:': T IIERS-
DACfJ:\RUS and U.S. J a.pal\ ASTER Science Team).
""is
.'
affected hy wave ac non, The vided into (Selby, 19R9j:
.\ hflrt'
may be fun her subdi-
the ldf.'I/O/'<' area below the low -tide wave-breaking line;
'h ~a l
Ite
the nearshore b...twee n the low-tide breaker line and the hig h-l idc shoreline:
om
n-
the fareshnre between high - and lew -ride shorelines;
Jv I,
the h
m
litd
,. •d
l·
• I
5·
d
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a
Depos it iona l an d erosion;11 coas tal landforms arc discussed below, Hea ch ev, SlIlh. HOll ks. Ilan. narrtcr Isl a nd s. La gonns• and t:\ tuarit'~ A beuch is co mposed prim ari ly of inorg anic sediment deposited b)' long sho re curre nts in the shore zon c. Conunuous wave action causes beache s EO he composed of wellsorted sand-sited particles. a lthough th is can \ ary. For example, some bea che s adjacent 10 major rive rs are com posed o f gravel ma terial s or even co bbles transpo rted a lo ng shore from the bedload of rhc r iver. Th e source of'bcach \CJ-
iment rna) he from upland weat hered materials adj acen t 10 the beach such as a chtfwall, fro m the offshore zo ne where wa ve act ion moves sedimen t sho rewa rd. fro m fragments o f decompostng shell and/or coral. and from suspendcd sedimen t or bedload material from rivers and streams. The conunucd buildup o f sediment 011 ge ntly sloping shorelines may cause the beach 10 enla rge in size, move in land , move up or down the shoreline. or move seaw ard . A major sturm can cause :.IIlY o f th...sc e ffec ts in a vcry sh ort lime . In any cas c. hcuch ,.idg.'s may Ill' fo r med . [I' the beech ridge e nds in open water. it is called a .I'JIII, The Fa rewell Spit in Nc\\ Zealand is shown ill Figure 14-4 5, The bcach ridge o r spit in Iron r o f Morro Hay, CA (F ig ure 14-46 ; Color Plate 14- 7). creates an excellent bar hor if it is dred ged rout inely. S pi t~ 1... nd to develop in thc predomina nt direction o f the longsho re sed ime nt tra nsport unde r wave ac tion, If the spit curves hack towa rd the lan d. it is ca lled a houk.. Th e hook along the shore (If Kuwait Cit)' is a good examp le (Figu re 14-44 ). A sp il con necting two head lands is called a bar. Behind the sand spi l or sand bar a shallow /"X()<)tI or "'-I) ' may ronn. Some bars nrc so ext ensive that they are ca lled harrier ;<1,,11<1.-. On th... eastern coa st ofthc Un ited States they exte nd for a.. much as 100 kill and may be scv ...ra l ki lometers wide. For e xample. Sullivan s Island is a coastal barrier island near Ch arlestnn, SC ( Fig ure 14- n and C olor Plate 14-8.1). Barrie r isla nds take the brunt o f hurricane storm surf and storm
14
552
Remote Sensing of Soils, Mineral s. and Geomo rphology
:\Iorro
Ib ~ .
CA
a. i'"dn " f Morro Bay. CA, digital "rt h(' l'hn[o <.J U4r1cr 'l"" drJuglc (DOt)()1 M ay
2~.
1'N4.
c. Landsat Themanc Mal' f'CT Hand 7.
Fig u re 14-46 a) Panc hromatic USG S DOQ() of Morro Bay. C:\ . The thl} or 1,lg(lo1\ i~ ~r,\rJ I~t1 from the ocean by an e xtensiv e beach ridgt (courtesy U.S. G~'(ll og ical Su rvey ). b l The beach bar a ls" has numer ou s dunn. "" IlJ~'!l f 1'0hieh are vegetated. w ave aClI\lty In the shore Tunc is visible in LandS31 r \l hand -l cl Ran
Geomorpho logy
553
Figure 14·47 Panchromatic version of the USGS digital orthophoto quarter quadrangle of Sullivan's Island, Sc. Numerous wastal landforms arc present. including a harrier island created by accrctiun of multiple beach ridges. sandba rs. tidal ink ts, and tidal marsh (Sparr;,,,! altorniI/ol"a) , A cotor-mtrared composite nlthc area is found in ('" lor r lat... 14· lIa,
surge . Sullivan's lsland experienced a 15 n storm surge du ring Hurricane Hugo in I lJX9. A tomb oio is formed when a bar or spit joins an onshore isla nd 10 the mainland. ,\ 11 estn(II :\" is a buy at the mou th uf' u r iver where the tide infl ue nces the river current.
Tid:ll Flats, Tida l .' l a rslll.'s, li nd ;\ I ud Fl a ts
A cur ious thin g abo ut the nearshore 10111;' is that the conun uous wav e act io n ca uses clay and vilt-sivc part ic les to flocculate (meaning that the particle s crick IOgo-ther) into loose, relatively la rge agg regates in seawater. Often this material is moved from the shore l one into lagno ns o r estuaries hy wave or tid al ac tion . When the wave or tidal actio n ceases or becomes slad.. the floccula ted material is de pos ited un the lagoon or estuary bottom. Th us, one mightthink o f the shore zone as a place that scrubs the water column , (k positing the more coarse sand and gravel-size material on the beach and preparing the chi); and sil t-size part icles tor deposition elsewhere. This Ilocculuuon and movement of materials expla ins why there is such a differenc e between beach :l11J estuarine environments .
lidu! fl ats arc coasta l areas that
554
CH \P'J EN
14
Remote Sen s ing 01 Solis, Minerals. and Geomorphology
.\ l il n h Iw hi ll d hll' "r 1>:.I IIll~. sc
e. l"AS!\ ATI.AS Rand (, 1 1l<.-;u·;n ~m:I)_ Figu re 14-48 a J NASA ATLAS band 10 thermal infrared 3 x 3 m imag v o f the maNh behi nd Is le of Palms, SC . nhtninc d in August. 1m hj EIl[;,rgcd ATLAS Hand t> l1<'ar-infran."d imag", of a poruon of till,' area. The images wen.' obtained at mid-tide. Some urIbe tidal mudllatli [which have no \eget.uivn) arc \'XPO"l'tl , while others an' inundated by the incoming tide .lowing through tlte tidal cha nnels . The moll,' den se patches of smoot h co rdgrass (S,.urWIU ult•.,.,.if/ />r /I ) show up
"brin e Ter-races when a coastli ne is uplifted through tectonic activity. the original wave -cut platform is raised 10 a higher a ltitude and wave action begins to create a new wave-cu t platform. The result is the prese ncc o f a relic mari ne terrace and assoc iated slee p bluff s or cliffs . During the Pleistocene many tectonic uplift s occu rred . T he dramatic marine terraces along the
southern L'alifo rnia coast ncar Pa los verdes were produced in this manner.
Cora l reefs are created b)' living coral polyps and ca jcarecus a lgae ( Figure 14· 4'1). Cora l reefs develop bes t in seawater betwee n 77 0 and S6°F with norma l le vels of salinity Thus, coral is g c nerally restricted I I) the tropic al reg ions of lhe
I
Geomo rpho logy
555
I'a lall c n Reef. Cezumel, :\Ini co
..
Frenc h :\lururull ,\ 10 11 in the SIlm ll
b.
Figure 14 ·4 9 ,1 1 HI\: (i real Burrier f{,;cfof i\\l~lralia exten ds for appm"ill1aldy 1.211lJ miles (1.0()(I km Ialon g the Ou ..·... nxlarnl coast. T he reefs C;lp lurcd on this Sh un k photograph (STS H.. o_()77_0~ I ) arc located a l
world between 30 and 25 - S latn ude. Co ral requires water lha l is < 100 m dL'CP and generally free o f sedi me nt so that photosymhesis can ta ke place. Coral reefs etten ~'TOw b.:st on Ih.: wind ward s ide of islands .... here .... J,\e energ y provjdes food and o xygen fo r the co ralpolyps. Howe ver, signifcam reef development can also lake place on the leeward Side of islands if a stro ng ocean curre nt is prevent. For e xampte. the Palan car reef system on the leeward side of th... 0
:-.;
er s. e
Isla nd of Cozumet. Me xico. IS hathcd by a stro ng, clear up" cIlin g oc ean current. Fresh ....arcr and significant amoun rs of sedi men t can prevent co ral ree f growth. Coral cannot ~f\ m' (lui of sea.... all.or; therefore . mean lo w-tide determine s the uppe r hmit of coral grcw th, Sea levels may rise due to g10""'11 \l. armi ng Consequen tly; we ma y expect it comm...nsur:lle growt h in cora l reef building during th... co ming century if pt.,lIuliun docs nnt destroy th... co ra l first .
556
("tUY I Ufo
14
The coral polyps litera lly create a built-u p Iimcsrouc surface anchored to hnrdhottom materi aIs. There are three primary types of reefs. A barrier reef lies offshore ami is separated from the land by a lagoon. The Great Barrier Reef is an
"Remote sensing of Solis, Minerals, and Geomorphology
Ant arctic lee Sheet ncar
Ge
~Iollnt Vinson
excelle nt e xa m p le ( f igure 14--49a) , It extends I{lTmore than
1.200 miles along the north coast of Australia. If a reef is A
attached to the land and extends out into the sea. il is called a fri nf:ing reef A portion of the Palancar fringing reef on Cozume l is she w n in Figure 14-4% . There muy be gaps in
"g l to
fring ing reefs due to the input of fresh water or suspended sediment. Fina lly, we may encou nter an 11(/111, whic h is a ringlike reef encl osing a lagoon with a central island Iwhich ma yor 013 ) ' no l be present e ith er du e to subsidence or sealeve l riscj. The M umma atoll in the Pacific Ocean does not ha w a central islan d I Fig ure 14-1ge).
SI
rc b
f' M
n I, L
C ua..ta l Er ucien a l La ndfnr m c Coasta l erosionallandforms ar c crea ted when the combined transportin g capacity of wa ve an d longshore current energy exceeds the supply o f sed iment. Most coastal erosion takes place during storm ev ents due to the desrrucuvc fOR~ o f wav e ene rgy. Dependi ng upo n ho w 3 coastline is oriented, wa ve refract io n may ca use either a spread ing out o r a co nve rgence of wav e energy. Headland s or points experience a conv ergence of W3V'C energy a nd arc therefore more susce ptible 10 erosion . Conversely. adjacent bays generally cxpcriencc a divergence o f wave energy and less erosion , The eros ive power of wate r may prod uce beach cliffs with vary ing grad ie nts. Rock fragmen ts in the sur f and the treme nd ou s air pressu re produced when surf breaks may combine to erode beac h dins , crea ting ca l"t'".~. arches, and e ven
blowholes,
Glacial Landforms
A gl acier is de li ned as a body of ice. fim (c om pacted gran ular sno.... ). an d snow. originating on land and showing evidence o f past o r present 110w. Glacial landform s are created by the movin g ice , nivano n ( 3 combination of freezing and tha wi ng precesses ). and g lac ial mel twater. There art: tw o general categories o r gla ciat ion : cont inental and atp inc: D uring the Pleistoce ne Epoc h (so met imes referred 10 as the Great lee Agel. lay e r upon layer o f snow accumulated from year 10 yea r. creati ng va st g laciers that covered much of the Northern Hemisphere. There were approximately rour major advances and retreats or the co nt inental glaciers. with the most recent continenta l glacier retreating (diQpp.:aring ) approx imately 10.000 years ago from the northern Un ited States. Only portions o r Antarct ica a nd Greenland cu rrent ly
Figure 14·50 A small portion of the Antarctic icc sheet ncar \ l"url1 Vins"n recorded by ASTER 1-'11 November 15. ~OO~ . ~ole the compression ridges formed 011 the c... t ~C I' f the glol.:ial tee ,b it ~'s bl.1I1< l--.:tl I"" mountai n ridges. Antarctica contains <10"/. of tile world's icc. The Antarctic icc sh«1has an amazing a\erage thickness on, ] eo m (7.090 tH tcounesy ct ;'>lASA!( iSFO \I ETI' I,I{SUAClJ:\ROS and U.S) Japan ."ST ER Scien ce Team),
have continental glaciation . For example. fi gun..- 14--50 is an AST ER image of a small portion of the Anta rctic ice shoo nca r Mou nt Vinson. Note the com pression ridges alon g the edges or the ice as it 110\\ s through the valley be twee n two mountain ridges. Alpine glaciat ion is still present in many of the g reer mounta in ranges ofthe .... orhl, such as the A lps. Himalayas, Rocky Mounta ins, Sierra Nevada. Andes. etc. Both a lp ine and continental g laciatio n prod uce un ique land form s based on erosion and deposition . We focus (lUI" euemion first on the major land form s that C3!l be identified thro ug h an alys is o r remote ly sensed data . II sho uld be stressed that the optimum method o f study ing glac ia l land forms is often to evaluate them in th ree -dimensions. i.c., stereoscopically or in pseudo three-di mensions. For exam ple. Color Pla te 14.1} contai ns b oih vertical and threed imens io nal vic ws o f a small pa n of the \1a laspina Glacier in Al aska, Th e three-dimensional h igh obliq ue view was ereated hy dra p ing a Land sat Themati c Map pe r image o n top of a S pace S huule RADAR Topography Mi ssion (S RTM) derived d igita l eleva tion model. T he three-drme nsi onal vrcw
, I
r r
r
Geomo rpho logy
provides unique in formation aboutrhc relativ e heigh t, depth, and slope of the glaci:ll featu res.
hallgillg vulleys, lI :ulg ing valle y streams often e nter the main Ya lky as wnte rfalls.
Er o, io nal r.lada l l. 11n tlror m~ : C ir q ues , Tarns, A n 'li's , Ho r ns, l J.Sha pl't1 Va lll')" , I bn ~i ll lt \ 'all e)"
UI'lllIsitinn :11 G lacial La nd for ms: \lo rai ll l"~. '\Iorain a l Lakes, Till Plai n.., t-:,kl'n, K l"tt k~, and Ilrumlins
A cirq/lf' is a se micirc ular srccp-w ailed a mphithea ter-shaped valley ill the uppe-r reaches of an a lpine glacier. An a lpine
Impressive glac iallandforms arc a lso created by the depos ition of glacially eroded materia l, Rock material that acc umulates on the side or ed~e of a glacier is ca tted a la teral moraine, [ftwo glaciers mee t. a ""',Ii,,1 (or midd k ) moraine may he created at their confluence. This often ap pears 3.<; a dad, ribbo n on aerial photo graphy or other irnagc ry, For e xample, Figu re 1-I-55a de picts the Barnard Glac ier in Alaska .... uh several tributary glaci ers . Nume rous lateral moraines are prese nt. Several m~-J ia l morai nes are created h} the confluence (If the lateral mo rain es.
glacier erodes hcadwar d. downward, and alo ng the sides of the original v-shaped stream valley using the immense pressun: of the o\~rl) ing ice, niv ano n. and g lacial quarry ing of rock. Interestingl y. after the al pine glac ier ret reats, there may be re lat ively little material in t he bon o m of the c irque. In fact, the base of the c irque rna) have been eroded more severely in certa in areas creating a de pressi on. After glac ia l retrea t. the depression may fill with runoff: creating a glacial lake or tum, Numerous cirques in the Uinla Moun tains of Ltah arc shown in Figure 14-5 1abo,\ co lor image o f a Landsal MSS image of the area dra ped over a digi tal elevation model is found in Color Plate 14- IOa.
.,
he
of ~ .1
an ct
"
An /lff t" is formed .... hen c irques o n opposite sides uf a di\ ide erode hcad w ard c reating a narrow. serrated mountain ridge , If the I\VO c irques conti nue to e rode hcadward. they may even tually produce a ("01• .... hich is a sa g in the serrated ridge. Numerous arercs and cots arc visible in the obliq ue image of the Uinta Mo untams show n in Figure 14-5 Ib. A born is formed when more than two cirq ues erod e head ward, leaving only a sp ire-shaped pinnacle. The most famous is the Matter horn in Switzerland ( Figure 14-51 ). Horns o ften appear triangular-shape d w hen vie.... ed from abo ve in vertical remote sensor data.
'0
During g laciation in mountai nous terrain. the glaciers do not
~ II-
o [,
•l
, , ,, ,
557
normally prod uce new \ allcys, Rather, the accumulation and mov ement of g l;u:illl icc in exisun g \ a lleys erode..beadward. erodes the sides o f" the valley, and sco urs ami deepens the valley floor. Th is process creates a U-sllafl<'cfglacialtrough
or valle y that is \'0.'1)" impressive once the g lacier retreats. Wallsburg Canyon in tho.' W,lsatch Mountains of Utah is a good example of a glaciated Ll-shapc d valley (Figure 14-53 ; (',11m Plate 14·I Oh ). Some glac i~ rs ,c our c\ trcmely dee p . . alkys thaI become la"es a ller the glacier retreats. Fo r exam ple, La ke Tahoe sho.... n in Figu re 14-54 and Colo r Plate I-l-IOe was created in this manner. Lake Tahoe is 23 miles long (37 km ) and 12 miles wide ( IQ k m). It lies 6,12 8 IL't:1 (1,l\I,ll( m) ahlwc sea k'\,el a nd is I.MO feet (500 m ) deep . It is one of lhe dee peM lako:s in lhe l"o ntim:ntal Unih:d St.l tes. If the major g lacia l U-sh:1JX'd valley erodes down.... ard more c:\tcllsi\ cly than the tribu lary glal"i",r 110.... s. it may c rcate
If a glacier reaches eq uilibrium betwee n accumula tion and ablation (melli ng). it prod uces a terminal moraine at the end of the glaci er (Figure 14-55b). If the equ ilibrium lasis for a co nsiderable time . the g lacier co ntinues to move rock and debris dow nslope. ca using the terminal moraine to increase in volume. If abla tion exceeds acc umul ation. the glacier retreats. leaving the terminal mora ine as a remnant landform. I f t he g lacier reach es eq uili br ium once again. a reces5;UII
558
nL\pn:1{
14
Remote Sensing 01 Solis, Minerals , and Geom orp hology
Uinta .' fo u nta ins in Uta h
a . Land sat Th ematic Mappe r band 3 ( n..-..f l ima ge.
cirques and U·shupcd
va llcy ~
b. Landxnt T M band 3 illl.lg<.' draped ove r a USGS 311 '-
:;0 m d il1i u l c1~"\;I1I"n m" dd .
Figure 14 · 5 1 al Lenosu Thcmauc \-tapper band 3 lk'dl image "I' a portion "I the Linta Muuntain Range o f the Rl1Ck~' " Iountains in LulL b ) UUd>.J.1 T\ l ba nd 3 image draped O\ LT 3 30 x 30 m l: SGS digital elevation model ( vcr1lcd l exagge ration is 4 \ 1a.nd \i~ed ,," liquef y. t\ color YCr"'l t lfl IS ''''u:al in Co lor Pla te 1+ l ua Icou rtccy Spa<:e Imaging. I",: I.
559
Geo mo rp h o logy
Fig u re 14-52 f1i gh-ohliql,le aerial photograph of the Matterhorn in Switzerland formed hy ure headwanl eros ion or more than two cirques. The cirque on this side of the Malter hom still co ntains a glacier and to the lefl is a hangi ng glacier clinging \{J the side of the peak . Glacial crevasses are Tl.'adi l~ apparo:TlI [courtesy Amerkan GL"Ographical Society Collection archived at the !\'ational Snow and tee Data Center. Umversuy of Colorado. Boulder. CO).
\\'a..a lc h R an ::,t' of th e Hocky \Iuunt a in s i n Uta h
Mouru Timparmg ns
cirque arete cirque
Fig ure 14-53 La ndsat Thematic :\-la pper hand 4 mcar-mrrared r image ora portion ofthe Wasne ch Mounla in Ra nge oft he Rocky Mountains in Utah draped ove r a 30 x 30 m USUS tligital elevation model tvcruca l cJl:J/L/Lc raliull is SJI: I highlighting the Mu um Timpann!:l0S glaci a l cirques ,1ml uretes and U-sha p<:d Wallsburg Can yon . Seve ral eols arc present on the serrated Moum Timpanogos nd gcbnc. A color version is found in Color Plate 14- l llh (co urtesy Space Imaging, Inc. ).
trend ing across the terrai n in Northern Manitoba. Ca nada. Th is es ker also dcposued S<111J y alluvium imo the g lacial lake as the i!lacie r ret reated . h.
'"
Somcnmes a large bloc k o f glaci a l ICC that co ntai ns an assortment of glacial debris becomes detac hed fro m the
main glacie r. The bloc k of ice and materia ls may he s u bsequemly co vered b)' nth cr deb ris. A It er glacial retreat, the ice in the block mel ts, leaving a depres sion in the lands ca pe. These depressions or kettles ti ll with wa ter, creating lakes and swa mps. A relat ively large kettle is s how n in Figure l~ 56a.
•
14'
560
Sle r r a
;'\ 1,"\
Remote Sens ing of Sa lls, Minerals, and Geomorphology
ada 'fountain Ra nge in Califo rnia
F'9ure 14·54 Land:;,.,.1 \ISS ha nd 3 (ncar-mfraredj irnag... of La ke Tahoe in In... SI\.'fr.I ~ evada o f Lahfomia draped 0\ cr DcfL'TlSC ~la rPing Agency Levet-t Digital Terrain EI.:\ arion 0 ,,13 l\ cn ical exagg"r~lion is S:\} . In addiuon to Lake Tahoe. there arc also ....... enl stair-stepped glaciated valleys in the southern ponion oCth.. image Ih:1I contam lakes [courtesy USGS ~AlC d.a lab'!sc). A color \'ersinn is f011l1(\ ill ( '" lllr Plate 14- I Oc.
A drumlin is a smooth. oval- shaped (e llipticel) h ill o f glacia l till material w ith its long axi s parallel to the d irec tion o ftlow of the fo r mer glac ier. It is generally more blum and sleep on the g lac ier-facing end and mor e elon gated down -g lacier .... ith a thinning tail. Drumlins ofte n occur in clusters. re ferred 10 as drumlin swa rms. Drumlins consist of unsorted gra vel and sand mixed wit h some clay. There is much cantrovcrsy as to the processes thai produce drumlins. It is genera lly believed Ih
II)IN)..\1 osl sa nd gra ins moved d uring saltat ion on ly rise I 2 em above the g rou nd wh ile a few bounce I - 3 m. The repeated coll isio n o f partic les causes them 10 become increasingl y roun ded and smooth (and slight ly smaJlcr~ \\'hich mak ..-s. II c \ en easi er f,IT the pa rticles 10 become entrained in the wind field . AI'>I:I. some of the, encrg} of saltaring grains o f sa nd is trans ferred directl y III part icles on the ground upon impact. This causes tbcsc grai ns to 111('I\'C ferwurd sl ightly or creep. Extremely fine-grained silt smaller tha n ZOO urn may be captured in the first I - ::! km of a turbuleru atmosphere and moved great dis tan ces as dust. For e xample, npproxirn.ucly 10 em nfs lll has been dq)l~ ilt\l in southern Fran', from sources in A frica in the last 300 years. Thu s. part icles of san d arc tran sported in the w ind I"oy Sl) ;'pe nsion and sal tation. and o n the groun d by c reep.
Eolian Landforms
When wind erodes, tra nsports. and -or depo sus mat erial. il is ca lled eolian (aeolian ) acuvuy. WinJ l)pically- creates both eros ional and depos iuonallundtorms in coa st••l area s and in deserts. Eo lian land limns ma y develop wbcn there is an ample supply of sa nd and enough w ind velocity to mow indi vid ua l soil panicles . Good SO U T\.'CS of sand include: coastal and lacustrine bea ches . a lluvial river de posits. and material Irom g lac ial lill pla ins . Given a srrong w ind and amplc supp ly uf sand. the individ ua l gra ins of sand b ounce along the terrain through the p rocess of ""IIII /if", (Sel b) .
Sometimes thc b lowing, sahmin g sa nd encounters vegcunon or other phenomena tha t impede its forwa rd progress, III w ind " doci ty decrease s. ca using the sa nd panic les to be depo sited . Whe n su fficient sand is accum ulated . we have a sand dune which is defined as a mound. ridge. or hill of windblown sand-size panicles. This mound o f sand affects the n ow Ill' the air over the mound. (ienerully, the wind speed is greatest on till' w indward (up w ind) side of the mound and decrea ses un the lee ward (s lipfaccl, wmdshadow side .F igur c 14-57a I. The zone o f red uced air velccil) cnuxcs the sand to he depos it!.'J just beyond the lop ofihc mou nd onto the leeward back -slope (s lipfa ce) . Every size of
Geomorpho logy
y
561
lateral moramc
-
__________\ t~~---
sping
vcrn l
medial moraines
et. .\ 3.
lateral morame
Lat era l and med ia l moramc s o n Ba rna rd Glacier, :\ !\:.
,,The ome ler},
• 531 -
t rhc for-
suer tu r-
Fo r din ta rs.
terminal moraine
sush. Lateral and ter minal glacial moraines
a
I of
"''' i nd the nd0< -
t he, of
011
Hyle r lvlnnd. Balli n ls1;ltld. NW Ter ritorie s Canada.
Figure 14-5 5 ujlhgh -cbliquc aC IUl I plnuograph uf the Barnard (i 1,u: ;eT. AK. Ladt olthe tributary !;!lucicrs ha.s latc ralmuraincs. The connue'n ee o f the rrihuta ry g laciers .:rem.." med ial mo ra ines. The tributary glacier on the irnmcdimc right receives mate ria l fro m at 1c",IIIilC other tributary glOlcicr. us <, \ ;d<:11<:<.1.1 by the two med ial mor.uu..", wufun Ill.., cclllcr lO r it, 11m" lel' unes)' American (iL't>graphil"ul Soc iL'I) Couccuon 31 the Narional Snow a nd tee Data Ccmcr. I :ni\ of C olorado, Houldcr j. b) l.ow -ohlique pholu~raph url,ll.:ra l and tcrminalgtacialmoraincs 011 ll yllll ls l;lllJ . lta tlln leland. ill Ih,: CUIl;IJ I;ln 'II,,"hll C~l Te rritories.
sand gra in has a different a ngle-of- repose, i.e.•the maximum slo pe a t whic h loose soi l ma te ria l re ma ins stable. Whe n this angle is reac hed for a pa rticul ar sand t e.g.. .30 - ~Oo l . the sa nd pa rt icl es slide dow n the leew ard s li pface caus in g the
mo und to grad ually mov e
fO N
ard in the di rection o f the pre-
vail ing Il ind .
Sand deru~i l S mit)' to.: shaped m to a variety of bedforms including ripples (bctwc.....n 5 em and 3 m apart a nd 0 . 1 - 5
... ( 'Il , -\pn;~
562
14'
Remote Sensing 01Soils. Minerals , and Geo morphology
drumlins
•
a..·\ n esker and keute in Xort hem Man itoba. Ca nada.
b. Drum lins in Kcjunkujik National Park. Ca nada.
Figu re 14 -56 a t Lu w -obliqec photograph o f 3 si nuous, gravel esker an d oV;ll. slupo:d h'uk in the ho.lC\.'al fi>rs'$( o f Northern \{ ;m iloN. The Iigh l-loos-d a rea hi the left and righ t o f the es ker in tbc foreground life !'and de lta.. deposued b> ttl<: ~l~ into the glaciallalt that was formed as the glacier retreated. b ) Low-obliq ue aeri al phol Ob'faph of severa l drum lins in th e Kcji mkujl\ " :uiooll I'ar\( 01 Canada ICtlUT1("o.)' Ten-ol in Sciences I>lvi ~ion. (;,-olojl.ical SUf"'e) of ( "lInadal.
e m high). dunes ( .~ - t,OO m apa rt and 0. 1 - 20 m high ). and m",l{udum:.\ (3tlO In J km apart . 200 - 400 m high. and
many kilometers long). Of course. small ripples may exist on ind i\ idua l s and dunes a nd rnegad une s. Th is discussion focuses on dunes and meg uduncs.
All d une types may occ ur in three forms : simple. co mpound. and com plex . SimpIL- dun es arc ba sic Cornu. wuh a minimum numbe r of SIiP!:lCCS that de fine the gco m ...tri e type. Com{101m" dun es are large du nes nn which smalle r du nes of sirnilar t) pe and sli pface or ient alIo n arc supe rimpose d. Compler d unes arc co m binations of IWO o r mor e du ne type s (Walker.
Ul·llUli tilln al [ lilia n 1.1I ndfo r m\
Il)lJlo! ).
Mo st dunes arc co mpose d o f medium gra in-size quartz sand; howeve r. they ma y 1I 1 ~ o he composed o f volc an ic ash. ca lc ite. and even gyp sum panicles. The re arc a var iety o f dcp c sition nl sand dune type s tha t have characteristic dC\iClopmenta l eyries an d di agnost ic shapes that can he recoguizcd in aerial photo gra phy or other imagery. Scientists have co mpiled inventories of the major type s ofd unes found througlunu th e world an d how th e d une s appear in remo tely se nsed data . For example. sec work hy Rinke r ct al . ( 199 1), Dokka ct al ( 19\)7 ), and Wa lker t 19X(,; I"Nx),
Crevccnt rjc: Th e crcsc crunc dune is the mo st common dune on Earth (and Mars) . They arc gene ra lly mure wide tha n they arc loug. Hascd on the work o f Baguold ( 1941), these dunes arc o fu-n re ferred to as barcha n. ba rchaaoid, (If transverse dunes. Barchan crcsccntric dunes such as those shown in Figure 14·57b,c may be produced when I ) the prevailing w ind l"ll111CS frnm a urn form . consistent direct ion. 2) the re is little vegetation present 10 ancho r any port ion uf'thc d une , and J) there is a relatively spa rse su pp ly of sand. The two horns o f the c rescent point downwind. The gent le windwurd slope is usua lly < IS°. T hc leew ard, slipface side of the barcha n dune is sh:l.' pes t with an angle-of -repose ofapproximald ) 34 - 4()" for dry sand. lndi vidual barchans or cx rrc mcly la rge lIlegaha rdmn ~ commonly occ ur in elongate c hains or train s that ma y merge with coale sced dunes in tid ds or ergs. Small ba rchan " move se veral me ters per year, but mc gabarchans me v1.' more s lowl y (Walk cr. 19981.
T he earli est sig nifi cant work o n the phy sic s, orig in, and evolut ion o f eo lian sa nd dunes was performed hy Ralph Bagnoll! ( 194 1l. who work ed in Egyp t prior to wortd Wa r II. Il l.' rectlgni / ed two basic d une type s: the crcscc ruric dune. which he c alle d "b arc han." and the linea r dune. wh ich he ca lled longitudinal. or "scif" (Arab ic fo r "sword"). Unfortunately, his tcrmmology wa ~ then app lied 10 many ot her types o f d unes, rc.... ulting in a be wild ering te rmin ology, Th is secnon utili;..:s the follllwillg d une classificat ion sys tc m ada pled from sc \ cral sou rel.'S (Wal ker, IQ~f> : I
!.i ncar; Linear (or lun ~ i t llu ina l ) d unes may be straight or irregularl)' sinuous. t\ 10" -ohliquc photograph o f a linear dunc in thc south c-nd o f S..lt1a La ke is shown in Figure I+. 5Sa. ThC'M: dunes mil)' b< llIany kilom ...tcrs lo ng and hundred~ Ilf m...lcrs high. They arc gl.'ncrally co mposed (If loose,
563
Geomorphology
a. Sand movement nn a dune
.
.'
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... . -
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.. \, r
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.,
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:
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,J
.
,~
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b. Oblique view of crcscemnc dunes catted barchan Of tranev "r~" dunes)
c. \ 'kw of a single crescentric du ne
(al~l
n
e I.
)
e
Figu re 14-57 a) ( Ieneral charactcrtsncs <,1' 1101'1 sand is moved through sahanon and creep nn a sand du ne. This illustration is keyed 10 the wind direction and feature s in \ 0 ). b) Several crcsccr uric (OOl"l: h,1I11 dunes on the coas t of Peru migrat ing from right t(1 left, par alle l wuh the wind duecnon (courte sy U.S. Geologica l Survey: Walke r, 1'/<1101; ami Jnhn ~kCauky ). e) View " I' a single crc ' c cntric. barchanoid dune (cou rte sy Desert Processes Working Group: Rinker et al.. I"N l ; Dokka ct al.. 19') 7).
well-sorted very fine \(J med ium grain sand. Extreme ly straight. linear dunes are o ften referred 10 as ,\,( /1111 ridges. whi le the linear, sinuous var ieties arc o ften ca lled .wi6. T he leng th o fa linea r dune is much gre.ucr than its width . While the crescemric dun e is the most com monly occ urring d une. linear du nes cov er more desert area. esp eci ally in central Aus tralia . .s outhern Africa. the Arabian Peninsula. and parts of't he Sahara. The la rges t
ulso play a role in the ir deve lopment. It may be tha t the length of the d une is enlarged when the wind nlow s in the predo m inant direction. The width o f till.' dune is enl arged when the wi nd blows strollgly at right ang les to till' prev a iling w ind direction for relatively brie f period s of time. A n ex tens ive SCi! of linear dunes is shown in the Space Shunk photo graph otthc J\lar/ uq Desert ofl.ibyc in Fig ure 14-58b. Dome Dunn: Oval or circular mounds of sand that gencrally tack a slip face arc called dome dunes. They are rcla tively rare . Figurc I 4-5Xe dc picrs a ste reopair (11' do me dunes in the w estern Shicld o f Saudi Ar ab ia. The domes arc partly separated by interd une hollows tha t are en c losed by subsidiary dunes of hard-pa rked sand .
The origin of linear dunes is co ntro versia l. Some suggest that the linear d une s are pro duced I:oy un idirectional winds and that the alignment o f the linear d unes is par-did ..... uh the
Star nunes: St:lr d unes may develop where there is an ample amount of sand and the ..... ind blo.....s in many dircc-
w ind direction. Others suggest Ih31 mult idirectional winds
nons. They arc a lso called pyramid or radial dunes. Three or
01,\ 1'1EK
564
a , Obliquo:
\~
or a lin.::u
l Jon~nudin;>11
14'
dune on Soda
Lak~ .
Remote Sens Ing 01So il s. Minera ls . and Geomorpholog y
b. Shunk pOOl<.>gfllph 1)( linear dUlk~ in the Manuq Do:.:-s<..-n. Libp..
Figu re 14-58 a) Exam ple of a linear (longitudinal) dune. Nore the phy, ical uhstrucuon cunsiug ihc majority of 'li nd to deviate from it.> course w hile some spi lls OWl' the lOp (court esy o f De sert Pnl<:CSSl'S Working G ru up; Dok ku c t 'II.. 1')<)7). b ] Black-and- white vcrsi ,," nf Sp an : Sh ull lc ph
111"
the AnTI)· M ~ p Ser\ icc: courtesy or Desert Preces ses W0rldnl! Group; Rinker cl .11. I'N I: n ul la el .II. 19"7).
mo re arm s of sand typica lly radiale from a high ce ntral mou nd. Th e arms can vary in leng th. width. num ber. and shape. but eac h has a slipface. Star dunes acc umula te in areas w ith m ultid irec tion a l w ind re gimes . Sta r d unes tend to inc rease in he ight rather than migr at ing ho rizontall y across the landsc ape. ca using them to tJC one of the tall est d unes
found. They may reac h 211Cl - ]llfl m In the great deserts of the world. Star d une s a bo occ ur as sec ondary de men ts on or in co mbmauon with oth er du nes. A single sta r du ne in the Namib Desert IS sho..... n in Figure 14-60a. and a Spa ce SbuttIc pho tog raph ofstar dun es superimposed o n linea r dunes in ,\ Igeria is show n in Figu re 1~ " M)b.
565
Geomorphology
Nam ib Desert. :\am itJia. Arricll
Ftgure 14·59 Looguudmal JUIl~"S in the: l'\amib Desert in Xanub-Na ukluft :"ali"n..1Par\.. r~""1....dcd by the Landsat 7 EP.,1+ on Augu~1 12, 2000 These arc: the lalle~1 dunes in the world. some > JllO m (almll~l <,ll'i0 IH (.:tlune') l 'SGS and ~ASA). Refer 10 Color Plate 101-11 a fur a \ i..:.... of a portion uf the lkUrIC urea rec orded by Ihc ASTER sensor.
m its " hill' uncs. JlS< H1
!d by
-ts of m or "he
ib utes. m
Parabolic Uum'\: A parabolic dum: ha-, a crescent. U· sha pe like a ba rc han d une l:J.("{'p l lh3t its horns point in the oppo site d irection into the wind. They are also called U· shaped. blowout, or hairpin du nes. Parabo lic dunes are ereatcd 1-1 hell wind is sufflclcmly intense 10 literally blowout the cen ter of a du ne- but a rehnivcly small amo unt of \ egetation Oil either side ca uses the edges o f the dune to be sta biIizcd. Someti mes the horns of the parabolic dune remain attached to the vegetation for some lime as the main bod y Il l" the dune migr ates do wnwind. w hen this occurs. the parabolic dune resem bles a hairpin lying on its side instead o r a neatly shap.:d barcha n crescent. Parabnlic dune s arc alway s associated with vcgctarion - grasses. sh rubs, and uccasionnltrccs tlun anchor the trail ing anus . They usually form in areas with stro ng umdirecnnna l winds. I.o r's : As a continental glacie r retreats, it may deposit gla-
cialnll in all ou twas h plai n. Stro ng winds blowing fo r millcnnia ove r the ou twash plaiumay ex tract the small. si n-size particles. These wind bornc, sin- size pa rticles may he deposited du wnwind fW ill the till plai n as II laye r of IOt'." I' soil. For exam ple, the thickest know n depos it o floess is 335 m on the Loess Plateau otCtnna.Loc« accumulations in Europe and in the: Ame ricas resulting from the: Wiscuns in glaciation are generally 20 - 30 m deep . Loess is a very highly erodablc soil thai is usually j ust 3 fe w feet thicl.. Drainage cha nnels in loess so il often have very steep banks. Dunes arc not gcucr-
a ll) limned on loess de pos its. beca use of increased co hesion between the Itles S soil panicles . Enl\iullil l t';olia n 1.II11dfurms
Blowing sa nd can a lso produce impressive erosiona l features. T he kinet ic energy ofwind acts UPOll the ground surface. So me ofrhc ene rgy is transferred 10 the grou nd as heat while some ofit detac hes soil part ic les from lite' ground and moves them along through salta tion. When material is remov ed from a S Url~ICC via wind, we have de flation. The cont inuous remo val ofboth sand and sill from areas with an allu vial depu sit lea ves onl y a comb ination of coa rse sand nnd pebbles and some d ay mater ial. This can resu lt in the creation of ;l desertp,n·t' llwlIl landsc ape wh ich is a sheetlike surface of rod. frag ment s that rema in after wind and water have remov ed the fill ': particles, Almost half of the Ea rth's desert sur faces arc stony de flation zones. Desert pavement reg ion>. are culled I"l:K~' in Algeria. ser ir in Libya, andgibbcr.\ in A u-aralia. These deflated regio ns may be ve ry extensive in large dese rts. A de flated basi n is ca tted a blowout. Sometimes a dar k, shin) dese rt varnish is found on the desert pavem ent surfaces produced from manganese, iron oxides. hydrox ides. and clay minerals. Ihe surfaces of rock bodie s may also be erode d by ab rasion and sandblasting by wmdbomc particles. In extreme cases the wind may he so strong that it cuts channels in the less
C HA P IER
566
14
a. Star dunes i n the Namib Desert.
Remote Sens ing of Sa lls. Minerals, and Geomorpho logy
b. Space Shuttle photo graph of the complex linear F rfcrnm c Dunes in the Ta s~i l i ~ 'Ali<:r of southeastern Algeria supe rim pose d with sta r dunes.
Figure 14-60 a ) Large-scale aer ial photog raph ofa sta r dune in the Namib de sert . Each star d\lnc consists o f mu ltiple arm s ..ac h with the ir own slipt:,,·..., radiating from a central area. Star dimes are produced by winds W illing from multiple dirccuons (n lurt<.',y USG S; Walk er. I')98). b) Blnck-nud-whitc version of Sp;ll·c Slnl1lk photognlph ST so70-70:". O'14 o f the 'l'ifermnc Dunes of Alpcri;1 in July, I'N;. Extremely I,m!!. Itn"lIr d unes arc pre sent. The linea r d unes ha ve star du nes S UI)<; r i lllllU~J un pu rti,ms of t hem. Resistant. weathe red sandstonelies 10 lhe so uth and ca st ~md appe ars in dark ton es. Se ve ral while" pla yas arc present in the image (cou rte sy NAS..\ Jo hnson Space Ce nter].
res tsta m roc k. leavi ng residual streamlined ..pines ca lled
uoc co. Ii . Vda7quC1.. A . and C Siebe. 200 S. " Usin g t teomor-
.m n./ung l. wh ich may be tens of mcrcrs high and kilomet ers long,
phulog ic \ la pping 10 Sne ngjhen l\alurat RCWUTCC ~hll3gc· meru in Develo ping Cou ntries," Cat ..ne. (,0:23<,1 - 253.
Ch al:lrillal. S.• GoeIT. /I.. F. II.. Krosley. I.. and II. W.
References
Oh~,
:!OO2. " Use o f Hypcrspec ua t Image s in the ldenuflca tion and Ma pping u f Expansive Ct ay Soils a nd the Ru le o f Sp atial Resulu l inn.- Rt''''o/,' SI'IHl IIJ.: "JEnl'irullm "/II , 1'12:4 31-44 5. AS 'I f-. R. . 2U1l6. A d l'llII<,<," .1,"
("]ar ~ ,
Ba ld i. P.. Fa bri s. M.. .Marsella, M. and R .."' " nlied li, :!OO.'i. - Mo nllo rmg the ~ l orp h o l o!! IC 3 1 (-vo lutio n of the Sci ara del Fuoco dur ing lhc 2002-2003 Stromboli Eruption using Mulutempora l Phorog ramns et ry," /SPRS Jo"rtI~1 til Pllologramm,·In,' ~ R" m(ll" S.. nun~. ;<,1: I W -211 .
Che n. J .• Zha n g.
Ragnol d, R_ A .. 1<1 4 1. The 1'11.1'. 1;0 oJ RlolI" -",md uml On " N /)l/l1e ••
Lo ndon:
~ Cl h u e n ,
2f1.'i p.
fk l nilp. J., 2003. "T he Wo rld at your Feet : Desert Bio logica l S...il Cr ll sl , ," 1-"1'""1 /.,,-,, ;11 f.'r otoR\' un" III<' Environme nt, l( S ) : I Il I - I ~ <) .
R. N.. I')')'), "Sp ectros copy u f Rucks and Minerals. and Princip les of Sp cct rnscn py:' in oHm"',,! ol N"IIIfJ //' S('IlI;ng <;.·0\('...11(-, «. A, R. ~ nCT. ( Ed .) , ~Y: Joh n Wiley.
~ . Y.. Wang . L. . Shimazaki. Hiand M. Tamura. 1005. "/I. N.:\\ tndec for M lIpp i n ~ Lichen-domin ated biological Soil Crus ts in Dcecrt Areas." R,'mo',' S<"Ining tlJ Em';"",· 111<'11I. <,1 6: I f15~ I 7S.
t:ern andes da Silva. p, C . Cr ipps. J. C. an d S . M . wr se. :!OO5. "The use of Re mot e Se ns ing Tec hniq ues a nd Empi rica l Teeto nic Models for In fere nc e o f Geological Stru c ture s: (Jri d ~i ng fro m Regi onal I" Loc al Sca les: ' R" mo lt' S"II-'i"8 "I E"l"{nmm e lli, 'l o:I I'l-3h
567
Referen ces
Dalton. J. IL n o ve. D, J.. \1 lil,l inie h, C. S. and II. W. Rn.:k1.\- e ll, ~004. "ldc ntif'ic auon u rSpec tra lly Similar M ~ to:ri" b,lls i ll g the USGS Tcrracordc r Algor ith m: the Ca lc ite -epido te -ch lo rite Problem.' Rt' mof. ' Sell""~ "f Em 'i n m", e",. 1\9:455 -41'>6 . Da vis. H. A , and J. R. Jensen, I<)<)x. "R emote Sensing of M anl'ro \ e BrophysicalCharacierisucs." Geocarto Imi.. I J :55---{w. Do kka. R. K.. ~ l u } <.'r. L.. Rinke r. J.• Wa lls .L Wakc fletd. G. MeCauley. J. f. anJ C. Breed. J'1'l7, .\lDEP Surfu<"t' .tIaferiu/5 .\ lapp ing em"p 1)"II
Fll is. R, J, and P W. Scott . ::!rlt14. "Evahiation of Hyperspe ctra l Remote SC'llsing as a \t ea n ~ o f I::II \ i n," m~ t4 1 Ml>l\ ito ring in the SI. Au~ tdl ChinJ Clay IKaolinl Reg ion. Cornwall, UK:' Rem"'.' .~"' III1r of flll'ln",m.'11I,
Ji'L. 2(1111>. AST1:'X Sf'.:"'''al f.jh,."'T. Pasadena : NASA JCI Prop ulviou La b, hllp:flsped ih.j pl. nasa,go vl, King. C .• Bdl> hdadi . N.. Lecomte. V, OInt! D, Ccrdan. 2005. " ThC' A pplicatilln or Re mote S.'nsing 001101 to \tnn itnr ing and ~I"d ~ ellmg SOil Erosson." ("<11..11(/. ;' 2:7<) - '-1 3. Kruse . F, 1\., Kkn:III- vo ung . K. S. a nd J. W. Boardman. two. "Mme ral \Ia pping at t'upruc . Xevada with A ej-channet ImJ lling Spectrometer.- 1'I",wxra",m." rlC DI~I"'i'erm~ anJ Rt'Rill'" S"II.•;ng. ~(,( 1):l<3 9::!.
Loynachan. T. ·L. Brow II . K. W.• Cooper. T. II. an d M. tJ . ~ 1iI ford. IQIW. S,,, ,mlllflg (}IIr .
W. M , and J. D'llil.'f, l(jll i. Landl""I"' ; .-In 1",,,,Juet;oll 10 I'hl ~"o,1 (ll'''}!,""phy. Rea ding: A ddison Wes le}'. ;' 37 p.
\1 a r ~h ,
( Ialv ao . L. S .. A lmc l{la· f ilho. R, and I. vnorelfo. ::!(KI5. "SJ'<:'Ctral I>lserimi llJlion of lI )d rotherrn"lly Altered Mate ria ls using AST ER Short-wave Infra red IJJ n d ~ : Evaluation in A
Tropical Savannah Environme nt."
/1" ,. Journal
01 April",} Eu,.,;' Observation ,.m,} C.'"III("ml.llwIl. 7: 10 7- 114. Hapke, B.. I'N J , Th"" ,..!' "IH"/1ec /,mee ,m Il 1-:m ll/ul/('" S{'<"·/,.,,,,('(-'1')'. ~ew York. NY: Ca mbridge Uni vers ity Press.
en.
nd
Hoffer. K., I'17X. " lIwlug ical and Physical Co nside ration s: ' Rc"'",.. .'1,'11_' ing: Till' QI"ItIII'al I "•. .'IPI' I'IJ
\t eC au l,' ) J. F.. Schaber. fi G . Br.....d. C. S.• G rober. \1. J.. lIa} lIes. C. V., Is-aw i, II.. Elachi. C, a nd R. m om, 1'-Ix::!. "S uh,ur facc Valle> s and (;eu- Jreh "e olog)' " f the East ern Sahara Rl' Velde<1 hy Shu ll Ie Rada r," S" ;,',,n'. 2 1K:I (lU4-102(l. M cuc rnicht. G I. and J. A . Zinc k. 20 03,
" Relllllll' Sensing of Soil Sa lini l y: l'otcnnals a nd Constrai nts." 8,'''''''1' S(',,-,inJ; 01 Knvtrnnment, KS: 1- 20 ,
Mojav e Dese rt EC
esHook . S, J.. Dnwl·hu l>.s" i. J. 1: .• How a rd. K. A .. Rowan. L. C. Karl- tnuu. K. E. and J. .\-1. Stu,·", ::!(}05, " Mappi ng Variat ions in Wd gbl Percent Sil ica Measured tT()1J1 Muluspcctral 'l'h crma l In fra red lma pc ry," N,'"", /;: S<'II.\' III):: 1::111';"0111""'11/. ')5:273 :!IN.
or
\ nl" 11/ l ' lYJj! I"II Hied/lill ie I h u"ha" e, Wash ington : Dept. or Defense ilnd usnl. II CD s an d maps. o u», G S, and T. 11. l'uituer, ::!1I04 , "E ffect or Grain Size on Rcmotcly Sensed S l'ectrnl Reflec tanc e of Sandy Deser t S urfaces ." Rem",,· S"/I"ill~ 'il fm 'i rolll>l ,,>II. K4:272_ ::!KO ,
•• i· ,.
l toopcr. D. M.. Hursik . ,\ 1. I. and 1".1 1, We bb , 2( 1)). " App lic atio n nf High -resolution. tmcncrom cinc DF. \-ls III Ge o mo rphic
Per gola. N,. Marchese , F. and V. Tramuroli. 200 4, "A utom ated
Srudics or I;a ull S,'urps. hsh l.a ke Valley, Nevada-Ca liforn ia. USA." RI·",,,/,· S"".'III,~ '1/ EII.';m"''',·"I. 11 4:255-267 ,
Detection o f Th er ma l ~ e ;l t llre s " I' Ac tive volca noes by Mea ns of Infra red AVlI RR Rli co rds." Rcnwl.· Sc m illg vi Ellvi f
,••.
Hunl. o. R.• IY7 7. " Spectra l Signatu res of Particu late Minerals in the Visihle and Ncar -Infra red." G. ·uph,nin. 4::! : 50 1-513.
""'11'. 'H:31 1-3::!7.
• >
P<: l er~ en ,
G , 1')<)1) , correspondence. Pres ide nt uf the Soil Sci-
enc c Socicty of America. Pen nsylvania State University.
Ja mes, A ., 2()()h. curre~pondence.l!/eulJ1orphologlsl in the De pt. o f Geography. Lniv. o f Sout h Carolina. Co lumbia. Sc.
Rae. B.. S"nl..;lr, T., Dwivc di, R,. Fhamm a ppa. S.. Vcnkataratnam . 1... Sharma. R, and S. Da s. 1'-14 5. "Spectral Be ha vio r of
568
( 'Il A I ' n :R
Salt-affected S,lils:' Im l 10:2 1~5 -2 1 Jt. .
)Il u,."al (!f
14
1("1>1""-
St'", i"X.
Remote S e ns in g o f Soils, Min e rals, and Ge omorpholog y
n- Sci"lIccs : .111 " 'I"J,!ralt'd
nerd . J. and It. \1 , Hazen . I'N5, Arl'l"tXKh. "Y: John Wile) , /iH P
Rasher and weaver. I(NO. HO'i< Phowlm.-rpre/mwIJ. Washin g Ion : So il Conservation Service. Wilh phulugrup bs ;.I lld s liJcs.
USDA, 1')<)1'1 . A" :I',' 10 S"jf T
Reddy. G P.O., \i..jr, ,\ Morp homet ry and ib in a Uasa llic Terrain. GIS App roac h." Inri
USDA , :!OO3. A·.·,l" to S"jJ T
K. and K. S . ( jajhh l)c. 2U0-4. - Dramagc Influence 01\ LallJ f" rlll Churucterisrics Cc nlr a ll ndi a - " l{cmOll' Scn~lOg: and
)(>110 1<11 n.( AI'f,/ied E",.,J/ ",,,I Ge"in for m" II,m. b : I - I b .
J{ encv. A.• (Ed. ), I'N 'i . H,WIIl,1,,{R,-,"oIl! .\"'/1,"",1.: ex, :-.I)": Joh n Wiley.
ta..
()b.a"'~liu"
/J'·lJ.I<"it'Il,··
Rinker, J. "I .• Breed, C. S.. ~ cC a ~ k) . J. f. and F. A. Cord. I'N l. R"/I"'lt, St'II,,-j,,);! Field GI/ide - Dew,.I, Fl. Belvoir: U.S . Army Engin....r Topo graphic Lab. 5 t>X p., htt p:!wlu• .tecarmy.mu t~rralnldesen covcrpg .htm . Ro wa n, L c: Crow ley. J K,. Schmidt. R. u., Agc r. C. rl1. uud J C. 'ob rs. NOl). " \ Ia pping Hydroth ermally Altered R..cks h) Anal YL ing Hypcrspcct ra l Image (AVIRIS) Data 01 Forested Areas in the Southeastern Umted 'crates." J ournal fir (;,.". hell/k"t 1:.:\1,1,,/,,1/1011. {,X: 145-·1 (,6.
Salisbury. 1. W., Welter, L. v , ve rgo. :'\. and D. \1. I>'.-\ ri.., 1'19 1, /l11,.,,/'.'d (2.1 • 2S p lll i S"""I"" "1,\Ii"...·,' I , , Haltlmnre : John Hopkin s Univcrs uy r re ss. 2n7 p. S...lb) ..VI. 1.. 1'1~N. E" r,h j- C/"'''lling S",/""t': ..." Inln " III"/ It'" 10 G,·"m"rf'h"I"g:.~ (" ford: C larendon Pre ss . N17 pSh ... ltun. l . S ., 19(>6. G,'''/''XY IIfll ,
US(;S Spcclah, ! lll/fl. L ,W;S f) ,gu'll .'O,,1i1><.4 S/",,·/ral1.ibr,Jr)' 0.2 III J ./J m;..,."I>I<"I<'I".•• Wash inglUn; USGS, hup:!:sp<'L'I11h.e r.us!!s.gov /.;pcetra l.ll hIl4Is re'·l ra l.l ih04,hlml. Yan dcr \leer, F., \ W 4, "Th... Extractio n " r Mine ral ,\I' SMJlllOll Fealures from Il igh-Specl rnl R,'sl.lullun Data lJsin~ NonParame tric ti cos t.uisuc al Techniques." Itltl. Jo"",,,1 of RI'"wl"S" m ",!:, 15 :!1 9 3 ·2! 14
Wall er. ,·\ . , .. II/XII. -L" lian Land fo rms." in Shurt. N. M. and R, \V. IlI.Ii t. G"""''' 'l'h"I''.l!j' jm", !l/"'<'''. A (i!"nt/! (h·t'r rh·l! "I RI-gtm.nl l.ml.ll"r,., . , Was hmgton : \I -\'>A, 44 7- 5:' 0 . Wa lkcr. A , S ,. 1" ')X, f),',,""" ; ( ;""(Ogl ' m,d N,·s""n·,'.•, W3 sh i Tl~ ton: U S( 'S. h llp :lJp lII'> S.USl.-! s.gu v,g ipi\lc sert sic ,>n!Cnls,
Wal ch. S . 1.. BUller , 1>. R.and ' Cla ssific ation h;l','d on the Br-dirccucnal Re flec tance Distribution Function Samp led b) Aed;>1 I'h.. tog raphs." em.-"" . b:!:q4-l l fl .
Sho rt. .~ . M. and R. W. Hluir. PJIll), G' ·"'"iJ/l'h"lt>gl'.fi"Ol1l Sr'''''', A CI,,"',/ On·n·i,..,· 01 He-ginn,,1 /'wld fi".nn . I'\AS.-\. Wa-!>hin g· ton. http:! daac.gefc.nasa.gov I/OA,\('_ DOCS/uaae _cd.h tml.
\\'-a ~ .
Strain . 1'. and F. Ingle. l 'IlIJ . ,-""kllIX Publishmg, 304 p-
Zribi. M .. Baghdad i. :-.r .• ll " lol h. :-.r , Fnfin, O. and C. Guerin. : nll ~. - j- vafua no n (If A R (lu ~ h Soil Surface Dc scnp uo n with AS ,- \R+NV1S,\T Radar Da ta: ' Sen sing "I
<1/
I'"r/h. .-\ II
D S, and J, R. En' fell . I'N 7. '"Cha pl,'r 3: Landforms and
Geolog y," \{""/lal '!( Plw l"g ro!,h ;c Im ,-rpn'I
R,'",,,,,·
Swayze. ( i, 1\., Cla rk. R. N.. (i"el/. A. f. II.. LiHI. K. E. and S. S SUI ley. 1'1'1'1, "AVIR IS l'I'I t-; Low Alntudc Versus l llgh A I. titude Cump;m",m ( h er ( ·Uplif.... ~ e\ a,b :· Denver: LS(j ... hll p:" speclab.cr.usgs.gov I.
"h·//I.').'i:(,i 71•.
E,..·",...·
In Situ Reflectance Measurement
I
15
n s itu spectral renec tance measureme nts obtained on the grou nd using a han dheld spcct rorud iomc tc r call be used to : gai n ins ight intu [he spectral reflectanc e characteristics of selected mater iels: ca l i brate rem ote sen sor data : and provi de unique spectral data for impro ved mform .nion extractio n usi ng mu ltispec tral and hy pcrspcctrul remot e se nsor data .
ln "'"11I spectral rene-cnaucc data are ottcn col lected by scientists simply to gain insight into the spectral characteristics of Earth-surface materials (e.g .. Bahiag raw). Add itional knowledge about the material can be ob tained by subjec t-
ing it eo \ arious treatments tc.g.. application of different amounts of Nitrogen to Bahiagrass ) and determining if the trea tments r esul t in different spec tral reflectance patterns. The various tre atments and the ir spectral re fl ectance characteristics ca n be: monitored th rough lime 10 obt ain additio na l insight. Scientists often create spectral reflectance libraries o f the materials found in thei r stud y area. Se vera l publi c age ncies share the ir spec trallibraries via the I n t ~'01 ":!, e.g.. U.S . Geologic al Survey Spectral Library 115 (C lark er a I., 20()]) and thc ASTER Spectral Libra ry (ASTER. ~OO(i ) . Rcmot... sensing systems collec t spectral reflectance data o f the terrain in the visible and ncar -in frared tVSIR) and short-wavelengt h in frared lSWIR) pornon of the electromagnetic spectrum l O.35 - ~.5 p m ). Atmosphe ric sca ttering. ab sorpt ion , and reflccuon often impact the energy reflected from the terra in and recorded by the remote se nsi ng sys tem (re fer to Cha pter 2 ). Fortuna tely, remote se nsi ng-derived sp ectral reflectan ce data ca n hi: corr ela ted w ith i n .Ii/II percent re fl ectanc e dura uf the same phe nomena ((I CIlTT~'C t for aun ospheric effec ts {Tcillct et al.. 20(2 ). For example. a 3 x J III plot of'Bahiagmss on the ground ca n he measured using a ) a high spatial rcsot uuon airborne multispe ctra l scanne r. and b ] a ha ndhel d spec troradiometer. The remote sens ing data may be co llect ed tho usand s o f meters AG L. The in situ specrroradiomcter measuremen t is typic ally collected ep prcximatcly 1 III abov e the canopy. Numerous paired airborne and g round-based spec tral reflecta nce mensurem cms (c.g.. 20 to 301 ca n be used to calibrate (adjust) the remo te sens ing-derived spectral reflec tance measurement s. to min imize the etfccts of uuuuspheric scauer ing, absorption. and reflection (jOel/, ~nn~ ) . T he result is a calib rated remo te sensi ng data set that often y iel ds more accurate la nd cover or b ioph ysica l information (e.g.. biomass . lea f-are a-inde x] than an uncnlibrared dataset.
569
570
( ' H A I' n :R
15
In Situ Refl ectance Measur ement
Spect ra l Reflect ance ;\l e3suremenf Using a Handh eld Spect rnrudlomet er
Referenee
Targcl
(Sp l'crrfl hm Plate)
(4:'.g.• B(/hill~r"_H )
-
Refl ecta nce = Target I Reference
--
•,.
-
'.
eO<
,..
.,.
. ,.,
_.....
•
' >0
.,.
.,.
."
".
II'<'
...
I»"
w.......
,. Figu re 15·' A spectral reflectance curve of Hahia grass obta ined spect ra tc.g .. a " hile Sp..'Clrnlo n referen ce plat e).
c.
b. b~
//1 sltn spect ral reflectance data from almost pure Earth surface materials (e.g.. hea hhy full- canop y Bahiagrass. fresh asphalt. Jeep-clear ....
Spec tral Reflectance of a Material
• The proc e ss of ob taimn g handheld spec tra l reflec...ance measu reme nts is intriguing . To obta in the re tlecrance s pect rum
d i\id mg the target spectra (I lilhiagr;lss
In
this C\ 3111I'h.·) t>~ the reference
nf a target ma terial, PI' it is neces sary to onta in 11,','0 spectral mea surements:
I. the amount
"I' radiance reflected
wavelength interv al trom Spcctrnlon plate):
11 rt:(I'I"t' I/{ 'P
in ;1 specific sample. f. , (e.g.. a
2. the amount or radiance reflected from the target of inte rest, 1. 1' in the same wavelength interv al (c.g., Ilahiag rass).
The renccuncc spec trum. p " . is computed by dividing the spe ctral res pnnsc o f Illc target of inte rest hy t he spectral response o f the re ference sample:
PT =
L, -x L I.,
(15·1)
T he correcuon la ctor (kl is the rano Ill' so lar irradia nce to ref-
crcncc plate exuancc and ideally should be nca r I ( McCoy. :!.OO)). An e xamp lc o f re fe rence __pcctra (Spccrralon 1, targel
Referen ce Mate rial
571
Ill umination Considerati ons
e
O.\lH
" ow, E 0 o. ~ •• 0.\12 •
,,
,
0.'" O ~~
250
500
7'0
I~K)
1 2 mt 5 00
1 7 5 n2Iro
22 5 0
2 ~K )
Whe n com puting the reflectance spec tru m o f a material in the ficld or in thc laboratory, it is impo rtantthat the illum inatio n charac teristics o f the referenc e mate rial (e.g.. Spec tra!\)l1 ) and the target o f intere st (c.g.. !3ahiagrass ) rema in the same .
Wa' ''.....C'b. nm
Agure 15-2 Spcctr.d rdk'clanc... cheracrcnsucs of a Spcctralon pIal'· over the.' spectral range 2~1l - 2~()() nm mensurcd in the 1;d:...,ral\l[) under comrulled artificial illumination. The reflectance ru n e d......s nUl exh,t-it the atmosphe ric absorption bands that arc present when measurcmcms are obtained in direct sola r illumiuanonas shown in Figure IS- Ia.
spectra (Bahin gm ss }, and percent reflectance o f Bahiagms s is demons trated in Figure 15-1.
Refe ren ce Material
" Ic a 1
J
Spearakm is th... most wide ly used reference mate r ial " hen ob taining insitu spect ral re flectance measu rements. II is a thermoplastic white (o r gray ) resin that has dcmcnstrared the high ...st diffuse re flectance of any knllwn materia l or coating for terrestrial remote sensing a pplicati ons for bo th fiel d and laboratory ap plic ations. Space-grade Spcc tralon combines h igh refle ct ance w ith a n extrcm e ly Iambc rtian re flecta nce pro file , exhi!>iling reflectance values o f >99% over rhe wav e length rang ... from 411() 10 1500 nm and >95% from 250 In 2500 nm {Labsphere. 200 tl). Spectra l re flec tanc e characrc risucs of a Spcc trnlo n p late measu red in the la boratory arc shown in Figure 15-2. Spectralon plates range in size from:! x 2 x 0.56 in. up 10 24 x 24 x 0.56 in. Most scien tists use 10 x 10 or 12 x 12 in. p lates mounted in a dura ble 3110Jil ed a lumi num fram e . It is possihle.' to purc hase larger plates ba t they become d ifficult 10 handle in tho: licld. They are also wry expensive . The surface of the Spcctralon plate sho uld be ke pi clean from dust and de bris. After heav y usc it may he necessary to use w utcr and very-line sandpa per to restor ... the surface . Each Spcc rralon plate is calib rate d by thc manufaelUr...r. Ca libralion data from 250 10 25()() nm. e\Cry 50 nm i:s suppl ied with a Spt.'Ctralon plale . Cal ihralion da ta ar ... tracea hle to nat ional labo rntory standards.
A ny \ ananon in the illum ination characteristics bet" cen the lime the reference spec tra arc collected :1110 the time the target of interest spect ra arc co llected resu lts in error in the derived re flectance spectru m. Tha t said. it is usefulto rcv ic.... various scene illumination co nvide ranons.
In Situ Spectral Reflectance Measurement Using Sofar Illumina tion
Th e so lar energy reachin g the Ea rth's surface and the domi nant factors a ffectin g th e illum ination .... cr ... di-eus,...'1:1 in Ch apt ...r 2. They are revis ited in Figu re 15-3 for this hand held radiometry disc uss ion. wate r vapor impa cts the iocoming radiant flux the most (Gao a nd Goetz. 1(90 ), So lar ent"rg) reaching thc Earth 's surface is es sen tially zero in thc regions aroun d 1400 nm and \900 nm bec ause atmospheric wate r vapo r absorbs light in these region s ove r the lung path length of th c atmos phere. The great er the d istan ce that thc energy has 10 pass through the auuosph e re (i.e.• tho: path length l. the greater the a mount ofabsorption thaI ta kes place by the var ious atrnus pheric constituents , The amount of .... mer vapor in the atmosphere changes diurna lly and seasonall) and can vary in space o ver shtlft distances dependin g upon the characteristic, o f regional a ir masses. KeIlcct anc c spectra obtained in the field usi ng a handheld spcc trorudro mctcr arc infl ue need b) fi ve types o f sola r illumin ation . T he mo st dominant irrudiancc is dir...cr solar illumi natio n (E,,: path I) as show n in Figure 15-3. It may contribute as muc h as 90'% IIf the total energy illuminating th... ta rget under clear sk) conditions. Scasonal so lar eleva lion ang le HJl and atmospheric co ndnio ns (e.g.. high watervapu r co ntent ) will uffcc t the amount o f radiant tlux and its spectral cha racteristic s illumi nating the target. Figu re 15-4 documents the sola r irradia nce that actu ally mak es it to the Earth 's surface after pasving through the atrnosph ...r.... Sca tte ring in the at tllo:sph" r... res ults in d il1"us... sky ligh l illumin ation . Thl" ditlusc sky light usuall y accounts Ii)r 10-20"/. of th... tota l ...nergy illum inati ng the terra in. T he spl'ctral chara..:teris lics or J itTuse skylig ht illuminat ion ,Ire a ti lllct io n
In Sil u Reflect ance Measurement
572
III .filii Spec tral Refl ecta nce \Ica \UTelllCnl U s i ll ~ Su lar Hlumin ation Sun
Cl (>uJ~ l) 'r I:CI "",' l3r illu mllut io n. Eo
S pec lru r.ltl ",m"h"
•
[S]
Pa th
r.u liar;::..( () ,tlu.;e ",ky lrr.....ianco:
\~'
\"
~ In"lallla nc"u'" lidtl·...I'-H<•.'w t H'O\ "' o ( lhc .....n""l"~~"l"m
II H z ] m Ah lhKle " 00""
b'TOund lc-..d lAG L I
,f,ldili"",,1fac/on Iv <'
"hadow. OI:'arhy ot>Jcc l ",hadO".
w ind
1_ 0 _1 d iafll<.'\ '''' ohM gmund-r roj,"'l....t lf OV " n th e IalS'" .1'''01
Figure 15-3 Spectroradiometcr setup for obta ining in sim "lX'<"tra l rerl ec ta nce measurements u, ing solar Illumi na tion.
of the type and amount of atmosphe ric scattering and abso rption taking place. Some of this d iffuse sky illumination never reache s the target bUI is scatte red into the remote sensing instru me nt field o f view ( Ed: path 2). So me of t he diffuse sky irradiancc reach es the ta rget and is subseq uently refl ect ed into the rem ote se nsing instrument flcld of vic....,
Solar Illuminat ion l-l:ea chin2the
t:a rth ' ~
Su rface
Solar radiation at the to p of the atmosphe re
nearby terrain is retlecre d into thc rem ote se ns ing inst rument 's field of view (.t). Fina lly. the targe t of interest (e .g .• Bahiugrass} may be illum inated hy light scatt ered from nearby agriculture, grass . fo re st. or urban structure s (5). C urtiss and Usuu ( I98H) found that as milch as 20% of the illuminat ion ( In cleared forest areas ca me from adjacent forest cove r,
(Ed: path 3). So me irradian cc on
Th e irradiance that never reac hes the g round (2) and the reflecta nce fro m nearb y feature s on the gro und (4) are co nsidered to be noise and arc called p al}, radiance (L pl. T hus. the total rad ian ce reac hing the sensor (Ls ) is a fu nct ion oft he atmo sph er ic path rad ian ce ( Lr l a nd radiance re flected from tile target o f interes t (1.,-). Sever al atmospheric c harac ter istics also affect illu m inatio n, incl uding the presence o f d oud s an d wind . CI(J ud,\ are visual e viden ce Il l' wat er vapor in the atm osphere. C louds can modify the spec tral characterist ics o f the irradia nce reac hi ng the terra in. Th ere fore. on e might th ink that it is necessary to han ' an absolutely clear sky dev oid of
() 0,2 0,4 1) I'
U. ~
r.u
1.2 1.4 1.1,
I .~
W.1"c len~,h .
2.0
n
2.4
z.e 2 . ~ 3.0 3.2
j.lm
Figure 15-4 Solar illuminati" " read, ing the Earth's surface.
clo uds in order to o btain reflectance sJlCctra, T his is not the case. As long as the re fere nce spect rum (e .g.. derived from a Spcctralon prate ) a nd the t.lrgel spec trum (c.g., derived from Bah iilgra ss ) arc obtained under a lmo st identical clo ud-cover cha ract ensuc s (i.e.. taken in very rapid success ion j. ihen the subseq ue nt rauoi ng will reduce the error introd uced by atmospheric cl oud and wa ter vapor varia bilit y (clouds).
1,
573
In S itu Spectral Reflectance .\ h'a\ UH'mcnt U..in ~Art ifici allllllmin al inn
Tung.'\lt'l'i-Quart7lIotlogcn bmp
o
p
/I Alt itude above
tnstamuncousfield-o f-view
ground level
Tungstcn-QuartzIlalog~-n Lamp
fi rm') of tho:
(AGL)
M:nWf system
o
/1 - I m
I _D _ I Diareetcr of the ground-rrojeeled tFOV on tile laI¥~ area
Figu re 15· 5
SIX'l.·lroradu'm~"lcr setup for
obtaining i" ~j,,, spectral reflectance m.'aSUT1."ITICTlIS using amflcial illumination in a lab.
If the ill situ re flectance spectra arc going 10 be used 10 calibrate satcttuc or aircraft remote sensing-derived spec-Ira. then the ill ,f i lii reflecta nce spectra should he collected at ap proximately the sa me lime and under the same atmospheric conditions as the remote sens ing miss ion.
Hilld can play havoc when obtaining in .filll reflectance spectra . Vegetation ca nopics are particula rly suscc pnblc because reflectance spectra for a target typicall y arc not obtai ned in a ~ ing lc me asure ment. Rather. a Spcctralon reference measurement is made. and then perhaps III or more wrgl.: t measu rements arc m.nlc. T he 10 targe t spectral re n eeranee rncas urcrncnrs arc then averaged to yield a singk target re flecta nce measurement that is d ivided hy the reference spec tra to yield a calibrated reflectanc e spectrum for the canopy under investigation . Idea lly, the ca nopy rema ins completely st ill d uring the co llection of the 10 target measurements. Ideally, the leaves are in the same pos ition. and so arc the shado ws and the a mount of hare soil seen by the spectrorudiomctcr de tectors through the o ptica l instanta neous field of view (l FO\') Wind moves the leaves in the canopy. mod ifying the amoun t (If vegetation. shadow. and bare soilmeucured within the co nstant 1I:0 V of the spectrerad iometer, Wind can even cause d ifferent structural pans of the canopy te .g.• stems , the unders ide o f leaves) to he viewed dur ing dufcrcm scans. This introduces noi)e into the reflec tance mca surcmcms.
In Situ Spectral Reflectance Measurement Using Artificial Illumination in the Laboratory
Somet imes u is useful to obtain the spec tral renectance charactc nsucs (If grass , lcaves. or other land cove r subjec ted to various treatmen ts in a cont rolled laboratory environment. In a lahoratury envir onment. the analys t has con trol of: illuminatio n geometry based on the positioned and calihrared lamps:
IIS C
of carefully
spcr tromdiomctcr viewing geometry (usua lly poin ting at nad ir): environmenta l effects (e.g.. there is no wind . and it does nol rain in the laboratory ]: nrmospheric effects te .g., it ts possi ble to control the tempera ture and water vapor in the la b). A good configurat ion for indoor artificial illuminat ion is shown in Figure 15-5. It consists of two 100 - 500 \\ . Tungstcn Quartz Halogen filament lamps (each approxim ately .l 4 nO K color temperature ] placed in aluminum reflector housings. orien ted 30 0 Irom horizontal, and placed I m above the phenomena of interest (ASD. 2005). The power sup ply should he stahk-. The specrroradiometer optics are posuioned to \' ic.... the vegetation ca nopy at nad ir. Idea lly.
("IIArn:H.
574
15
In Si tu Refle ct ance Mea surement
Tung~ lt·n -Q ua rtl. lI a lo~l"n
J~
400
.J~O
.0;00
5~ (.t)(J
1150 700 750 ROO 1150 QOO
W,,' .:k ngth 111m)
Figure 15·6 Ibe spectrum of a rluorcsccmhgju.
the "CnO;OT fiel d of \ iew is compl ete ly tilled by the rarge mater ials of interes t (e.g.• Bahia grass ]. Can: must be exercised ...hen using artificial illum ination 10 collect targ et reflectance spectra. how ev cr. because exte nvive expos ure 10 the Tungst en-Q ua rtz-H alo gen lam ps can actually "c oo k" the vegctauon. Thi s can d egrad e the chloro phyll in the pali sade parench ym a and cause plant \\ atcr to hi: evap•orated fm m plan t spo ngy nicsophyll. These conditions result in spurious vegetation reflectance spec tra. Why TUIIJ.:.\l(·,, - Qllu rt;-lIuhlJ.:(·" ""Imillalit", ? Many sources o f light can toe USL"
Charact eri sti cs at th e Spectr oradio meter Used to Obtain th e In Si tu Refle ct an ce Spectru m Th e reflectan ce Spo.-c lr:l 10 be measured are spec ifi ed in the project experime nta l design . For example. perhaps \\ e want to collect Uahiagra ss reflectance spectra. There arc seve ral
500
eoc
IlXI(I
\\"a ", kn~l h
La mp
2l'IOO lo ml
Figure 15-7 The ' f'<."\: trum o( a run~ll'1l-Quart.l-lIalo~:t'n Ia.-np.
oth er important c harac terisncs that must be "pec ified to ob tain thc de s ired spec tra. inc ludin g: general spectral region o f interest. spectral rc....olu rion. spectra l ~ m p l i ng interval, spec trome ter desi gn, da ta colfe-ction speed. view ing georretry. and field of view.
Spectral Region of Interest
If rbc goa l if> til obtain reflectance spectra for a particular m.ncrial t c.g., Bah iagrass) and neighboring lan d co vcrtypes te. g .. bare soil . forest. aspha lt). we may nee d 10 mea sure the spec tral re fl ec tanc e of the materials thmughout the wavelen gth reg ion 350 to 2500 nm . The most impo rtant absotpnon features associa ted with vegetation are summarized in Table 15- 1 for the wavelength interval -UO nm 102350 nrn. Figure 15·1! depicts tho: spec tral reflec tance characteristics of IWlllthy gr een vegetation from 400 nm 10 2400 nrn . Strong chlorop hyll nhsorption bands occu r at 4.)() nm and 6h(l nm lur chlorophyll {/ and 4(l(1 nm and 64 0 nm for chlo-
rophy ll b. Wh en vegetation is stressed there is also noticeable moveme nt in the tmnsuion region trorn ncar-infraredto red reflectance known as the I'ed f'dKf' position. The greater the amount of "tress, the greater the movemen t of the rededg e to shorter wavelengt hs (Ca rter et al.. 1(96). The shon wax elcng th infraretl (S\VIR ) from 1050 to 2500 nm provides valuabl e information on the amount o f wa ter in a plant [i.e., its relat ive turg idity ) I Figure 15-X I.
Nume rous vegetation indices di scussed in Chapter II requ ire mformanon in the chlorophyll absorption bands. Tbe theoretica l basis lo r "empirically-bused" vegetation indices is deriv ed from examination (If typical spectra l refle ctance spec tra ofleaves IF ig.ure 15·~ ). Th e re flec ted em:rgy in t/l( visi b le band s is 10\\ a.. a res ult o f hig h ab sorpuon by photo-
C ha racte rist ics 01 the S peclrorad io meter Us ed to O b tai n t he In S itu
Tab le 15-1.
aenectence Spectru m
Folia r ~~I absnrJllinn feat ures tadaptcd from Curran, II.JIN; ,\ 'il >. 2U05 i.
Mechan ism
Wavelength
Chem ic a l(S)
t~OO
Electron tran sit ion
(,h l0l'Oflh~' 1l
(J.l ~J
Electron U"an~ ition
ll~O
Elect ron tran sition Electron trans ition C _ll stretch. 3rd ovenon... C-Il stre tch, Jrd overtonc 0 -11 stretch. 111d overtonc O-H stretch. 2n" overtone
ChlOfUph),1l b Chlorophyll II Ch lorophyll a Protcin Oil water. sta rch
UM O 0'110
U'IJll OQ10 11'1'10 1020 1lI4CJ 1120 121111 I,mo 142U 1450 14QU
Protein
19Ktl 21Hltl 20611 20HtI 21011 2UII 2111n 21411
C-Il stretch
15J U 154ll 1:,1I1I 16'111 17Kll
111211 I 'HMI
19J1l I Q~II
1960
o-n
2l~ n
D-Il stretch. O· H deformation
2l7fl 2lHil
C-II SlrelciliO- H stretch. C I I:! beml/ Cll:! stretch
z.tnu 2.\ I u 2,UO 2.1411 2.1 ~1l
C'· ll strelch/r l12 deformation N-II stsctcb. CoO stretch. C· 11 bend, :!nd overt on e ("· H bend, 2nd 0\'CI10 1lc
("-II ~treleh.ICIl2 dcformanon ("· H slreldl/O· H dcforrnanou r · 1l deformation'O- H stretch Cl I2 bend, 2nd OV<:f1One. (". 1-1 deformation, :!nd overtone
synthet ically active pigm ents wuh ma x imum scnsiuvuy in th e blue (470 nrn j a nd red (670 nm) w3H' !cnglhs. \1os1 of the ncar-i nfrared ra diati on is sca ttered tret lecied and transmitted) with \cl) link- absorpuon, in a manner de pendent upon tile struct ural p ropert ies o f till' ca nopy ( L \ I, leaf angle distnbuuon, k af murp hology) , As a re sult. the nmtru\( between red and ncar-infrared re sponses is a s e ns it ive me a -
a
Starch
!,<-11 stretch C-I I stretc h. C-H defo rmation C-1I stretch, :!nd 01ienOIW 0 -11 bend, r« overtone 0 -11 bend. 1st o vertone ('-II stretch, C·B deformation 0 -11 stretch , l st overtone. (' - II stre tch. C_II deformation (l·H stretch. 1st {w ertone 1'0 -11 stretch, 1st overtone o-H stretch. 1st overtone 0 -11 stre tch, 1st overtone O-H stret ch. l st overtone C ·1i stretch, 1st overtone C-H stretc h. Is, overtone O- H stretch.1I-0 -H deformation 0-11 sectcn'c-o sl.l\.'1ch. 1Ild ovenone stretc h. C -0 stretch A bsorbed water O-H stretch. 0-11 d.:lonnalion O-H stn: teh/O- Il bend N·H asym metry O-H deformation, CoO dcforrnanon N-t! bend , 2nd overtcnezv-H b.:nw'l"- H stretch (l· U >tTeldlfO-1l deformation O· H bend/CoO stretehiC-U·C stretch, Jrd overtone 1"-11 stretch "'-If bend. 2nd ovcnonc/ c-u slrelch/C·O stretch:C- ~ ..u crch
mo
575
ou Lign in Water, cellulose, sta rch, liguiu Will"r Ligum Stare'h, sugar. lign in, wate r Cellu lose. sugar Protein. nitrogen ~Ian; h
Starch, cellulose Starch, sUgilr Lij,'11 il1, starc h, protein . nilmg" n Cellulose, sugar. starch Co: llu1t~
Starch WJk'T W~I<:'T, hgrun, protein. nitrogen. starch. cellulose Sugar, starch rr"tei n Starch Protem, nitrogen Sugar. starch
Starch. cellulose Protem
Proeein Protein Starch Cellu lose. sugar. starch Starch . cellulose Protei n. nitrogen (l il Starch Cellu lose Cellu lose . protein . nitroge n
s ure of vcgcta uon amount. with maximum red HTSUS ?\ IR differences occumng OH1' a full ca nopy. a nd m inimal contrast over la rg ets wuh little o r no vegetation. For 10\\ and medium amount s of vegetation, the con trast is a result of roth red and ~IR changes. wh ile at higher amounts of vegetat io n. on ly the f\IR contributes to inc rea sing co ntrast as the red band be comes satu ra te d due to c h lorop hy ll a bs o rp tio n.
15
ClI-\ I' IEH
576
I'h ~ , i ll l ll l!j c a l
"
In Situ Reflect ance Measurement
Ua,i.. fur Ik \d lll' i ll~ \ 'l'J,:ct a t iu ll In ll in ''''
I
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Carotenoid and chlorop hyll absorption
liquid \'o Jk r .rbsorpuon
Fuli.1[ rctlec rance
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R gu ra 15 -8 I' h}s io log ic:II I>Jlils for dn cloping \cgctat i,m ind il'C'S in the n'g in" fro m :!:'iO - ::!¥ )() nm .
The red versus :-.11 K corurasr can he quan ti lied thro ugh the UM~ of ratios (f'\ 1R I lh -dl. diffe rences (:-.1 1R - RedI. \\ cighted
diffe rences rNIR - ( k • Rcd t]. linear hand combin.uicns [(:-.
2 00~).
Numerous
vegetation indices were summarized in Chapt er I I .
Spectral Resolution
ohnion of about III nm (refer about A\' IKlS I.
10
Chapte r 7 fo r information
Sp ectral Sampling Interval
....i1"clral .,(/ml'lill,~ interval is the sp;H: ing betwee n sample poirus in the re flectanc e spectrum. It is w ise to use a handheld spcctrorudiumcrcr LIMl has a spectral sampl ing interval (If I A nm (il J:'i( l - ]LUIO 11111, and 2 nm (if I l IO(l - 2500 nm {ASD, 2tllJ5J.
Spec trometer Design and Data Collection Speed resolution is defined as the full- wid th-half-m aximu m ( FWII" !) o f the spcc rrorodiomctcr response to a monochromatic tig ht source ( AS!>. 20115 L T he FW HM conce pt was introduced in Fig ure 1·6 . Spec tral resolution may a lso be de fined :IS the na rrowest 5.pectral feature that can be resolved by II spect rome ter. I\I00ny scicnnsu, are imerested in obtaining re flectanc e spectra for selected land cove r types S,/IXlrlll
subjected II) various tre atments in order ttl understand thc spectral respllnsc to these trea tments. If po.;sib lc. it is idealto use a han dheld spcct roradiomctcr that has a spectral rcsotulion of 2 to 3 nm for the region J f>() to 1000 nm. and III nm (or tho: reg ion woO nm to 2400 nm. Hypcrspcctral a irborne remote sensing sYSh~Il1S such ali A\'IRIS have a spectral res -
Some spcctroradunuctcrs used for in .\'il/l data collec tion record thc spectral infurmarion mo re rap id ly and accurately than others. The mor e rapid ly the spcc tro radio rnctc r collects all individua l scan in th.... field. the hig h<:Ttho: probability that additional spectra '" ill be obta ined before envirenrncrnal conditions t e .g.. cloud cove r, win d) and ~e nSOT system condruons IC.g.., vrewmg geometry) change. Reme mber. the gOJI is to ho ld as ma ny env ironmc rual a nd sensor paramet e~ a s constant as po~s l h le while the target a nd re fere nce scans arc coltccwd.
.-- - - - - - - - - - - - - - - - - - - - - - - - - - - . ,
Characteristic s of the Spec troeadicmeter Used to Obtain the In Situ Reflectance Spectrum
Si licon de tectors prov ide the b..'S1 perfo rmance for remote sensi ng invest igations in the- \ isihk a nd near-infrared (VN IR ) portion ofthe spec trum from 350 to 1000 nm . In the sho rt-wavelength infrared (SW IRl region from 1000 - 2500 om , the amo unt o f so lar e nergy availab le for me asure men t decrease s. There fore . mo re sens itive de tectors a rc required III mea sure energy in the S W iI{ region ( AS D, Z005 1. Typical detectors include 1w 0 separate InliaAs ( Ind ium ga llium arsenide ) photodiodcs.
577
Fil'lds of Vtcw ,.\....nc iated with
Var ious Fere-optlcs
All spcctroradiomcters produce: .... nn e noise. Dar k-cu rren t {i.c., electronic o r detector no ise) can be measured by view -
ing a blac k reflect ance target or hy lak ing me asurements w ith the optics cove red , The dar k-cu rrent sig nal can the n be subtracted from subseq uent spe ctral measure me nts. Most spcctro radiom ercrs include softwa re lo r recordi ng and subtracung dar k-c urrent.
2~ ~ 159,9 em diam"l"n
1M" (42.Mem olamd er)
Viewing Geometty and Reid of View
g" t l ll.l'i ",m Ol"" Ktcn
Ideally, in ,H t /l a nd remote senving-dcrived refl ectance spectra are ob tai ned by a spcctrorad iomctcr vie wing the terr ain at nadir. Most spec tral invest igation s have problems dea ling w ith the bidirect iona l refle ctance dis trib ution funct ion (BRDF ) effe cts introduced by the di urnal chan ge in sun I:Ievntion and azimuth. Schil l ct nl. ( 2 ()O ~ ) doc um ented how the spect ra l reflec ta nce o f Smooth Cor dgrass (S,,'lrtil1,j ulternijlUrtlJ cha nged throughout the day du e 10 changes in Sun a hit udc and ze nith angles . The HRDf problems become even more acute whe n the ~nsor ob tains data o ff-nadir. Th ere fore. when ever po ss ible . ill situ refl ectance da ta shou ld be obt ained at nadir. T he actualte rrain ... icwcd by the spcctrore dio mctc r at nad ir is a function of several facto rs. The diam ete r (/») of the ground-p rojected ins tantaneou s field of view o bse rved by the spcc trorud iosnctcr optics is a function ofthe ang u la r fi eld o f view (IJ ) multiplied by the d istance of the rad io meter abo ve tho: phe nomena o f inte rest (If): 1J ""~xlI.
( 15-2)
Th o: d iameter (0) of the ground -projected IFO V sho uld be decided earl} in the project. In ex ploratory studies, [) mi ght be set at re latively sm all d imens io n 10 obtain spect ra at the leaf. bra nch, and cano py s patial se al... [e.g .. D va lues ranging fr om j ust a fe w centime ters to 0 .25 III (appro ximately-' I tt.j]. Thi s wo uld provide detailed in formation Ull vegetation . sha duw, and soi l characteristic s typ ically encountered in a remo te se ns ing inve stig anon Refl ectance me asurements from individualleaves and branche s arc bes t obta ined in a controlled laboratory en vironment fo r reason s pre viou sly
1° (2"' em di a m~fi) -:1::~::::~~ JO( 7 em ,harnet"rl
5" ( l l .ll em diameterl
Figure 15-9 Fi,' I,lsofview using 1• .1.5, 1(, l x. and 25 degree foreopncs fur a handheld spcc troradiomcrcr positioned I ~ ~ ern above th.:- terrain uf interest.
di scussed re.g.. illum ination varia tio ns ca used by clouds. w indj . Valuahlc information about the effects o f me va riou s treatments might be discove red in th is ma nner. Howe ver, it sho uld he not ed that reflect ance spectr a derived trom indi viduallea ves and branches ar c usually (If limited valu e " he n tryin g to per form matched-filtering M othcr ty pes
-15
578
l'Iunt.1{
of view fore-opt ics may allow the spectroradiornetcr 10 ob ta in data that ls more represe ntative o f airborne hype rspec tral remote se nsing systems.
In Sit u Refl ectance Measurement
Cu rran . P. J.. IQloN . "R cmote Sens ing of Foli ar Chemistry," R~I1!<'lf
Sell.'mg of f :m 'i n mm,'nI ..'11:271- 271( , ( 'urt iss. £l. and S , l. Ustm , l'IXI( "S pectral Changes in Pond.-rosa
Candida te specrroradiometers Reffectance Data Collection
fOf
In Situ Spectral
Pine associated wuh Natural <>lnne Ex posu re." Fore,.' Se" '1lY Fun :!>1 R.·~pulI."· l'nJg ru,,, Am lll
mary. 1'1' 23- 26, There arc a variety o f handh cld spcct roradiomc rcrs that may· be used 10 collect the required in situ spectra l reflectance information. Tw o of the mos t widely used spcc tro radiomclen; arc prod uced by Geophysical Environm ental Res earch (G ER).
cr..
{",u~<' : mji.'ulivn L$Ulg" Ralch r"'wending Fuz::y Lellrning v.'C'"r QII
Filippi. A.. IQ<)<). IIll,,-·,..,{,,-'c!,.,JI
G l: R, ;:1100. f"idd
"""',lfH...
SI'r<'fmruJ",merel"'1>. M illhl'OO.l k, 1\Y: GnMlI' for Environmen tal Research , www.gcrt.com .
Analytical SpectralDe vices. Spcctroradio merers produced by thL'SC vendo rs are capable of obta ining the required spectral reflectance data over the spectral region from 400 - 2500 om at approximately 10 om reso jution. Each is easy to usc, stores info rmation in a d igital format. and can be customize d 10 fulfill speci fic user req uirem ents in the field {c.g .. field of view, interfaces, bac kpacks) . Specrroradiomcrcr instrum ent speci fica ti ons change rap idly. so it is ncceeoary 10 con tact tile vendors to obtain cu rrent information .
Goetz, S. J.. 20ll:!. " RL-.:o:nt Advance, in R<:nwlc S<."llsing o f Bil>. physical Variahles.: ,\ n Dvervjew o f tI'M: Special Issue," R,·_t ,'\en\inR n/ En 1'ln mm ..nI . 7~ : 145- 1 .u. , Jt'I1 'lC1l.
mor,'
J. R.. 2005. Intr....JI«·/,H)·Dig ilu{ Imug"
PrtH.·,,_uing ' .~ R..-
,o;.-n'IIIR P""(J<'< 'f" '<'. 3 rd Ed .• U J'f'('T Sadd le I{IW T: Pren-
uce-usu. S:!5 p. fiac, B. C and A. F. H. (;,)("tl-. I INO. "Column Atmospheric Water Vapo r Ret rievals fro m Airborno: Imag ing Spectrometer Data," Jnurnal "1 C""l'h,n iml Rl,« ,,,lt"h • Alm"'l'l...r.:~. Q5:354Q-3564
References Hu ct c. A , R.. Did an , K.. Miura. T.. Rod riguez. E. P.• G ao, X. andG Ferreir a , 2002 , "Uvervicw of t he Rad iometric and Hiophysical
Perform ance o flhe 1-.101)1 S \ ....1i-c( HlitHi lndiccs." 1Ie-"Wl
ASO, 200~ . T"cllIIi('ill Gui,I,·, -tth Ed.,l1 oulder: Analytica l Spectral
es..",mg
'if £11\'1"""''''/11 113 :195 -2 13,
De vices. hllp :l/w ww.a.
l.ahsphcrc. 2lKJ(,. ,\i " ,,'lruf"l!. North StUt"l l. N f l. http ://ww w.labAS]), 20llo, F I('Id.\;><'( Pm . Boulde r: Analytica l Spectra l Devices ,
sphere.com.
hltp ://www.asdj .cl.rnlproduc ts-sp...c troradiometers.asp ~k Coy,
AS TER , 20{16, AS7't.'1I S{wC'tml Library: Pasadena: A STE R Com-
rmnc c,
R. M.. 2004, Fidd Jkllwd ,' III 11..",<11,' S<'lI.
r"nl. 159 p.
hl1p ://, pccJib.j pLo a"q~
Caner.
Schill. S.. Jensen, J. R. arul (i Raber. 20U-I, "Bi-direct ion al Reflc ctnncc Distribution Function o f Sm ooth Cordgrass (SI''''''I II'I ,~ /_ I,'mlt/"r a l: ' (I/Sn,'"' ''' ,to R"m"'" Sen \'i" l(. 4 1(2):I J(,- 135.
Dl'll'Cl i" o of Pla nt Stress." Jlltlm,,1 vi l'lll'll Php iulub:v ,
1411:515- 522. Clark, R, N.. Swayze, (i A" Wise, R" Live, K, E,. Uoc f<.' n, T, \1.. Kokaly, It 1'. and S J. Sutley_ 2UOl USG S Digifal Spect,." f L ,brary : Splih()jll. USGS O pcn Fi le Re port 03-3Q5, Was hi ngton: USGS, hnp:/l sp..'Clah.er.usgs.ll OV!sp,:clral. lih. hlml .
Tcilict. I'. "-I.. G aeth ier. R, P" Cbic hagov, A . and Ci Fe-doscjc vs. 20(}2, " lima/d, In tegra ted Earth Se nsing: Adva nced Tcchnclogic s for In Snu Sens ing in the Ccnrext of Earth O bserv ation." Co-
n,,,fia,,1011""./ nj Rem"',· Sl'In i" f.:. 2K(0) :7 [ 3-7 1K,
•
Appendix· Sources of Remote Sensing Information On -line Tutorials
Funda mentals ofRemote Sensmg. by Ca nada Center for Remote Sen si ng. W \Ii W .ccrs .nrc an .gc.cazreso urcc ·I UI Of' fundamJindc.\_e.php
NASA Observatorium. http ://o bse,,,e.arc.nasa .govrne sa 'core.sht rnl.h trnl NASA Global Change
Ma.~'l'r
Din-crary. htl p:lIl;cmd .gs fc.na sa.go..-1
mdex.hunl
Remote Sensing Core Curriculum, hy l eRSt: . A SPRS. and l'\CGIA . http:/ Iv. ww.r-s-c-c.org / Remm e Sensing Tutori al, by Ni chola s \1 . Short. NASA God dard S pace flig ht Ce nte r. hn p:flrs Lgsfc. nasa.go \'/ Remo te Sensi ng Tutorial, by the Virtua l Hawaii. hup :/lsatlip.sClcsl.haw ai i. edu .space/ha wai i/ vIts/oahu /rem_scns_cxzrsex.spc rrar.t.tumt Virtu al Library: Remot e Se1l-<; II1:. http ~ ll\' i rtua l. vu.fl/space/rsvlib'!
IAEGS Model Curriculum, by t he Univ. of Miss iss ipp i Inst itute fo r Advenced Educ ation in Geospatial Sciences. hup :llgeo\\ork force. o km iss. cd c /overview.p bp Societies Alliance fo r Marin e Remote Sensing -, www.wrncrohscrvcr.crg Ame rican Geop hys ical Union - www.agu.org / American Soc. for Phot ng ra mmctry & Re mo tc Sensi ng - www.asprs .org
Canadian Remote Sensing Soc . - www.cavi.ca/ind-ex. phpvpg ...crss Euro pea n Assoc . Remo te Sensing Labs - www ,earsd.orglwelcome. btml FeJ ...ration of Ame rican Scientists; Image imcfligcnce - www.fus.org/
IEEE Geoscience and Remote Sensing Society - ww w.grss-ieee.org/
579
Appe n tU l< • S o urces 0' Remote S e ns Ing tntcrmanen
Inll. Comm issinn on R ~' rn' lI'" Sensing - hltp:/i hydmlah . arsusda.gov 1- j ritchie/
( '01111'' '''''''''''
Int i. Soc. lor Phorogrammetry & Remote Sensing - www. isprs.org
Eart h Observation flfaga=i"f' - www.eomo nline.com'
( i("<,sc i ,,,,,",'.,
w\-"w...,b;cliicr,eo miloealcl
compgeosci/
National Stereoscopic Assoc. - www.stereoview, erg/
Gcocano International »- "" w w .gcoca rto.com/gcocarto, himI
Remote Sensing and Phorogrammetry Soc. (L:K) - "" \\ w.
Gcohsfonnattcs
ww w.j-gcoinfo. nct/
rspsoc .o rgr
Geosp.nial Solutions - www.geospanat-onlinc.com ' Remote Sensing. Spec ially G roup. Assoc. Am er. Geog raphers - w"" w.aagrssg.()rg! SPIE tn u. Soc . For Optical Engineering - www.sp ie.org/ Nat ional Space Ag en c ie s Canada Center Remote Sensing - ww w.ccrs .nrcan. gc.ca/
G IScie llce & Remote
Sell~ ill~
- www.bellp ub.cnm msrs
IEEE Transactions Oil G.'O.<('iI'II c e & Remote Sensing hup:I/il'ev.p lore.i«c.o'll/xpI /Rcccnthsuc.jsp·? punumber= 36 Inll Journal "f Rem ote Se n,illl<: - www.ran-df.co.uk/ journa ls/onlincl O143- J 161.a sp
Centre Nat iona l d'Er ude s S pariales - www .cnes.fr/ CS IRO -Scientific and Industria l Research for Au srralic -. www.csiro.au/
IS I'RS Jou rna l o/ I'lw lox rulI/l/ft'lry Ulld Rt'moTt' Sensmg -. www .ehc\"icr.cum 'l<)c:lte'isprsj pn;
t'anern R.'coXflilitm - http ://se ienc<,: .dir<:ct.eom European Space Agency - "" .... w.eva.iru / R"II/tl/,'
Na tional Ae ronau tic s 8; S pace Adm inistration nasa.gov /
Sn l"i" x 01 Environment - www.elsevier.com
~ WI-'.'W .
National Re mo te Sensing Agency Ind ia - www. nrsa. gov .in!
Photogrummctric Eng ineering .{ Rl'/I/()/" Sl'IIIillg asp rs.o rg/pubIicatio ns Iindex .hI m I
www.
Sl cn'O u'orld -: National Stereos cop ic Association - www . src rcov i CW . I lrg/slereowo rld .hrIn ]
National Re mote Sensi ng Agl'ney Ja pan - www.nusda . go.j p/index _c .hrm l
Aeria l Ph otography Sou rc es K ite a..'r ia l phorogrnph y - htl p:!!arcl1.l: cd .hcrkc lcy.cd ul kap/k aptoc .htm l
Journals
Ad vances ill Space R"I,t,tIId, - www.clsc vicr.co m'wps/ product/cws_h01l1e/644f Aunosphertc R"~I:
NII A I' lind NII AP
USGS , Na tionalHigh Al titude Photogra phy ( I\ HA P) & Natiuna l Aeria l Pho tography Progra m ( ;<'; .'\ 1'1' ). hltp:/lcdc,llsgS.gov lgui dcs nap p.luml
US DA Photog ra phy - www.apfo.nsda. govl Bl1t"k.n-'II II,: r -
marine remo te sensi ng: www.watcr
observer.erg/ Cartugra phy.( Geographic lnformatian Science - www. acs m.nevca g is/cagisjr. ht mI Cunadian J ournal 0/ Remote Sens ing - www.casi.ca, indexphp
Multispectral Remote Sensi ng Data Resource s ADEOS-J1 NAS DA Ad va nced Ea rth O bse rving Satd · lite-It , hu p :lls ha ra ku.c orc.j axa.j p/ AD EOS2/i ndcx .html
581
Multispectra l Remo te Sensing Dat a Resour ce s
A\1SR - i'\,lI"SA Terra Advanced vti crowavc Scanning Radi ometer [onboard ADEOS-III, hnp:/lsharaku .eor c. ja xa.jp/ A:\ IS Rzindex _e . htm ASTE R - NASA Terra Advanced Spucebom c Therma l Emiss ion a nd Re flectio n Radiometer, h tt p : //ll ~ t l' rw e h . j pl. nasa . gov /
LA:\DSAT TM - Themat ic x tappcr, http://l' dt.: .us gs.gov / products/ sa te 11 ite/t m .htm 1 LA:'oi DSAT 7 (En..I-t- ) - l. a ndsa l 7 Enhanced Themat ic Ma pper Plus. hllp :ll landsa t7 .usgs.go v! Mer cury, Gemi ni. A pollo. Sky lab - .... ww-pao.k sc.nn sa. gOYIh isrory/rucrcury/mcrcury.htm
r\V II RR ~ ~O AA Advanced ve ry High Revolution Radicmctc r, hHp:J/edc.usgs ,go v/prod uc ts/satel Ii te la \I hrr, html
M[ T EOSAT - hll p:!lo iswww.cu mcts31,org l l[)[)S -cgi l lis t!mages .plv mebnw
AVIIRR Pathfind er - hllp :l/podaacjpl .na sa .go v/cgi -b in dcatalog Tam _su mma ry.plvss t- pfsc t
:\IIS R !\"ASA Terra :-.t ult i-a ng lc Imag ing Spcc troradiomet er. \\ ww-m isr.jpl.nasa.go v/
AVIRIS - :-.IAS:\ Ad van ced Visible/infrared Imag ing S pec tro meter. hnp:/la \ insjpl.nasa.g c v/
1\IODIS - l\:AS/\ Tel"r a \Ioderate Resolut ion Ima ging Spect rometer. htlp :/Imod is.g '"fc.nasc. ~O\"
CAS I - Compact Ai rborne Spectrog raphic Image r, ITRES Rese arch Lim ited of Canad a, www.n res.com /
1\ IOP ITT - \:ASA TI'I""o Measurem en t o f Po lt uuon in the T ropos here. hn p:1f e (l~ " cb .Iare .na...a. ~() vi I' R0 OOC S:' mopi ltlla bIe_lIIopi tt,html
C ERES - NASA U '/"I '
1\ lOS- II ~IU S - 1 b - 1\ I urine O hsc rvation Satcll itc, Im p:!1 www.cocja.\a.jjlfsall. llitclsaldata/mos_e.ht III 1
(' O R O ~ A.
O('TS - Ocean Color and Temperature Scanne r. www. eoc.jaxa.jp satc lli tc'sc nd ata /oc ts_e.html
D\ISP - Defense Meteorolog ical Sarelhte Program. " W", ngdc. noaa.gov /dmsp lndcx.hnn l
O rbvicw-j - GcaE)1.'. Ind .. www.Gcoliyc.c om
ARGO"l . LAf\YAR f) dec lass ified ima ges. htt p://edc.usgs.g:o\!produets satel liledeclassL hunl
EO- I - NASA ~o:w Millennium Pro gram . Earth Observing- L Advanced La nd Imager. htl p:lleo l. gs fc.nas a. go v!
GO ES - l\:O AAfN ASA Gcoste rionary Operat ional Environ -mental Sa tell itc, hllp :!lg oes.gsfc .nllsa.g nYI
Qu ickH ird - lJigilalOloho:. Inc.. ww w.digital-globe.com abou t quic khird.hnnl RESU RS-OI - R IJ ~ s i an satellite, hUp:!lsputnil.,infllspace. ru -rcsu rs.cng l.rcs LIT s , lu In ScaWi FS ( O rhVll'w-2 ) - Geo t.yc. Ind.. www.GcoEye.c orn
Goog!c Earth - Gcoglc. Inc.. h tt p://ea rlh.g{ll)g le.com / I ~ [I nformation. ln te gr unon. Image, lnc.j. www.iLccm / IKO~OS
- Geohye. Inc.• " 1-\ w.Geoli ye.cum
IRS - I A. B. C, D - Ind ia n Remote Sen sing Syst em . Linear Imagi ng Sel f-scann ing Sensor ( L1SS). hltp:/i .... 1-\" . spac.:-i mag ing.co m: prod ul'ts: irs /index. htlll LA NDSAT \.1 SS - Multispectra l Sca nner. hllp :/!ede .usgs. g O Yzpnxl ucts/sa tc lInc/mss.hun!
SO IIO - Sc..lar and l te ho sphc ric O bse rvatory. http:// soh owww.n ascom.nasa.go..-t Space Shuule Photo g ra phy - www.nas m.s i.cd u..c epsirpi l1 ssp r.cfm S PI:".!·1 TK-35 0 and KVR · IOOO - U.S . co verage served on Micro soft's Te rra Server (www.rcrraserver.com ' pTOvido:rs/SP I ~~ .a sP I S POT 1- 5 - www.spot.com
582
AppendilC - Sou rces 01 Remote Sensing Information
SS M,.' I - NOAA/ NA SA Spe cia l Sen sor M icro wav e/ Ima ger. hll p:/lpouilac.j pl.nasa.gov :203 1/sc nsof_docs/ssrni . htm l
SLAR - NASA Si de - Loo ki ng Airborne Radar, htt p:// p uhs ,usg s.gov'/ofl20( 1)'o llfO-OO6/ ht m/s lar. ht rn
TO Yl S - Tota l Ozon e Map ping S pectromete r. http;/! j wocky.gsfc .nasa.go v/
S RT M Shunk Rad ar Top ogra ph y M ission. w wwj.jpl. nasa .gov .sn m'
TOPEX/POSEI DO:-J - hn p:/II(\pC':\-www.j pl ,nasa.gov!
STA R-3 i Sea Icc and Terra in Assessme nt Rad ar. Tnrerma p Technologies, wwwin termap.c o rn/ jma ges papers/ Imcrma p _STA R.3 i. upg rade.' _ ~crecn _ v'2.pdf
TR M M • NASN}J AS DA Tro pica l Ra infa ll Meas uri ng Miss io n. hnp:htrmm.gstc .nasa ,gnvl
Virtual Earth - Mi c rosilli Inc .. ..... ww.local.li ...e.cum
UARS - !'ASA Uppe r Atmos phe re Resea rch Satellite. htlp :l/um pgal .gs lc .nasa .gov/Rad ar Sensor Systems
On -line Remote Sensing Resources at the University of South Carol ina
AIRSA R - NASA JPl SA R. htt p://airsa r.jpl.nasa.gov!
Or. Jensen provides I'o w crPu int 1M lecture materials containing non-copyrighted illust ralio ns round in this book free of charge for educationa l pu rpu~s . The proct.'SS can be initiated by , 'is lt ing the Unive rsity of Sout h Carolina Ce nte r for GIS & Rem ot e Se nsing 31
ENVISAT·I - Europe an Space Agency. hnp J /c nvisal. csa .int ' ERS- 1. 2 - European Space Agency. hlt p:!lcanh.csa.int' crs/
JERS- l - Japanese Ea rth Resource Satcflit .... www. nasd a. go.j p/proj ects/sat /jcrs I ii ndex_e.htmI Li ghlS AR - NASA Spaccbome Radar (propos l:dl, hn p:/I sourhport.j pi ,nasa, go vI Iightsarl
Dr. Jensen a lso provide s free acce ss to remote sensing cxcrcis~ an d selected re mote se nsing daiascts that he- uses in the Univcrs uy o f South Carolina "Remote Sensing of Environmcm" course . Please acce ss the infc rrnanon at: •
1\ 1\ \~ .cas.S(".eJ
u/l,:cul,:' Rsbook/indcx.html.
RADARSAT - C anadia n, www.rsi.c u/ SE AS AT - hUp://SOUl hport.jpl .nasa.g.ov!seicm.:..:apps/ scas at.h un !
SI R-A. B. C/X-SAR - A'ASA Spun: Shunte l /l/ugillK Ra.tor: Sl R-A -
htlp:llsIlUlhport.jpl J1ilsa .gov/sc icncca pps/si ru,
htrnl S IR- H html
http : //sllu lh pl lrt .j p l . lla~ a. gll v /scie nceapps/s irh.
S IR-C/ X-SAR - http ://southpo rt.jpl.nasa.gov/si r-c!
You are welcome tn usc the lecture mate rials a nd exercises and adapt them to your req uireme nts. Several of the exercises require access to the ER D/\S Imagine digi tal ima g~ p roc essing sy stem ( Of cl[uiva t.: m ) 10 perform fundamental op crution s such us vicwiug a culm-co mposite image and m~ "-ing rneasuremcnr s . In most instances. uhe imagery used in the e xercis es is in thc public dom ain unless otherwise noted. If yuu usc the remote sen sing e xerc ise materials. please send the autho r information about inno vative uses. Il1ctliOlhllllgica l re finements rhat co uld be made. and improved d;LlaselS rhat might be usc,i,
• Index
A Absolute zero. N . 249
All....>rptiOll bands. atmospheric. 51-52. 5+-.55. 25 3 ~254 extinction coemctem . 51. 411---4 12
rocks and mineral s. a lunite. 5 19 holi nite. 520
518-5~O
quartz, 519 vegetation ca~cne. J59-3 ~. J ~X
chlorophyll a and b, 205, 35Q- J60. 4 11\-41 9. 422
phycoery th rin, 351)....360 ph)'l;ocyani n.359-360 ...·1111.,.,
4 1 ~ lq .
423 . 425-----4 26
Across- track scanners.. .....' Scann ing A("th ·c microwave. S
.p stup. <)(......97. 109. 118 imllgemotion compensation. 'i'l_1 00 mtcrvalomcter, 9<) jens angle of view. IN shutte r. 95-96. 9~ shutter speed. 'In.-'n, 117 tYPI:S of digital, 9 7, l OI- 105 mulripte-Icns. multi-band, 97,10 1-102
panoramic. 95 sill~l.:·lcns
mapping. 'n-l 00
Aerinl phulograph ) films, HW- 124
blac k-and -white
infrared. I II -Ill panchromati c, 1[ 1-[1 2 orthoch rornanc , I [1- 112 color color t non nal). 111. 1[3, 122- ID color-infrared. II I. IB , 1:23-1 24 history of, 62-M negarivc'poshive process . 62---6.5. 113---11.5
583
584
winduw s. 25 3 -254 rada r pe nerrauon or; 32H- 32 I M:all~Ti n!:\ in. sec Scatteri ng
silver halide crystals. 110-112 spccd.Lln
Aerial photography filtration, 104- 109 band-pass fihcring. !07- 10S haze filt er, 115 Kodak wranen, 107- 1Oi!. 122 minus-blue. IN polarizing lih ...rs, Iii, 107- 110 Aerial photography platforms
aircral\, 72-74 \lo n ght brothers. 72-73 WW I and WWII . 74 -76 balloons, 60-70 (i\,'1lctri\ . 77 c ivil wer. t>~9 cold ...ar. 7r..-lll Corona -a retlue. It 1- 10
SR·71 aim afl.. 1I0 U-2 aircraft. 77-1l0 glidl.'B. 7 1. 7J klle:<. 70- 7 \ ormthoptcrs, Of> pigelln s. 71- 72 rock ets, 6 3, 69
unmanned aerial vehicles. K5- lIl! Aer osols. remlll.: sensing o f, 4 31..... 02 Agri culture Nonl'llinl Source ( AG f'\PS f po lh.l\ion model. 43 7 Agric ulture . remote sen sing o f, 371 - 373 . ~ 77
13.240-241 Aircraft . Sloe A...ria l phn\ography platforms Alluvial depos its fans . !i4f>. !i411 bajadas. 546. 5411 pediments. 546--54~ Altitude above-ground level (AGL), 92 . 150 American Plan ning Associntion. ~ ~ 1-452
Analog-to-digital conversion. I. 1Ill - I l l. Ancillary informntirm, 1 ~4 Angle of view oblique
101<. 92 - (,l4 high. 92 . '14-'15
vertical. 1)1 - 92, 1·4'J Anastomotic drainag.. pattern, !i2K-529 Annular dra inage paueru. 527- 5211 Ante nna . sec Radar system com ponents Anticlinal ridges. 522- 523. 53~. 54U An-a arrays. !In. Illn. 101-11'" Area measurement s, 189 - 1"'2 dot ",'Tid. 19H... 19 1 on-sc ree n
dlgitiz;Jtiull. 191- 192
Arete. 557- 5511 Atmosphere
absorpti(lfl and transmission in. 51-5 2
B Beck scartc r. '
'1M
parallax. 173- 114 shor... hll..:.45 1-452 Harriet' island. 55 1-5 53 Basc.lilm.llO- 112 Batho lilhs . 5.':1- 534 Bcach . 551- 553 cliffs. !i54. 5 sn Ikdflld,. 5()ll-501~ Bid irec tion a l reflectance dismbuuon funct ion . 2ll-- 21 Ui"d i, ~1> 1 1). .N 3- 3~ 1 Biophys ical variables. 10--12 Hlack-and-w hue pho tog raphy, 111- 122 Blackbody. W. 254 Hh...:l o f ae ria l ph" logra ph)'. 150- 152 Braided drainage panc m . 527 _52"j Brightne ss lelllpc:ralu r..:. 'ec Passi, ~ rnicrow av... fluildin... infonuanon, 11~ . I K ~ _ II¢Q. 4 ~ ~ -404
C Cadastral mforruauon. 17 ~. 4
Cam c nl ~. ' ce Ac rial photography cameras t'a mu\l 1 1ag~ d..rec uon Iibn , s"~ Aeria l photography films Ca nopy closure pe rcen t. 1- 2. 344 ---.'45
leafurea index. 1-2 penetration rradan. 317- 32 1 Cardinal effect , !>I.''': Rad ar. lcrrain L'cntrifugnl drainage I'
I"W r.X
Cloud". remote sensin g of heig ht, -1 32 -4 35 III therma l infrared imagcr)', ·02-13.' in \isiblc imagery. -I32 --l33 type. ·B -I C03"lal Zone (' 1,lor Scanner (e ZCS I. 2sn Collateralmtormation. 1-14 Col, a glJdallandform. 5SS Coll>l' additive theory, I0-1- 105 balance shift in culot-Infrared film, 124 complitncurary. I~ false. »ee Aeria l photography films, color-infrared history of. 65-66. I O,t 122 photography, see Aer tal pholography 1iI 11l~ primary CQII'~ 104 subtractive theory, IM - ln7 (oll>l' photography, M.'C Aerial photography films I'omrnerciallnnd IISC. imerp rcrauon o f. 42 ('- 4 3~ aulomot ivclbl....I.405---loo central business dicmct (C RD), 41\5 finance and construction. 4M---4611 food and drug, 4toX-4 6'l funeral and \'",m clery. 41>11-170 bouse and garden, 471 Iwusinl,! ~ temporary I. 40 ')...47 1 other co mmercia l, 472 recreation. 4 7 1- 4 12 ward'K''UsinS shipping. 4 71--476 Fommunicatious and uuhues. intcrpre tauon 01: Compact Airborne Spectrograp hic Imager. 13. 2-lI - 24 2 Conduclion.37-3X Cone, volc ano cllKkr.S3O--531 c(>mposilc.532-533 Ccrqugate pnncipal point. 153. 101>-1 hX I'onnnental drift, 522 (01'1\'«:1100.37-31' Convergence of evidence, 132 - 133. 145 Coral ree f 554---551, ;11011, ~5S -55 6 bmicr.555---556 fringing, 555 556 Corona satellite. XI- IIJ Critical environmenta l a reas. interpretation uf, SUO---SOI Crop (alcndars. ~ \ 'cgctatiol1 rh\'1'\(llngical cycles
o Data Analysis analog {visual image proc\",si n~),!). 24 :'!6 digilallmage proc essm g.. "I. 24---211
Data t'cllection 1-2 . ('I laplcr 15 remote sensing, 2 -1'
III $;111,
D.:fcn-e M C1\'UI"01~ical S..telli l'" Program 1 (>\1 S PI.. Ikforma1ion of rocks, 512-523 l>clla,
585
l.'f<'ll ula1c. 5-10- 54 7 cus p:llc.S·U, -S47
elongated or diguat e. ~S47 lobate. S~(s 547 Dendritic drainage panc m. 520--527 Ik ns ltomell.'r , l l l' -l l!) Dens ity. 11ft- II II f)q>ress ion angle. S<'C Ra dar system components Depth perception. 163 Detectors. 1 )5_ 197. 224 -226 ' Did lOh't11ic drain age panern, 527---52'1 I>tclec tric consram, complex, J I b - 3 17 Drffcrcnua l fMra lla\, see Paralla x. stereoscopic lli gi lal(, lot'l:,233- 235 I) lg iWI ele vation mod e l. 335 D igila l
frame cameras l.e jca Emc rge Il igital Senso r System (U SS). 2-14-245
Vcxccl Ultn,C"am, 24S / i 1 Digua l M"du lar Camera , 24 5 Dsgrtal surface mud d lO SM I. 335, 3)7. 3-10-34 ( Dignaltcrram modcl (I> r~f). 3J5. J -II -343 Digiti7ing liucuroran-aarray. 11 '1- 122 rnicrod cnshomctcr, us 119 \,idc< •• 11"1 Dig it:11 im age proce ssing. 9 change detection. c, 21> C'lJX·n syste ms and neu ral nd\l.urb . 'J gc<>melric coerecnoe. 26 hypcrspecua ! data ana lysi s. 'J, 27 m<>dchtlg. 'J. 27 tlOlll'.lramdrie infor rnatlcn ex tra ction, 'J, 20 para metric feature c 'l1ract ion. 9. 26
radiumcuic corrccuon, 26 Sllti-c(lPY photogrammctry, '), :'!5- 2(, terminology. 104 - I 05 I>isast<:r emergency response, 131. 500 502 Dolinc ts mkhole], 528. S4'J !>llmc lav a. 530-5 .1 I sand d une. <;03-5M Dooplcr frequency in raJat,3011-3 12 1>01 grids. 1'10- 1'11 !>r
de ranged. 521' dichotomic, 527. 52'1 parallel. 520, 52R pinn ate. 5:'1' radial tccrun fugal} and centripetal. 526, 528 rcctaug ular, 526--527 ~in kholc (dolinel. 5~R. 5-N trellrs. 526--527 Drumlin. <; 67, <; 6fI. 562
II\ IH:\
586
I lull ~S .
l.mulvion. ",-"e A.'rial I, ht>wgr" phy lilms f nJ iap. ~1crcosc"r ie, 151l -151 l:nc'1! y. 37 Fnc'1!} . matter i nlc r'lcli "n~ h..r msphcncal ahs"'l'laIKe. 54 -50 hemispherical rc tlcc umce. S4 -56
sc e Sand dunes
E ('.anh Observer (lO -11 NASA Advanced Land Imager (AU I. 2 11-212 Hyperi o nhyperspcctral senso r, 2 11- 212
LE IS,\ atmospheric correc tor. 2 11-2 12 Earth O~",,'in~ System ([ OSI - ~ASA Landsat 7 Enhanced Them atic ~1" l"PCr"' . 11- 13. 20:,-2llQ science plan. 22- 23 T erra §O;'1lMlr syste ms ASTl::R. 11- 13. 2-4, 2.;1-233. CE RES. N . "' ISR . 11-1 J. 2-1, 232-233. \tOOlS. 11 ~1 3. 2-1.242- 244 ""O rI' ETT.2-1 Earth o>Os<....... ation economics. 2~ -30 Earth RC'l'oun:e Technolog y S
hem isp he rical lr
Eastman, (j~'OI'f'c. 66
~all l1 s. l!col ~ ic, 522-524. 5.ln. 5 4~ tiduo: ial nwb , 152 -153 Field llf view. see InstanlanC'(lUs field o f, iew r lightlinc, 150--15-1
Elasnc dcfllnnal itln. 52.' E1ocuu magnt:tic radiation. 37- (>0. Chapter :2
al>sufpl ion. 51- 52 b) atmospheric gases, sec A lmOs phl;'11,' hy s urface leature ~. budget eq ua tion, 54 creanon -1 3-4 7 fiu\ density. H -:'i f> e xua ncc. :'i4. :'i f> irrudiancc, 54. :'i e,
","'C En.~y-rnallc:r
naerccuon -,
cr.
~ X-47
p"nide.3R. -I3-4 7
waw. .'I'(-t ~ radiance, 54, 5t,-5 7 radiant tlux . 53-5 4. 252 re flectance, 51, 53 - 56 rcfra,'lioll. 4K-t ~ speed orliglH, 3R units o f meas urement. 4 1-44 waveleng th, J() 40 Elem...ms nfimag.. interpretation. 25. \ 27- 1../1\, Chap ter .5 association. 25. 132 133. 143 hcighlAI"('ll h. 25. ' 32~ IB . 142 pattern. 25. 132 -133, 1)') - 140 shadow. 25. U2 - U3, 1511- lfI () ~ hOlPC, 25. 1.'2- 133. 137- 13ll, Sil",25,132- 1.\3, 143 siluall\>l1.25. 132- 133. I·B s i J~, 25. 132--1.'3, D'\-.- 137 slcpc'espc ct. 25, 132- J33, texture.
25.
Ll ~ -J33 ,
I3s- IN
lon.:-, o lor, 25, 132- J33, 133 - 135
9
film . 11 5-1111 stations, 150
l.y c base. 163
F Fa l ~ 001...... see Aeria l phOf(lgra ph) films. co lor- infra red Fan. a lluli OlI. 546. 54 !/'
Film.....'(" A.'lial r hOlOl,!raph) film~ r dlers. sec .·' erial phv1
covered. 5-l4
Irequency. .'It>-4U interactions . sec Energy- mailer models.
t- \ ro- UR"
localion. 25, 132- 133. 132
Ele vation data. sec I>igila l elcv anon mode l F.I ~;n o. sea-surface tempe rature. 427-t2!/' Emissivity, 2S 5~256
meand er. 54 .\. q ~ 11m ial lJ nJ rllnns. 5~ 1 :"'4!/' Focullcngrh . sec Aenal photograph y ca meras l-oc al p lane, ,.:e ,\ eria l photography eall1o:r....' Folding. 5~3. 5.\11. 537 541 h're,ht>rll'lIiulI in radar i lllJ~CS. J 05-J()(,
r "n·,l ry. SCI.- Vcgcrauon l r",:luring "f rock . 521-5 24 f~l "p . sec ,\ ,,·ri'l1I'how graphy com..'ras, 9(,
G (iilp
analysis, Nil -.1'J7
(ic\lEy..,/SI':\" · lma lling, 2.15 2.1h
(je"lng). 52 1 521\ dr.unagc ,k nSlly. 525 pancrn. sec Drainage p.mcrns
Icxlllll.", 525- 520 5:22
1i [h~,I .. g),
«mc twe. 523 faulling.5:23 -5 25 normal. 524. oblique slip. 524
reH' r'lc. 52-.1 . sl:arp.524 strike ~li p. 5N thru'l. 524.
!"!dmg. ';2 _1 --5\7 alitictmc. 53!:!, 540----5-.1 I
587
I:'lUEX
hoglxld•. 538. 54 1 mm1l1(11nt'. 52.' overt urn....J. 5~ 3 s)rw:line. 53 ~ Geometry of a vert ical aerial photograph. 153- 155 (ico morphll lllgy. 52'1- 51'>1'> Geostationa!)' Dperauonal Environmental Satel lite l G O ES ). 2 11
H u w e. see At mosphere lleat Ca pacuy \t.pping 1-hsMtln (11( \ 1\,1). 2 ~1 Heatloss. the rmal infrared imag"s u f buildings . 2 5 1. 1 X2 -~ !(7 buri ed heatin g lines. ~ 67 lIei!thl me asure ment W>lllg air p ho to relief displacement. 1 ('() · 1 6~ ,hado " le ngth, I (,~ stereosc opic p arallax. 162 - 17-1 so n-
manua ls. 47 11 ext raction indu stries . 4 711 --482 fab rication ind ustries, -IJol1 --4lU( heavy. -I1l 7--4JolIl light. 4X7---1 R9 proces sing industri es. 4Jol l---lX4
chemical. 4S3 - ·U~ 5 hea t. -I1<4 -41l7 mec hanical. 4R ~---I83 Infrared
reflcctive. 12-15, 42--45 , 4 7. -1 14 mid dle. 1.2-1 5, ·U --45. 4 7 Iht'T11l al, I2 15. 42 - 45. -17 Infrared ill1"gcs. ph,'l ograp hy, sec Aerial photogra phy film s, infrar ed th..e-mal. sec Thermal in fra red remore snlsmg In _,11" da ta cotl ..- cnon. I 2. 8 til ' S. lea f urea index, 1-2 spect ral re flectance. 1- 2. 5t>lJ---.5711. Ch apt er 15 f"lfJ'O"< of. 5M referen ce materia l tspectralon). 570---57 1 targct m.ucrial. 570 -57 1 ilhamnanon .ular.571 -5i3 la bontl'l!)'. 573-574 spcctrora dio mcter ch.nac rcns ucs. 574--571\ lns tantaneous tidd of \ jew. 3 jnrcrv ctomer cr. IN
Inverse-square law. 2l'>-1
K Karsttupl.>graph). 523. 54 '1 Kenle. 5511. 51'>2 K inelk temperature, 253 Kirchotf's rad iat ion law, 257-.260 Kod a k acriul films. see Aer ial ph" tography films Kodak wranen liilers. M:C Aerial pooh>graph) filtration
I l K O ~OS.
11- 1J. 235 -13 (>
Image
enhancement. 'I. 26 uuerpreteuon
analog or \ isua l, 'I. 25-26 digital. ....'\.. DigItal image processin g Imag ing spect roscopy Imagi ng spt'CIT'OIlll"I("I"$ sec AV IRIS. CASI- 15txJ. fl,10UI S reflec tion and absorprirm processe s. 5 1R 52 1 elec tronic proce ss es, 520 vihrational processes. 5~0. 575 spectral re flcctan..-.: lib ran..·... 5211-521 lncident a ng le. see Radar system components lndex of rc fracnon. 4:S--4 ') Ind ian Remote Se nsing l IRS ) Satellite progrJ.m . 1~ 'I · 231 Industri:tl lanJ usc. mterprcteuon of. 41lJ--4~'I classification logic. 47'1
L Lam bcrtia n surface. 53 Land eo"'er......-e Lan d usc/land cov er Land form s, m tc rpreranon o r. de\' e l"po.'ll nil horizontal strata. 53n. 53-1 developed on Ii-.ld ed strata. 5}O, 537 eolian. 530, 56() fault-contr olled. 5_1tl. 5,lll 110\ ial, 530, 540 glacial, 530 . 5 17-52 2 ig neous. 530, 5}O ~ an.1.. B tl, 5-111. sborcliue, 530. 5-1'1 Lands,·ape ecology, .'IIJ---W7 indica tors . 3<)4-3')(, patch mct rics, N 4----3% l.and use land COH'f, -150---45 1 clasvrfl canon sc hemes. 4 .~ I ---I.S(,
I:'"I) EX
590
advantages limuauons. 7-& art or "l:kn,;c." 5 h,ophysi';31\lanah lt"S Co be sensed, 10-12 data colll-Clion,:! R. 12 - 2 ~ and Chapler 7
definuions " I~ '" ASP RS. '" maximal and minima l. '" di stance , how r,lI is remote. history of: 2-4. I> instrum ents . 7 logic. ~ milestones in. I) (Table 1- I) process. 11 -<,1 reso lution radiometric, 14. rs. 20 sp.uial . 14-17 spectral. 14- 1f> temporal. 17-111 statement of the pr" hlcm. lI
Ik prl_m.u i\ c traction. 155-160 Residen tialland use. mllTjl rCI
imaging spectrometers. see AVI R1 S, CAS I- 15IKI. M ( )l)I S ref'lcction and absorption processes. e tecuomc proc esses , 52U-521 evnnc uon coc fficrcm. 5 I'" index ot refrecnon, 5 1'>1 .ibf".llwn.1l processes. 5~O 5~ 1 spectral reflectance hbraries. 5~U
S
Saltanon. seo. :10.1 Sand dunes. 562 -Sf>(, types crcsccmnc. :162-563 dom e. % 3- 5(," linear, 5(,2 -564
para1:'(llic.51,5 s tar. 5(.) -564. 56f> radar pe netra non u f. 310-317 Sandstone. 535--536 Sea lc (If a verucal aeria l photograph, 155-160 terrain 1e\.:'I.1:l5-151\ \anable, ISll -IM rep rcscntanve rr-Jctioo. I55- 100 verba! sca le. ISS Sca nning across- uack. I'Jf,_197. 261 -261' Scattering at1l1mpheric. 4R- 5 1 mic.4'l -50 non -selec tive. 50 51
ra) leigh , ..9-50 surface in u tlar imagery. 30~. J 1~ -3 15. 3 17-32 1 in vcgetanon, 35'1--J03 mlooils.5lo-512 in water column. 4 10--4 12. 415 Sea -vie wing Witle FidJ v r View Sensor (Sc a WiFS I, 13. 21lt-21Q S,'din1<"Olary roc ks, 522, .'U5 Se lec tiv ely r~tl i at i llj,\ hlldies .155 - 257
Services land usc. mtcrpretarion 01 pu blic buildings and fa c ilitie s, 472- -17<1 Sh'ldow. D2. 1-11 142 Sha le, 535 Shape. II1.137- 13~ Shun k Imaglll g Radir (S IR). 293, 323 ·324 Sidclap. sltTOO"COrllc, Side·looling alrborllc radar, SI.."'C Radar Sig moid or s-shape dl"101110o. 20'1 Silver halide.SI.."'C A ..1'ial phot ugraphy !ih n lo SilC. 132. 135 1.17 Slant-range, scc Radir SOli-copy photog rammctry, 174--- 1 ~" aero-triangulation. 178- 1so collincuruy condinon. )80- 1:< I co ntrol. 175·- 17h definition. I H c:>. lrd cl il ~l of cOnitlurs.1I11-11I3 dlgilal d"" i1tion moods. 170, 18 1- 1!l.J elcva tions.I7l>.Il'l I - llG l>rthoimal!-L"', 176. 183 - 1811 rhcmanc tearures. l i6. IKIl-- I II.,. ....."'fltallOn •
•-xtcrior. 171l. 178-180 mtericr, 17(>-1,., Space Imaging, lne .• IKO 'I OS. 11-1 J. 235 -231l Spa.'e Shunk phol,,~r,lphy, 245 -2"7 Specia l Sen,or Mic ruw avc/fm agcr (SS M/I l. .U n-3 _~ 2 S 1'111 I l1l a !! ~ Corporuuon. 223- 22') hi~ l
s..,il ddil1llion "I' ..... tum, 50>; grain sile (sand. silt ;lod clay I, 50!l ~511 ho n 71111S. 50l\--51)1l bedroc k. SOli ")flO:
o f eluviauon . 50S
mn c o f illuvialion. 5011
reflec tance dom inant fa cto rs . 51 ll- 5 17 air -soil interfac e scauc ring.rctlccemcc. 510-5 12 iron ox.de, 515-51 6
59 1
,"ohturc colllcnl , 5 1~-S IS
Ih...rmal infrared remote
..rgas uc m atter. 5 15-517
salinuy, 5 I5 517 stlil c m"N. 515-S 16 subsu rface volu me scattcrinJ,:"rdl~'l:lancc. 5 Iq surface toIJ¥-II~,. 21(>...217 texture. Si ll SlJ h)dr""yl al"""l'fIlilm bands. 52] intcrsunal air ~pac~"" S13
melhods of 'lewmg.I M- IM principles. 162 - 16-1 St('T("Omcll"f. ~c Parall ax ba r Stereoscopic
model. 150 pa rallax . 162. 1M [74 \ ie \\ ing a l i ~l1Incnl tl f r hmo gr
T Tangent ial scale distoruon, 2MI-2fl') Tempe rature cn 'ss~l\Ier periods in. 27~ 277 diurnal. 274-170 imagl.'l' l, l~ sec thermal in frared remote sensing km cnc [ t rue ], 252-253 radia nt, ~ 5 2 -253 'I empcral resolunon . 14, I 7-l li r"rr
tenu re drai nage. s...... Dra inage patterns photographic . see Elemen ts of image mtcrpretano n in radar ima g...e. sec Radar, terna in. surface roughness Tbemauc Map rct (T M I. see La ndear
N tJ- 2<)(). Chapter K
sources. 2n
l.;]\ oo
SO:\!\R. 4 :!~ ·CS Spectral hands. SC'e Band ~ ctme ~leClromagneiic spect rum Spectral reuectaoce. 14 -1S. "~5. Spcctroradiometers airborne. see AV I IUS. { 'ASI-I ;(10. MO()lS handheld. 2. 5/)'1, e ha»!cr IS Spectrum c1cclroma!PlCllC. ll·e -+; SR-7' aircra ft. Sfl....X \ Stefan-Boltz mann law. 254 Ssere....SCOfty. 11'> 3 h)po:n.tcrc<>cwpy. 1M
.cllSIl l jJ,
calibration raJ lumetric. 2M 27 1
Therm a l rrof"l'Tt ic~ capecuy, 2(>4) con ducnv it),. 2W
inertia and apparent inertia, 2bO Thermogra phy. 24q Toumachou. Gasl'afJ Felix t J\AIHR). 67
Trcnsmutancc.c-t Tran cporta uon intra vtructure. intcrpretauon of. 4lN....-N 5 airports. -In boats a nd ship:.. -I~ rt>;Ids and hig hways. -IQO rarlroads, '; YI Trc Uis dn, i na~ e patte rn. 52(,--527 I'ropic al Ra infall ~kasu rill g Mis si"n (l'R MMI. 33 1-33 2. 4311--13 I
U U- 2 airc ra ft. 77 1I0
Ultraviolet mdiutmn. SIT Hands o r the elec tromag netic spectrum United Sla ll'S(,,:" klgk Survey ( USGS) land lise land cover elassifinrl10n system, 4; I Unmanned acriu! vehicles. S5- S ~ Urban. 44 ,' - 50/" L'h aptcr 13
developmental cycle. ~-I'; -4~1\ ht'at islan d , 2Xf, -2 X7 laud us c/Lmd cover, sec Land usc/land co ver meteorologica l data . 49~ Urbanizat ion. ~-I3
V Vcg<'l mion. 35.'i -Inx. Chapter I I agriculture. remote sc nsi n~ o f. 355 hiodheNiry and gap analysis of, 3'16-31)7 billmll-'IS leaf area mdcx ( LAI) o f. 2. I N> canopy model ing or. 371-372 chang .. detection of 3\l7--WO nn aging sf"l'Ctrumctry 0 1: 372 -373 inu lC<..'s. JlS2-3 ~3 landsc ape em l.'ll) mc tncs of, JQl -3%
592
I"' OEX
phenological
(yd~"I.
373
rnanaged.J75-J16 natura l 377-3S2 phceosymhetically active radianon ( PARI. JMl rcflc..'13n<;:C dom inant (acton.. 356 chlorophyll a and t> piglnt"llls in, 10\\l1' cpidcrmrs. 355-360 pah~ IIle!\.Of'h~ 1I cells. 355-360 sJlt,ngy mC!otlph> IIcells• .' (i1- 365
upper eprdermrs. 355--300 ot her pig me nts anthocyanin. 3Ml canncncs. 359 xanthophyll. 3.:'i') phycoe ry thrin. 35" ·3M) ph~ c,x)' ll n m . 359- .•(,0 lcafndditivc re fl ec tance, 362 -3(,) lea f water con te nt. .•114 _) oti bidirectional re flectance dembuticn funct ion. 367- 37 1 u no!')' closur e. c hlorotic. )(,1 phcrosynthesi s, -'55-3 51> Vo k ancx"S. 530-534
reflectance domina nt facl"r~ bottom radiance. 410 chlorophyll. -II ~~J in eoo~13 1 and inland water. 421-422 in ocean .... all". 42lJ..--422 dissolved organic material. -1 15 G..:Ibl.tulTc. 4 ~ J free-surface layer radiance , -I1lJ..--41 I subsur face \ Ullllllc:lric rat!lall\:c, -1 1(1.--1 11, -1 15 suspended mi nera ls, 4 1~-III< wavele ngth. -1 11-1 1-1 sno w. 435-1 37 surfac e ex te nt mar r inl.l. 41 3--114 t ...mpcratu r.... -12(, -421< vapor. -133. -135 \>"':l\l' lo:nglh J O Ill inant. 3'1--1 1. -I J un its o f m c asurc mcnr. -II 4-1 \....ien's Displaccment law, W--11 Whisk broo m scanning, 1')" \....indu .... s. a tmo spheric . 51 -52. 253-254
X x-purJll;u.. S<.'\: Parallax ,
>t...rcoscc pic
W Waler. 4~2 . Chapter 12 bathymetric mapping. 423--42" U DAR. 425-4~ " optical. 423 SO'l r\R. 424 ...t! S c1oudsA32 -435 optical properties. 4 \ 0---4 14 penetration. 4 11-1 1J. 4 23-4 20 precipitation. 4 2K-43 1 q uafuy modelin g. 437-43'1
Z /.(lOm stereoscopes . t" 7 Zoom-transf...r-scupc, It> 7
S ila lia l :IOd Temporal Resolution for Selected Applicntiuns WtI
.11,1-
"'x"-
10
I a
be
Utility, Transportation Infrastruc ture
...........L~I~~I~~~~ .1.6. ~~ !~~i.:'~1
0.1 Precision Ag ricu lture
• • • • • • •• •• • ~ ~~~~I!l~~~. ~ .d.ay. ~o:.\!~i~ _ J satellites : -l Jay rc... isit
(WI
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r
a
l' ...fJ
, ~
..:..:< 100 m
~
"
I km
10 km
100 km
No minal Sp;lIial Resolution
, • e r
Color Plate 1,1 l he nonuual «pauul and 1l,'IlIi"lntl r<'s"lnl l\l1l charact cri-uc s 101' ,d<'<'lnl :l1' P!i,',ui " ns are pr"'''llI <",L w hen couducung
Sola r a nd Hcllosph eri c Observ atory (SO Il O) Imag e or the Sun Obtained 011 Septe mber 1~. 1999
C o lo r Plate 2 · 1 An image nf the Sun obtained Ily the So lar 311d Hcbospheric Observatory {SO HO I ElT ins trum ent on September 14. 19V1 (cou rtesy Solur u au Analysis Cente r, NASA God
,
' -"Ullt., Pon ton nf th e Elccrromegncu c Sp('('l r uni from .snu to 7UII nm
5 >ll1
500
Xanu mcte rs
'~. /
1'; ' ~ ~
./ 3
Gamma
sc
X-ray
Ultraviolet
I O!
I O~
./
..
7;.
10'" (~,.m ) §'t.m:Al'ht - -
Radio
".s t
., 0-
es
"
Color Pla te 2-2 The portion " r llle electromagnetic spec tru m \ is ihlc by hur uan beings is ge nera l!) cOlls i.k rcd to be from -lOll
ttl 700 nm c,msisting o f hl llc(..\OIl .. j (M I nm). grt"t"1l l5UO- f>OO nm ]. and red ("Oll .. 71M) JlJll l light, Th o: image o f the solar spec trum was obse rved with the Fourier Tra nsform Spo..'Ctrmllch:r at the .\ h; \-l.llh· Pkrct: So lar l' acilil) at Kin Peak l"at ilma l O hSl.'TVat0I)'. near Tuc s on. AI. Eac h orshe 50 s lic('~ covers Nl angs tro ms lind wavelength increase, Ir orn lop to bouom along eac h slice. Nut.: tha t it con ta ins rclauvcly narrow. ,furl Fra unhofcr lines n.1lI1cJ for the Germa n phys idsl Jos eph von Fraunh...r... r ( 1787ll'l~o) who " mappe d" thc location of over ;70 of the m In thc solar spectrum. Later sciennsts dis cove r ed that the: da r\. lilll:'"' an: ca used b~ cheuuca l clcm...m absor puon in the uppe r l.l} ef ~ uf the Sun and some .Ibsorpllu n b) o .l ) ge ll mu k,<:u l.."S in the fanh 's alrTl(Krhcrc 11e-c'<1 with 1"'1'llI ; \o.~ iOl1 o f :\ . A. Sharp. M )A( )11\";( I Km I'e:&k ~TSJ,\ U R AI'\ S ~· I.
H urr lcan c Katrfna Damage :11 G ulfp o r t. :\ IS
a Low .. >hli
l lit:hway 'It),
"",•,.. r-
o
b. Vertical aerial rhol~r.!rh ofthe Grant! C asi lKland ~u rTOUnd ; nf area o Naiocd at a - paual re~oltll i,,,, or 37 a .\ 1 e m ( 1.2 .. 1.2 fll, Co lo r P la te 4- 1 a ) 1 " w....., h li411" ae rial ph" lugra ph "r w intl " lid ~l"rm surgv J am ag..: L'a tlsctl b) I Iurricnuc Kamna at Gu lfJ'l,n . \1 S. obremed "11 August ~ (). 20H5 (c' " 1l1e ~y "f I IS{ iS ( 'O;"I .d and \laTl n.: (i ...olog) I' I"tl~ Ta l n ) . t>J Vertica l ae rial plHll0!lfllph (co unc, y of
."\( l -\A l{e lTInl<, Sen_in],! 1)1\isinll l.
Dispe rslun o f W hil e L igh t Th rou gh
:I
P rism
.-\ddil i\ e Col ur T heory
Sub rructive Colur T heory
b.
c.
Color Plate 4 ·2 31 Sir lsaac
~ <'WII1f1 discov er ed th at ",hite l i ~hl could be dispersed nuo u-, spectral components by p;lssin g "hill.' light throu gh 01 pri sm ( " rl a\id Parker, 1"Wlo Resea rche rs, In.' ,I, h I .IJdil;n· ..,,/"', Ilu,<>rI' - <'GU
•
.\."".n.
~:\pn'"r(".I }(·Hlnl'nlt· n l .
lind (" nl n. Furm ,Uin" nn ("ul n r Film
r.n...... "".
a
... ( ;'C<'n · ,he
HI",, · It,.. romphrnenl~f)'
,i
0 .1•• of yd l,...-
.,.,~
[ 'l. l-'u ~ u r{'.
RC'd · ttl<'
«'OtOph""""~,y .'""ph""",'~1)' "" k... "fma~·.,n'. ""I." ,,{ ~~n
Developmen t, a mi C n lor f o r mal in " un r ll l, \'· C"lur I nfr ;lr c d ..-jlm
\."'
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:::r-
r. n""tan«
::I"
K. Hln,
\ oil " ..· \ \ n tl ,'n 12li ll n 1" lu.-bl" ....,i n~ 1 ,ft., [::~:;!~~~~;:;~[!!~:i:l~;;::E~E!!~~::J
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A.l ;\'B,.d L _ ,_ _...1__, __-'-""''''''''-J
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. , "liTo
c. r:ill " . f l n .-"1,,, "·,,,r••1 I'roc.'"i n~
, , "I "I •" "I I •" "I ",. "• "I I "I , , I
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Color Plat e 4-3 Process or ""P'-""inl!. ..k \duping. and fonuing ctllor VII atuormalcolor film.•md bj falec-color infrared film (<:olll1c..,y Uslman Koda k I.
Tivoli :"Oo r- th Bay un th e Hudson Ri ve r , :"O Y
a. Norma l colo r aeria l photograph.
h. Col or-infrared aeria l pho\(l~rJ p h .
Color Plate 4 -4 ar A normal tnatural} color plwlll gniph ....f Til o!i N" 11h l3"y ailing the Hudson River in )'.;C·WYork. CUlM ..eria l rh (llogr;lrh~ rec ords blue. grc-.:n and f C-..J light reflected from th.: scene. A bazc tillerl llF3 1 ilo usual ly placed in frotu ofthe lens to pre\'("fI1 scattered ultravioletlight from reachlllg the film plane, \ 'cgel.tlillfl sho...s up in green hues beca use the rlanl~ ah'Wfh more blue illid red incidcnt bghtthan gn.-.:n Iit:h!. h I A c(llof· i n lTaf~ aeria l phot ogra ph rec ords green, red. and nea r-infrar",t! hg hl ll'l1c'Cle d from Ihl' scene, A yellow IWr"Uen 11 ) filter h usuallj placed in fronl of the lens 10 prcvenll>lue light from reaching the film plane. The land-water interface is es prcinlly well-delineated because water a bsorb s most u f lhc inc ident nca r-infrared Iighl causing uro apr<"rdarl . VcgetlHion "Ilr
Un ive ... sil~ · of :'\t'h raska. Lin wln . :"'1\
~~;:::::;;;::-"1
a. Norm a l color aerial photograph.
--
b. Col or-infrared ucrial photograp h.
Color Pla te 4 ·5 al "Il" nn al (natural, c"l or terre- anal phowgmph of a huih,hnl! at the Un i\ cr~ll) of :"kbra~ka. b) C(,l" r· infr.
Remote
Sl'Il ~i ,, ).:
Ca II I' ro \ lde Knnw Icdgl' h~ ,\ h'a, ur i ll J,: r il l-flo:} C ha rac h' ri ..l k s in Sp l'r tra l Hl'g ion.. Uc}ond Our Human \'isu a ll'crcl'IHinn
(
r-
.... -
.... -
3_ Gl'C<.'1I r... l1 CCld llCt: of llJl
a~ricu llu ral
area in Siludi Arabia
c. :'\car-infm rcd reflectance.
d. Co lor composite 1RCm
-
ncat.infrarcJ, red. green).
Color P lale 5 ·1 :-'l lllli, p..":lr;tl imag ery of center- pivot ag ric uhurc in Saud i Aranla a.l1 ) " cg.'t ali,," ;lll'l(lrt'o .. m ost o fth ... gr.....n and red irn: idenl l'lwrg y ca us lUg \ .:gcl;llcu tields 10 ;lppcar
'-'-I)'
.J
Planimetric In fnnn atiun Ext r action: Acro-t rta Il l!ulal t'd Stt'n'upair Ui<;pla) ('11,\ ll a ~ l ) phi (' all)
Color Plate 6-1 Anaglyph su-n.. opair of Colum bia. SC, created lI~ i ng
E'h'ri u r Orit' u tatinn : \\ l·\ , j n ~ h n ll \l' Sa\ IUIlIa h Riv er Si u ' S ll"rco \cupic Colk1."li un of IllIll!:l' Coo r d inlltC\ of (; r" und Co nl rul P" in"
,
•
I
""'l --r_.... ~ru::l"~r-
. 1Y~) -: r-
,. ,.
~~
I
• Plate 6 ·2 a) b . ter " " oric...I;llill" "fa "Il·h ....,... ir of the W~'!il inghol1'>C Savannah KIH"I" Site ncar Aiken, S{ ' t> J The otl-.;opy phOl~r.a mm~"lric t~-.; hl l i
Planhueu-ic Info r ma tion Ex trac rion: Sh' rrnw u pie .\ n a l ~ ~ i ~ 'If An ,\ n a :.:l ~ p h ....It'r t'u pa ir l r ~in J.: th... . · I u a , i n ~ \ Ia r"
a. :\Cf\.. lfia,,~ub'~'ll anagl)ph ~l"f."'>pa" analyt.-.J m Ihree.,J,n"",. ,..,.. '0 t'\1~("1 r 1anim.:loc OOa\1. Please vi..... ' h,s ~r,"",>pa\r llM n~ lIIl
I> lluolu ",1.l r"" rl'rmb. l'
"M gl)l'h ~1"n'<"J'll' 1
.h"".. abov e
PI"" "" ",,,,, th" .r ~rt't'l"i'" ",mill ~
""""""'."1"<'.
Color Plaia 6·3 al This a n.l~d )ph stcrcopair ~ JS ;tnalYl cd in t hree -di mensions u,mg lhe l1'l;Ililig mark III identify three building f('l(l(prinl. till- perimeter o fa rc tlecnn g pond , and >I street centerline l>l l'he l~alU r~'S e \ lrdekd are J r"pla yed ill 111<: ae n l-lri:mgulatt stcr~...>pa ir
and can he \ i~· ...ed ...ilh a stereoscope.
1
USGS (,'J"b,,1 J 1.Hllllb ,rioll Ilewer
ll. St.-an:h f,'II" 1n1d~'<:1' . 'f l"h.Ulc1.l00 . SC. usin~ the cntena: Pa th Iii and It..... 37 . Land-a l 4·5 TM. \ b y 2005. 10l"'~ mH;m um dou
•
. '_
0" ••_ '.
1>. Sc,,,ch. fo r Chari" " ..".
~.
using
ri ~d,
'"""mpled to 240 m .
COO" Plate 7- 1 US<' n f l lll' l 'S(i S ( ;/,,"'11 I ;' II,,1I=
La ndsat 7 En ha nced T hema t ic Mapper Plu o; Illl a ~l' r~' of San nie~ll. CA
Color-infrared color eompocitc tRGR " h;mds .J, J. :!) , Color Plate 7-2 C" lor ctlln posi h: of l andsa t 1 Enhanced Thcmauc Map per Plus ima ~ el') of San Dr.-go. CA, obtaineJ on April 2t :!III)O t cou rt...sy "f 'I A~ ,\ )
- 1 - - - - - - - - - - - - - - - - - - - --
~():\A - 16
Ad va nced
\'('f)'
l ligh Resolution Ra diom ete r (A\, II IU{ ) 1111 :1 :':('1")"
- -
Sea-surfac e tempe rature (SST) map derive d from )\;(JAA· I(, AV!l RJ{ band 4 (10.3 . I I.J Illll) imagery obtained on October 16. 20D] . Color Plate 7-3 Scu-surtace 1"'I1\I'l,'r alUn:/ SST j map derived from ;\JO:\:\·I h A\ 'IIKi{ thermal infrared imagery [co urt esy of ~ (lAA nud the (k cJI1 Remotc Sen,i ng Program al J"hns Ilurkins University:
Ad va n('l.'d veey II igh Resotu ttcn Radiome te r [,\ VII HR ) .\ I II \ :I ir of the 1'l\ih't1 Slat e..
,. :\vcrage ' \ UI:II\ I ,\ \ "11 RK Nor ma lized Diffe ren ce \ '{'g l'tatinn I nd cv (:\ U\"I ) t t,lH I - 20110
Color P late 7-4 ..I ,\ VIIRR mosaic of th.: conter minousUnited States deri' cd from
Si .. tCL'1\ 1 x I km '\I() \A ·Kand '\10.-\:\ -<':\ n l RR inap! c bmrned ITlIm \-ta) 24, ] l,l1l4 . 10 May 14. 1'Ixt>. u~ing c hann.' j, I ..nil 2 t IlIUl \tC c' IUI1 ,"' y " f I\.O A ,-\ and U.S. ( ico lo~ical ~ \ cy. b) Awrage A ugu, t '\Ionn.lli l cd D ,lTcrL'11CC \'cgcWlion Ind.':I. t \:[) V l l lI l\ ;lgc o f :-,I,'nh :\mcn<;a derived from AVHD. im
--4If~-----------------------------
Ai n ...aU ' 1II IIi~ p Cl'lr a l SC;lII IIt'r Da ta of Four .' Iib- e r n ·... Delta in Suu lh C a rolina
Dacdalu-, ba nd 10 (O.')::!
1.10 1"111 ) on .\I an;h 31. 1':l81.
c. 1)J.cJ Jl us band ltJ (0 ,'12 - 1. IO lJm ) ....1 ,\ pd l 23.
R
OOnl~i lC
b. Color-infra red
( RGIl - bands 10.6.41
(;"l1l po.,~j l<:
(RGIl - hands 10, (', ..h
Color P la le 7 -5 D"cdahlS US- l 1(,0 uircratl muluspccual scanner inlilg..:s ofthe FOOf M ,1o: Cm: ~ delta on the Wc sl in ghtlu~ ';tV annah River S ill.". ~C. Band 10 near-infrared rmape obtamcd " 11 !\h.r ch J J.. I'ilol l . bl Color-infra red wrn pusilc .':l (lind 10 image obtained UI1 April :!J. 1'I<):!. d l Color-infrared composite. No te th...diffe ren ces in the werland vegctauon drstribution in th... sloughs ~1 "H'Cn 1"11 1 and I'N,! Iimag,·s C\ltJnCSY of Wcslinghouw s...... unah River C U!ll pan~ and the Department of Energy ).
;J .
,.•
]')<)1 .
b. Color- infra red
SI'OT:, Jm:l::t'r y or 1.11.. Anuetev, CA
Color Plate 7-6 '>!><) r 5 imagery of Los Angeles. CAl» me~ i ng 2.5 x 2.5 m pJ.llehrom.1tl.: wit h 10 x 10 m muhispec tra l dam. The cry wa.'>lb apo:d over a 30 x 30 m CSGS terrain model ( SPOT Image lnc.],
Purtton or th e Firsl G loba l Ten - Day S ~ nth eviv Im age Produ ced U~ i ll :: t he SPO T \ 'c~l' l a t i oll Scn sur
Color Plate 7-7 Punion <>1' ... Global Ten-Day Synthesis geiler-lied u,i ng the SI' OT of Vcgctalioo!iCr.Slt 111<' daily product pro vid...~ \ .:getalioll indo. iuformution ill ~l spatial resolution of 1 x II,;. ove r the whole l-a rth. The Global Tcn·!II!'
Synlhesis is derived from analysis of W S yn lh e s i ~
:-'I...~, 11-10. 1')98
dalll ( ") S I'l l ll lllagc, lnc.j.
Terra
AST E I ~
Op tica l lm agcr y of Oahu. Hawa ii
a, ASTER 15, 15 rn colo r WllIlX"ilC obtained "" June 3, ~nIK) ( RGB - "'l mh 3. 2. I I,
" m
'.
"
b. Enlar gement centered on Pearlllamor.
Color Plate 7-8 Terra ASTER irn;l~ery of Oa hu , Hawau (courtesy uf "' AS:\. (iSF l·/~ 'lTl/E RS :\DCd AROS. U.S ~ J;lroan ASTF R Science Te-am, and the Cahtortua lnstnutc l,f Teehnologyl.
I ~O\rjOS
c. £b ud
~
\ 1111Ii~ I)t'c l ra l
(0 ,70 - o .<)(l !-lm l 4
~
and l' unc h rum a ric IlIIa:.:cr y uf C ultllu hia. SC
4 m.
d. Panch romaticba nd 10 .45 · n ,'lC) !-lm) 1 , I 111.
e. et,lur cnm p<" ilc c RGU - bands 4. 3_ 21. Color P la te 7-9 IKO\;OS imagery " fa I>u~i ucss park in Colu mbia, SC'. a J ) In,lividll.II-l )( 41l1 I11uh isp<.'\:lral bands and the I x l mperr chromatic band are displayed. <' I Standard color composuc " I' IKO....( IS hand." -I. 3. and 2. l) ( "O!Of comp
AV I RIS Im a uc of I\loffl'lt Fit'I{!. CA
'''p
Image on o rrhe dsta cubc is a colo' e" I11 I'<"'lIC of II1Q~ "f mc 224 band s
c\-af'l>T:lI,on ,./ I"md~
214 hands al lOom
lJon
11m
nUl11 illal band... iUlh
l.uNI ern
I
l'IlK) nm 25(Nl l1m"
Color P lat e 7 -10 An Airborne Vb iNe Infr.m:tl lmJging SrcClnlmel"r \AV IRISI tlatascl l'f \ 1" nc u Field. CA . adj ac ent 1(1 San I runciscoHay . The data ...-erc acqurrcd Oil AU!,;ust 20, I '1Il2, toy ,hi.' NA:-'A 1'.H:-2 mrcrattta m"Jilk tlL"- 2) .n an a l1 it ll(lc of 2H.OOI)m I(,SJl/lO tl.) r''''u h inJ; in 21)x 2U m ""fIlmal ,p;tt ia l resolution. ..\ " IR IS acquires images in 224 ba nds ea ch III nm wide. in the 400 10 2 5ll/11l1ll reg ion. Three " f llle 124 ~I'<'clr;ll band s (If JOlla were used to produce Ilw l " I!Of Cl)!\ll" ...ire on 1" 1' " r the "h~ perspccnal dat ac ubc - 10 ac,'elllu;lle the ssructure in ' he ...atcr and in Ihe e\ a pornl ion J"'m js " n the right. The ~i "es of the cube de pict j ust the ed ge pixels 1;'>( all 224 o f tile AV IKIS -pcc ua! cha nnels. The top n ftllc' sides arc 111 the visi"k p;.tn ofthe sl-ccuu r n(ollK I nm ) a nd the I"..IIt"m is in the middle-infrared ( 2~1l/1 mil). Th e bluck a",,,, in the duacubc rqll\.~nl almospllerk ab:Kl!"pt iun hands, especially at I-lOO and 19/11) nm . The ~idc's arc' d l ~pI3y ....d in a pse udo-color rangin g fro m il iad and blue t vcry lu I' fc" J't'IISC ) to red Ihl!!11 fCsfl" ns<'· I. ( If pan;eul ar ;1l1er<....' 11I 111 e dat acube is lhe smal l region t,f hig h rc...J'tm"t' in Ihe LI pper r ig hl corn ...r of th... datac ubc j u-a 1'...: 1.1\\ the c vapo rariou ""nd,. This res po nse is in lhe red pan u f the v isiblc spectru m t nf-out MiU 11 m I and is J ue to th c presenc e of I e m In.; in. I lo ng red brine shrim p in th.... cv ,1 J't'rali'~l J't'nus I court c,) of R. ( I. Gree n, 1\" 'i:\ Jet Pn 'pur, ion l ab I
•. C" lor'lnfnu'e'd pMiograp h.
,
Color P la ia 7·11 I-me T!!" ()i~ild l s<''11.;c \f S~Slc," t Ih S Idata. a ] ( 'I>I"r- in lr"r~-d irnag.. ( f{( iii = near-m tra red, re-t. and gTe.:-n1otI xm kirk. ~"' . al I )( 1 III Ilblailled on Decem ber I~. ION.'!. Tlk: l cnn i ~ court am! tr.ld .. arc covered with astrotur f b l Natural color imagr t l{( i II - red. green. and Nue Iofan area :l
Ther mal Infra red and C ulnr \ ' i d c o~ r a p h~
or S Cl.:lIl l' ll h or t he Um pq ua Rlver Hll, jn in () rt'~n ll
a~;u!u
as 31.0
n. F olor de nsity sliced the rmal infrared image and natural co lor vidcog raphy of the con fluence of the Sou th Umpq ua River (27.5 "t' I ar1
h, Contlucncc o f Wn lfC rcck 119 ,7 "C ) 'InJ l.iuic !{ in'r (22.S ~C l ;< 1 river mile 11.
CWf Plate 8-1
I' ''rward-l"okin~
infrared (I"LIIU imagery of two segm,,'nl ' (, f th..- I 'mJlo.lu;l Ri\C'r l ~a-,m d , ~pl a ~('d a lo n}! '" uh narun..l-color at the sa me time . Th<- thermal-in frar..-.J data were c ClhN.aI~-.J I" surtacc temperature and color-ced ed Idc nsuy sh ceo.l ). rile remote >-Cllsi ng .de rin-d '" aler s urface tcmpcrmurc mc-as urcmen te are generally '" ith in 1. n.5 -c of' thc u"': kinetic temperature {imago:'s court ..,sy " I ()rcg" n Departmcm (,f Environmcuta! (J u;d ,ty. ~ O()3 ). ~' idCl~'T.lph, ohta;o<-'d
•
Thl'r1uallnfra r o:d Deteetion uf Thermal w a ter " " Il11 li" n in Iht, Sa\ lInl1llh Rn er
3.
Ikn~lly ~Iict-.J
I'rOOa"'TI therma l
in rrarcd l ~ - 1 4 I! m l J.lla .
h a ll",c lllll i~ '''l:ra rn
T nll "" '1 LUI(i<"
>20" C
"'0 En<.l in ~ rl~ <:1
in
rran-cct
2. <
,
E~
.Il" lw river amllk-Ill
wh ile
1'''lIl I'C r:ltU!C
10.2 • l It ' ('
red 140
~
c
Bcgillllilig ph d In u auscct
::c
J 20
'~
J()(I
g
8
5,2 · IIl"C
-r-c
'"
12" C riv er
'" '" "
ambient
'"
211
,. 1)
411
Pixel in I ran....-..:l
"'
c. C o lo r Pla te 8-2 3) Dc usuy ..heed d l"p I3)' .. r prcdaw 11111<'rm ;]1 in frar<:d dal .l " f til ,' Fo ur ~ l i k ("rwJ,. therm al plu me in the Savannah Rl\(I' llI \ ta n; h 2S. r<,lx I 12.1'1 x 2.1\ m spatia l resolunom, Ihe data are color-coded aCl'Ord ms tn rhe eta es intervals su mmanzed I Table S_lI. 1» , Three iransccts are passedthrough the plu me atlc r roc
SP lIC{' S hlltl lt, I'huln l:,rallh and S I H.-ClX-SA R 11II;ll:,t' of tilt' i"i1c River; S ud a n
;I.
Spa~c
Shuttle photogra ph.
b. SIR..('iX ,SA R image.
Color Pla te g _, a ) Space Shun k photo gra ph o f the Nile Ri\ cr. Suda n. l:>l SIR-C/X-SA R color-composite ima~c of C-l:>;lnd v. nh II V polarizauon, L. b.> nd with II V IX,lariL.lliwl, ;lI\d L-rond with 111 1 pola rization Th e dnta wcr c acqu ired hy the Space Shu nl ... EII-
d"",,,r in Apri1. 1' 1'1-1 (councs y "'AS A lei Prcputxion l.ab j.
S I R-C/X -SA R 1 11I ;I ~l' r~ o f Ron do nia , Hrll/il
Color Plate 9-2 SI H-C1X · SA R image or c pon itlll of l~ undol1ia, Brazil. obtained on April Ill, I<)<)-1 . It is a color composite o f Xband VV pular i711tion, C -band I IV 1'0 lanzation. and Lcband !-IV polurizalI ea\ y precipitation appea rs as a hla.'k cloud in the X-hand image, mo re faintly in the C-oond image, and is relatively in_isihle in the Lcba nd imag e. Til., hright pink is rainfon: st lcoune sy Nt\'\A J..t I' ropuls ion Lah },
uou.
X-hand\'\'
-band U\
L_haoo IIV
SII{-C l.- Uand a nd Ccu a nd Int crfcroa r am s nf Fort Irwin, C A
C OIOf P la te 9·3 SI K-C"X-SAK intcrfcmgrams of Fort In, in, C:\, in Ih~ Mojav e Desert The colored b auds provide Ikl nikd. l.j uamilil!llt
ekvati un informat ion that can be USl..'"tlIO con - rr uct a d;gila llcfr'tin model
( c (\u rt e~ y
l" l\SA Jet l'ropulsiou La b}.
Color P late 9·4 Three-dimensiona l (l<.'T'!
-,p-- - - - - - Ui:.:i131 rle,-ali,," \1 t1dd of the Wa ~a l (" h rronl in t:la h llerh ed fro m S huttle Radar TopogTaph~ \ Ih\i nn (S R " .) Ual a Ur:apl'd "ilh Landvat Th ematic 'lappt'r Ima l.:l· r~
W;""lch \ 1'HII11:lin Range
~ Pla te
9 -5 al SIH\1-
C om pa ri son ofGH) I'()JO n E:'\1 and S R r :\l-d(' r i\('d I) E:\I of :\loUl1 1 Kila ma njarn in Ta nzania a nd "':('11) 3
,
3.
GTOro30 I x l krn digital eleva tion mod el.
c. GTOP0 30 I 'I I km lli£ ilal cle vauo n model observed from an ubljquc vanta ge point loo king \\"-1\\....
b. SRTM-J erived 30 .\ 30 111 digilOiI elevatio n model,
d. S RT ~ I ·llerivcI130
'I
j n m digitill ele vation mod el.
Color Plale 9-6 a) GIOI' OJI) digital elevation mudd al I x 1 m. T his is pun of the global GI OI'OJO DEM database maintained b~ lht USfi S. I'!) SRl\.l -dl'rh l>d l>EM at J() x 30 rn. e) (iTOPt no IWM \ iewed from the w.r-.;w d l SIU M·derived OEM \~ frum the W·NW. NUle the detail associated with the small cinder co nes l'fI lhe Ibnl.. " r lhe Ill.'untain (images courtesy 'i .-\SA Jet
rnlrLl I~ i "n
l.a h ).
Adv a nced ,\ Ik rtm a' l' Sca n n illi,: Rudjurnct cr (A \ISR- J:)
3 C" ml""'ite of A\f SR-E derived S<"a
1c
~urfa.-c
temperature (SSTl f,>r June. 2002_
Color P1ale 9- 7 a) Co mposite imag e o f Advanc ed Mic row ave Scanning Raduunc tcr (A /l.1SR-E) d<'rivcd W;l sur face tem perature (SST) in the birthplace of hurricanes, the 1I1ICNll.lpicall'On\crg",ncC' zone. h ) A j-day iI\Crag'" of SST for the Caribbean Sea andthe Atlant ic Ocean from August 25-27. 10115. de riH:d Irom the .-\ :MSR-E. Warm oecan ....atc r fuels hurri ca ne s. and there was plent) of .... arm water for Hurricane Katrina to huild up stren gth once she: crossed 0 \'<:1" Flori da and mo ved into the G ulf o f Mex ico. All }ellnw. orange o r red water IS ::: 1 7 ,~ C 1 ~1 Fl . r\ hurricane r~q ui rcs SSTs .n about this leve l o r warme r to streng then. CJ
•
?
Swectuum (Liquidumbar .\ /y ruci flua L. ) '~ ~
• ••
•
. • \ .~
~
., .
~.
••
•~ • •
"
•
• , ,.-
·• •
,"r
•r
'"
70
."
0" t c" " ~
red lea f
60
50 yellow lea f
40
~ -'0 e
"
~
G
B
brown leaf
R
20 to
e.
green tellf
•
NJ H.
0 .J(M")
SilO
(,1)0
70f l
' OIl
-n ll )
10110
Wavelength. 11m C o lor P la te 11-1 1l1 1 'h\'llls> lIlhc"I.f In~ green Swerctgum lea f (L1 ,/wd
\
O r u und Reference lnfurmarion Ov crtatd nn II S inJ;:ll' Channel of ,.\ VIIUS IlIIa:':t"r~
Sa il Luis
\ ·all l·~ .
, "c l-:d :H ill" (' I""ili,,":.! Iion '141.)1 Sl' pl t' mhl'r J . 199J
CO
b. _
alfalfa
II
o at
II barley
h;J)'
\' l'~(' l at ill ll
••
canola .
~ spinac h
pasture
D
spi nach
II
nothing mapped
II] potato
_....
SCfl("' ('t' n n'/S l n '\\ .\ Ia p
healthy green vege tation dry vcgct.uicn' bare gro und
•
stressed vege tatio n
Color Plate 11-2 a) ( imund reference mtorm anon overlaid nil a ' ingl... channel of :;n x 2n m .o\VI!-t [S d;lla C't>l amed on ~epl ember J. 1'1'13. b) \ 'e ~ CI>l l i lln - pccic, c1Ol--.,; ilk aIlUll map derived frum JIldlpi!> o f A\"IRIS d..la l'l Ve ~<;tauun sen..esccncc stre ss ma p JOI ne r ('lark <,I ;11., IINS).
3. CA ~IS data (RO B = hands J, 2. J).
b. c,\ ~ I S data (RCm = hands o. 4. 21.
Biom a ss in a Pnrtfun of :\lurn'lIs Inl et, SC, Deri ved fro m.3 '( .3 m C a lib ra ted Airborne ;\l ult islll'l'lni l Sca n ne r (C A MS) Data O b ta ined o ll l \ u gm t 2, 1997 T o tal Bitllll
500 · 749
I
I I
I
I
1000 -1 49'.)
I
750 · 999
ISOO· 1999 2000 - 2499
c. Map o f biomass.
2500 - 2t)1)\}
Color Plate 11-3 a ) Nalural color composite of'n sma ll rtMti nn of Murrells Inle t. Sf". r~'C,>r
Phc n ulogtca l C ycle u f C ro ps in Ca lifo r n ia 's Sa n J oaqui n a nd Im pe ria l Va lleys and La ndsat ,\ I ull islll'ct r a l Sca nner Im a ges of On e Field I)UI"i Il/.: a G ro wing Season
Su/.:arhl'l'ts
M, y
Ripe
J une
HarvCSI
July
Au g
Fie ld prcparauen
S~'P
Oct
Ihll'i n~
Emergence
Plant ing
Thi nn ing
C otl o n
,,,
f
Mar
FielJ prepara tion
Apr
Planting Emergence Squa res
Bloo ming
seumg
Bolls
Roll,
s<.'t ti n ~
opcmng-
Harvest
Discin g Plow ing
defoliation
.
~
"
,-,
"
,
•
Floweri ng
1
{,
1Sl cun ing
2nd CUlli ng
3rd CUlling
'
tee,
-trh CUlling
Sth cuuing
6th (lilting
Color Plate 11-4 Phenological cycle s Il f a ) sugarbccts. h j conon. and c t 311:111":1 grown in the San Joaquin and lmpc rial Valleys "I southern Calilom i ~ , Land sat !'.ISS images .... ere I>b tuin..-d ov er a 12-month period ill Ihe S.lII Joaquin Valley. 'Ill..• colo r composite imagC5 (RG B - hands 4, 2, I) of three lield ~ arc ~"'fraCIC'<1 and placed hdl,.... the cro p calen dar inform atio n.
C hl\ !'l ifica li un ,\ I ap uf Imperlat Valle)". C A. nil December Ill. )lJH2
Deriv ed fro m Landsat Thematic
~ laIlP('r
Bands 1-5 a ud 7
a. HI ba nds 3. 2. I IRGB).
b. n t bands 4. 3. ;; (RG lll.
c. T\1 bands 5. 3.;; (R G B).
d T/-o. l bands 7. J. ;; lRGTl).
•
II D
SlIgarh ...ets
/\ lfa1!;\
I I l 'O\\Illl
D
t'; 11 1,lW
c ( ' Iassific,lli' ln map .
Color Plate 11·5 a j Land....1l thema tic \l ilp""t natu ral enl(... ,,,m po"I1~' ,ma!!e nfa "..,n i' " l ofl he l mpo:ria l Valle}. CA . ,ll:>wm,'1J 'In [)"cemb IO. I 'III:!. h ,II Set e ral t>lher ralsc--<,,,l,,. com po "il,·~_ e) C1"...,iJi,'a llnl1 mal" ,krl\CJ h~ ,hgital im"ge r rllcr.'Ss;ng _
r\~ricullUr aJ
Landccver .\ Inn;.: th e .\ l l1 lalh u, e River in Suuth .-U r ica
a . Part of Water :'\lanaI:emcm Area fOb; L'sut u and ~l hl Jthule RI..::r cac hmc nts recorded 0 11 S PO T 5 imaS~7) collected on J a llU.l ~" Q. ~ l ll).l ( Re iB = hand, _I. :!. I ).
Sugarc.", c Citru~
Foresl Bu.sh \ dd I
11_Clas-aficanon map ,"'ri ved fro m :!11l)J
sri IT mul1i'pccl ral and p'lnchrum ali" .1.11<1 _
Color Plat e 11-6 a ] SI'OT II KVIK c"lur composite image of a n area " lung Ihc Mhlathuzc Rive r ill Ihe' Republic " I'Stllllh Africa. hI Remote sc-nsinl:!....lcri vcd classifica tion map o f the st udy area . Tf us . }~ of mfonnation is used II) the' Rcpublrc o f So uth Al r k a De.. partrncnt of Watl'r .-\ m Ufl> &. F....-e""l1- 10 inh-ntUf} the ill;Ji<:nll ura llan d cover (, ... int' UI t..l the W Oller ·' ulh on,... i" n and k e. soerce \ l.lIIagc lIIcllI System I WARVIS) "I" llial dec ision sur!" '" cysu-m lcnun.:,y Jen ....n o:t al.. ~(I( lf, )_
r St'a -vit'\ \ in:: Wide' ""it>ld-ur-Vit'\\ (S t'a WWS)
Im a g{'r~
a. Global chlorophy ll u (g m J ) derived [rum S":JWifS imagery obtained from September 3. 199 7. through December 3 1, I'N7. The warme r tilt: co lor. the greeter the chlorop hyll co nce ntra tio n,
,•
illlal!": of Inc EiL'tcrn Seaboard o f the U. S . 'W>13ined o n S<.l'lcmo.:r .lO. 1'N7.
b. True-color
~WifS
----,.pI'-_..:
c. Ch l.>roph)1I u .llstribu li"r1 on Scplembt.'"f 30. 1997 derived fmm ScaW iFS d ata
Color Plate 12- 1 Exa mples ",fs.:.a· ~ lc'" ing Widc ridd-of-\k'" (S•.'a WirS j rcmorc ....."'.. 11" data [coun csy NAS.'\ Goddard Space FliPtt CCllo tcr and Ort>it:ll lmagmg Corpo ration (ORHIM:\( il- t; used wIl h poamissi.....J.
.\ l OUlS C h l o ro p h~ 1I a Product
Color Plate 12· 2
Chlllfoph~lI " ,Ji, tn "u titm on ~ O\ ('Tll ""..r 2J. 21NlJ, al''"11 the '''It.llh'''
~l.l les
derived using the \
•
Lake Ta hoe, Ca tifum ta- xcvad a
a ll~th~ "I<:I1') dcnv... ,J fWIll [ ID AR lor depth' from 0 h'
b lIackscaner mf"m1<'I,un
I ~ m amI f r" m muhirk· ho:a m SO"' i\ R f.'r ,kr lh. > 15 m
mu llir 1c-h.:arn SO K I\R
C o lo r Pla Ia 12 -3 ill Hathymctry or La ke Ta hoe d...nv ...d us ing th...SH O A LS L1J).\1{ sy sh:m fur Ikrlhs < I ~ m and a KUlIgst-erg: m ulnplc bece '" It\ AI{ li ,r dcpth s > 15 Ill. 1» Brig ht.:r ' '''' es in rh..- acousnc had".c llh:r ,h ta ind icale harde r Mlrfa".:. such as rod. [}drkcr tone' md icarc ...,ncr su rfac ..·,. such as ....x hm... nt . T ho: surr""nd il1l! lau d I" a sh,..kd-rdlO.'fimage g...nerated from USGS IllIII U E\h. 0:) Tbcccnrratpart of the \\ CSI
;\,OAA A\' IIR R-derind Sea-S u rface Te mperature
xo Arramie On'(JII
.20 "c a. Compos ite sea-su rface tern pc ra uuc , SST) m;.p ofthe so utheastern
oO"f
bigfu der ived from A\' II RR data. 10
v-.-', '#. \
.-
'"
'or; 1 , ~, ', ,,,,.' ~
........... , •
< ,
o
.•
b. WurlJ \\ ide sea-surface temperature (SST) map dcrivcd from
~ O:\A - 14
:\ \ 'I IRR data,
Color Pla te 12-4 a) Sea-su rface temperature I';;ST I mar derived fnun a three-day romposuc nf I\( lAA AVlIRR therma l in frared l!;tla centen-d on Marcn 4. ]lJ'-N, Each pi\d " ,I, ,lll"caled ' hc hllthe,t -unucc tcmpc r.nurc that occu rred durin!; the three daysr ecurlcs) uf SOAA Coasla \ Se rvices Ccntc n. h) (JI" h,lI ocean 51f x 50 km SS Tre i dcnvcd fnun Marc h 'I , I '1'Jl) through March 1'" I '1')'1 \ 'l~ h" Llfs 1 M l,.\·\ _14 AVIIKI{ data (co url,'s> ,.f:-J( lAAi \' LSI)IS 1.
n
'I flnthl ~
Sea-S ur face Temperatu re ("C )
32 28 24
20 16 12
8 4
o a. La Nina in Dece mber. 199 M.
32 28 24
20 16 12
8 4
o b. Normal in Decembe r, l QQ(J.
32 28 24
20 16
12
8 4
o c. EI Nino in Decembe r. l IN? Color Plate 12 -5 RC)Ill.llds numt hly sea-surface temperature (SS T ) mJ[)S ..Icrived from in ~ i1rl buoy (\ala and remo tely sensed data lcllllltO! '- ( JI\I\ JTAt ) f\,111t' '' ;11 CC'l1ICr lOr f n\ ironmenta l Prediction I.
Trnplcal Rainfall :\Ica sure mt' nl :\Ii",..io n (T IO D I)
a. T RM M Microwav e Ima ger ITMI) data ob la incd on Ma rch
Il
Q,
1Q<1l1.
h. I" R \1 \1 Pr.. cipimnon Radar ( " I{ I data obtamcd " 1\ March 'J, I'N I'\ .
III
n
' 1il1 ~..
n d BL.)
Hlt l
:!(JO ()i~t;:'"~'l: l l;ml
c . A ltlllg-track
<' n'ls~_""I:li,)n
" f TR MM Pr<'l;,p;ta', on Radar d;I' '1"bla in..'d on M;orc h
Q.
I'NX ,
Color P la te 1 2- 6 ~ ) Worldwide TRl\1111 Microwave Im ager data collec ted Oil Murc h '!, 1'1')1'\. til Precipita tion Radar dal~ of suu lhcrn Florida cl Cross -section o f Prccipita uon Rad ar dala (courte sy NAS A Goddard T RM M 0 1licC' and Ja pa n ~ al ion a l S pace Dcvel(lJllllcnt A~\'nCY ).
------ - - - - - - - - - - - - -r Selec ted Databases rrom South Cer ull na's S pa tial Da ta In fr astru cture [).~il.,1
Or1hor':~l iti,," Im'I!~1)'
01,l'l;l1 lemun
Tr:ln'l"""annn
Colo r P la te 13 · 1 Sd<'CI,'
Ih·rkt·I (· ~ .
~raljal
1),,1;1 Infra~lnI<·lllre _
Level Il'rh:m/.....un -urbau La nd cnve r fur Dorch est er. a nd C ba rtecto n Counnes i n South C a rullna
a. Feb ruary 14 , 1975.
b. March 26. I lJNI .
d . Jarmon)" -I, I QIN .
c. \ h rrh 17. 19<12.
"If
c, February 10.
1 l)~ 5 .
Color P la te 13-2 Level 1urt>.m/null·urhan landco vcr Berkeley. Dorc heste r. and C h;u ksh lll ,uunlks cente red Oil Charlceron. SC J<.";I,x from La ruh .m MSS 7" " 7" m data Th ... landcover intorm ano n IS d raped over a ncar.mfr:Jrrd Im.1g<: (:viS" h,.nd-l).
Co
_.w.___..-,--
'". . . . .........
--..".__. _.0. _ _. . .. . ..
_ _. _.. ,-I· ....
_
. ~
,""... ...=:~ :!: - .'.__.
,-_.'__.-_.
::,-...;.._. . ~.
~--
=0,'_ , ·~. I .
::dar Ptaie 14- 1 .\tilll;ra] llldl" ofCu pruc. r--:V. derived fWl11 I,,,, -ahitud..· O 'llmU iL) and hig h-a huude (20 km AGU AVIRIS dala .."t"i n..-d on ( lc t" ber 11. IlN s. "n,1Jllll<' IX, I'WI<. r<:!op,,:.:t l, d~ 1.:' .... n .."1>)" S"a)lc,,'1"1.. 199'J j.
_......,
Shuttle S IR-C/X-SAH. Images of Kilauea volcu nu in Hawaii
I
b. Color P la te 14 -2 aj { 'ullIp<" irc Shunle SIR-CiX -SA I{ irn,,!;c of'Kilauca \"1c:Ill,,. III. (hand.• C. X. I.) nh laincd on April 12. ]
S tcrco pat r of Mount Sl. Helens, Wa\hingron
Color P late 14·3
u.s. Geological Sllm:~ Hlp tude Phot ography IIlAP) infra red seereo pair of MlJlII Helens, WA, on A Ugtlr.r 6, 1 Thc ac tive lava dome in l~ i:CIo tor o f the cone is visible. Ai&
men-c hoked
radial drall-r:
paucrn has developed. I'or6.1 to the
left (count'$)' U.S,G
ical Survcyl.
c T he G ra nd C a nyon
a. Landsat
T~ I
colo r composi te (RGB .. ha nds 7.4.2).
h ('o[o rcnmp"site ( IUi H .. bands 4 , J. 2).
Co lor P late 14 ·4 Lands,tl Thematic Mapper color composite s of a portion ur lhe Gt.uul Cally"n (courtesy NASA)
Plate 14· 5 ASTF.R image uf Namibia's Ugab River obtained on Dec ember 15,1000 (KGB · hands 7, 3. I) . Thc river passes through nearly vertical folded la>'ef1'l oflhinly bedded limestone. sandston e. and silt,tunc [cou rtesy o f N ASAl( j S ~ O~l ETIIERS IH CJJAROS and U.SJJ apan ASTER Scienc e Team ).
:\1is ~i~s iPJli
River
c.:ior Plate 14 -6 l and:s.l l Thematic \la procr co lor com posi te ( RG B = bands -l, 3_ 2 ) o f lhe' \ Iis.sil's ippi River (court esy Space Imaging. Inc.).
r ,\ Io r ro Bay, C A
a Landsat T\t ("O InTcom pocitc ( RG H '" h,lnd~ 7. 4 . 2 )
b. Colnr c.. m posuc (IH, U '" I>" n..h ..I. J, 2) .
Col
Co lo r Piate 14-7 Landsa t Thc manc \ lapper color compovues of \ l orm Hay. CA Icouncw ~p"n' Ima~IIl~. Inc. I.
S ulliv a n's Island. SC ......"
3.
:\AI'I' color-infrared unhuphorograph.
b. ATLAS mulnxpc caral U.l'.l of the lidal flat behind r- tc uf Palms , SC.
Co lo r Plate 14·8 a I Portion " I' a IJS(iS ""·\I'P color-in frared on hophoto quarter quad r.ml1!c of ...ul!i\;m·, leland . "'C (c
(
,'(;::"" i, I:I<' i..,
" " " llrt! f ;hlc i..,
L\ lala,pina Glackr. :\ L
a, Land-at 7 1- nh.a.I1I;<"ol 3 1. 20(10 I K( i ll = NnoJ~ ~. J . 31.
b. HiglH.'>bhqu.: \ I....... ,.fthe ~lac i cr c reated b) oJrJ.plll~ II LandsatTbcmanc "" ~ppcr imag e obt ai ned in Fc hruary. 1000 . (R CoB .. I>J noJ~ 3. 1. I I. OH'r II oJ ,glla l ete... anon mo Jd extracted In au S pace Shull ic KaoJar Topography , Iission (,-!>anJ mtert cl'llmelri<: S!\R d.u a ':OIlCC1.-d in Fe brua ry 2000 ,
Pla le 14 ·9 a ' Vcr nca l nca r-infra red iln'" b ) high-obliq ue natural-color \ i.' " "fth.· Mala spina Gkmcr in A l a~la , Th is is ,",Iaska 'slargcst glacier and cove..... 150U '\Q mi (3. 1\ ~() ;,q kmj. II is a com pou nd ~I ae, cr formed hy the m': Il!'" g or valle')' g laciers, the lI1U,1 prouuucut o f \\ h' ch arc the A!!.I:>si, Gla cie r and the Scward Glac ier (Cllun.,S) ~ A S:\ antJ Jet Prv puls ion Lab),
Remot e Sensi ng Glaciated Landscapes
a , L'inla Mountain Range in Utah.
b. wasatch Range in the Rocky Mountains ofUtah.
c. Lake
lahoe inthe SIO:rm Ncvudaon ofCulrfornia and t",'C\'IJa.
the border
lIs
Color Plate 14 -10 Lan do,;u ,-,,1,,1' co rnposues of glacia ted landsc apcs in ""n,on. o f a l 1h.. Uinta vtoumams in Uta h. 1> 1 the Wa.salCh Rang.. In Utah. md cl lhe Lake l ahue regron III the S ierra :-';CI J oJa. CA. l' ka>.<.' refer l
Act ivo
---
Namib Ikscrt, ....ami hia . .Urica
lh eir
s
,h.
o! sp
;" fe
Eqc
"';
""me
3. Landsat 7 Fnh allCC'J Them atic Ma!'pcr Plus (ET M +I ima~<:r>' orthe " am ib Oc...:rt obIai"",d 011 August 11.10l111 (RG II :c band.. 5. 4. 3)
n a
H u
1
1 r
,
,
b. l uw-ob li'lU<: \ lew uf a portio n o r de same area in AST f.R inl.L~cry ,ltJlaincd on Oct.>l>cr 14. 100 1. The rmage wJ~ d raped OWl J d'gllal ek\"3!ion m.'
Color Pla te 14· 11 a ) Vertical and b i low -obl iq ue views of the Namib Desert in !'oi.llllib-:-.Iaul lu fl NatioualPark, T hew arc thc 1a11cs1 _ in (he world. some > 300 m (a lmost llSO ft). The area receives an J\ cr.I~C o f (ln ly to .; m m ra Infa ll per year. The CII'Z@\' cotordeveloos o ve r time as iron in the sa nd is oxidized . The " Ide r (he d un.:, ll~ hnglnc r lhe o ra nge color (eOllrt,"!>y tJ~ and l' AS A'GSFCM ETliE RS IlA DJA ROS and LT.S JJ.lpa n :\STF R Sc jcnc.... T,~.11111.
ing
337
Princi ples
per
b':l>
\ pulse m s I)
ncnt of
.. target
ulse III
L1DAR nUll) C o llec tio n
" S lc· xY
~ hnsnm:JG
.v--"
" 1lI
(10-1)
m:Clh' r
sensor
Ka nn ina; lIlirror i
h.:lght AGL."
rrang-
I ".,. ~
" •I "
p ower fincs '• •
..
I.. sc:r beam ,J,,·...~ ...nc... 0
-
y
Ilisiantauc ous la -.er footprtm
ion of o int , I
1<:.
r<~
-
a.~
ooims
h. U DA R elev ation r nas spoint s fo r a small area.
a. U DI\R data collccnou.
.'. and
the > thc scan a ngle. 6 ; > the a mount o f ca nopy 10 be
'(lund
Ih c
roun-
p c nctrat ...d 10 H'-iICIl lh<: h a r<: Earth :
rco us
cor n-
A
c
o-»
sca u ang le
E
u u F
aen-
ver;I!..
Iy{ing
01"1 Jh),
e. Impac t ofinc reaced sca n a ng le. ~re 10-1
n II r·
.....
a) L1 DA I{ m-annn...I1l,s tra nvmit pulses orta-cr hg llll" .... ardth... gWOlHJ o~lng a ,COlnnUI!! rnirru r. Sum ... ofthis ene rgy is scan...red boll;k towardthe aircraft anoJ rc....o rdcd III the rec e iver electronics Un board G PS and l' ll l doc nmcnt th... csnct tocauo n ot rhc aircntlt and th... roll, pitch, and ya .... at the insramthe lase r pulse IS s...nt lind rc-ccivcd. h) L111·\I{-,kri\eJ l,I', and z ele vation m;lsspuint, fur an area n,'a r Aik en, SC. Some massf"Jinls arc loc ated on the L IMh'" surfa",- while oth ers are loc ated in the tree ean "py and ...ve n on the Ill'.... cr trarwmi....~ion line and IX'..... cl As~u min~ that Ihe tree canuJl)! ha-, a uniform height an d canop y density. th,-n the l;r<:;lIer the scan ang le from nadir Ute greater lite amount "r can<,py th;l! .... iIl haw to be penetrated to reach the grou nd l
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