Remote sensing of the environment.pdf

SECOND EDITION

Prentice Hall Series in Geographic Information Science

KEITH C. CLARKE, Series Editor

Remote Sensing of the Envi onment An Earth Resource Perspective

'Three Gorges Dam, China

John R. Jensen

prentice-Hail Series in Geogra phIc lofor lion Science

KEITH C. CLARKE. Series Advisor un

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Brief Content

1 Remot • nsin oj III

tram en ti Radiati

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'n ironm 111 11 Principles

of -4 'I'; II Photography and Aerial Pial arm

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ensing of oils , I iinerali ; and G somorpho

15 II/ Sit" pe tral Re 1 tanc Measurement 0111'

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. Ill" erl II I Phulo Jmphy und Aerial Plat furm ' ,., Photograph • _, ...... . . .. .. .. . .... . •....•.•. • ...•. ,.. f 19b' and ( 'olor .. .• ... . .. ......... ... . . . /11 Camer« Obscura • . . . .. . Im 'CIlIWI/ of Ls, IJf-.\ nsltivL' Emu lsio n and Metho 1\. o] Perman m (, N .\ 1tI~ tit ' lmag . . ... " " " .. II I

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hupt er : - Ele men ts of Visulll lm a ge Jnt crp rctutlo n . .•... . .. . .... . . . . . . . . . . .. .. ) 27 IntI' duction . .. • . . . . . . . . . . . . . . .. . ....• . ..• 127 The lerial/R 'Riuflal I'ersp« I 1'( •• •••• • • • • ••• •• • •• ,. . • • • • • • • • •• • 128 Three-Diniensionat Dep th I JI' J'I.'tqJ!i(}!I • . . , .. • • • . • • . . • • • • • • . . ... . ..... 12X Obtulutni; Kno: '/ d!Sf! /1:don 00" llDAR ....-rlIOno functioa and on ('Tlllllt i"n i~ pmViJlxl lllll,ul Illl: ('alladi'lll KA\)AI~SAT-l ;md -2; lhl' F un ... !"' I\hssion I SRT~n Th.....eo:tion Oil a~1i\e micro· ",1\( inlcr fcmmelry inc ludes 111."" lJuh and Tanl a llla S RTM eu101'lcs Pa.,~i\c mlcro... a\( r.:n1l' t... scnt:1...eee the S,mple Rat iol ind.::\ and II..: ~onnali/ed DilTen:no: VC'1!ctallOll Inde.. Il'tOD\'I). lbc uSC' of e I) sensed lbll for cornJ'Uung bnd'lClpt: ec•.. k.¥) lTIC'd fI~hl of lho: It1O>I imJ'tll'Unl alo:"nlttms u:w:d 10 me-........, ph)'lopla.nJ..lon al>undano:c in ""I•.,. an: 00\Il prO\l&:d " """" ......."'1100 r...'.-i.....,s ,m l'rm emrnls in Nlh)m~'1ric m al'ping u.\ing pas. )I\C IlfIIlo:all1lCTt;l1 phnl:ography) and itcme n:molc s.:nsing tSO,",,,R and Lll> Alt ) Rcmotc ..... n\ ing rnclhllds fur muniluring wale r ..urfn.:( Icmro:r.alUrc.l'rccil' ilallon, .-lc rl,o;"lo; " H '; l 1'/I1" l Id, Fi ItI tlJ f i, l\ • ' / (I I' ( etl Jl7~ ) ~" r ll l' .\IlIlti_1' > tral l (1/111" /-" lulti pect al Imaging L sing LU Il:,H Arm _. Sl' T CI/.\'OI' .1 stems ., ln it, 1I1 R ' II/ (}( C msiug . ,1:1(1!Jll. 1 idvanced po t!lO I7I L' Thermal EIIIIS.W

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m el N -flcction Rudiometcr (A. TER) . 23 \ \fulli"lIIgl ' IlIIag illg ..../ .'C'fm mdioll/ le'I" ( ,\fl. ' /{ ) , . . , • . . . • .. . . . ... • •• • . ... _3_ I C1lSOf data b ) SJX"I.'tral relkct.u,,·t" mcaw . c:m."nt, from \ e..'CUlion are ""mil colk"'cd u.sing a \ f' canopy. rhe' II! xii" "f"Xlral rcll""l3.n1/1/ data-cell ecdon process First. the sci... mist in Ihc field can be imr",il'(,. This means that unless great cure is excrcis ...d. the: scie ntist can actually cha nge ihc c h a r".:t.tr1l1e!'T~ri.a1 lan,heaplm,.il't' if t he se nso r ls passavcly rec..lrJ ll1g t~ eleclm ma l?lletic encrgy reflec ted from or e mit1,"Ii by Ihe p henom eno n of interest. Thi s is a vel)' important considcrauon, aspt'.,.,il'(' n:mote "..n"inJo! docs no t di ,l urb the obj ect or area of interest. Remot e sc nlima tion ; cUlro phicalion sludin;; IlOn· poi nt W1JK C po llulion) arid cultural Ic.g.. la ud-usc con \ersion al the uman fring e; 1ll31...r-dcmand estimaliun; po pulalion C'S lim,1IionJ I"roce!;SCS ( Walsh et a l., 1Q99; Stow t:I al .• lt.ltl3~ :"cmani ct al., 1003: Karasl.1 el a1.. 101141. A good

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example is the d igital ck\i1linn model that is so important in ""lOy lnhutcd GIS motk ls , e l,,",e. ~OOII_ [>;gIla l Ck' 3Ii"n mode ls a rc- now produced main ly /Tom stereoscofliC lI11 ager) . lighl detec tion an d I1In ging ( L1 [)A R~ (e.g .• '-h um:. 200 I: Ii udg;.o n ,'( nl., 2()(l.'h: ] 005l, rad io dCI' -c'liun a nd mngin g ( RA DAI{ ) measurement s. " I' interferometric sy nth et ic aperture radar I IFSA Rj imagery.

Remo te sensing "den,'," has limitations . PcrhaP'> the grc-alc'l limitation is that it is often ovcrsokl. Nt-"",J" ...." s;lJg 11 p" ",ln'temalic fa.J1ion that c-an he termed the Wm,,'( Jewiin" I'n>ccdu fla ti n g the problem. 1) rormmg the research hYJ'M1thcsis u.e.. a ptlssibk ex plnna1lolI ~ 3l observing and cxpcnmcming. 4) imerprcne g da ta. .and 5) dra..... ing conclusions . It is no t nec essary 10 folio w thi s I plan exact ly,

The sciennfic me-thod is normally use d in conjunct ion with ell,

ten meue t models that are ba sed on IWO primal)' types

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• Unrcctif... J - Onhoimag..':S . Ort horh')!l,nmps - Th cm mc nw.ps • ( , I ~ d.t.laoo.~" ,\ nmw.lIv ns

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• Accept " r reject hypothesis

Scu:ntlsts gen..rally usc th.. remote si:nsing process " 11,'n " ' Ir to o btain know 1edge . T hc·re is debate as to how rhe different types o f log ic used in rhe remote scnving process yiel d n...... scientific kno .... led ge ( c.g.. Fu ssell et al.. 19X6; Curran. 1987: Fisher and Limk nherg. 19 !19; Dobson , 11JlJ3: Skidmore. 2iI(1) .

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10

Id entification of In situ and Remote Sensing Data

Requiremen ts If a hypot hesis is formul ated using inductiv c and'or dedu ctivc logic. ;1 list of variables or observ ances are ide nnfled that will be used du ring the invest igat ion. In si tu ob wrv urion and'cr remote scnsinl; may be used to collect infor mat ion on the most important var iables.

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Sc ientists usi ng remote sensing tec hno logy shou ld be well tra ined in fiel d an d laboratofv data-cotlecuon proced ures. For example. if a sc ientist wa nts 10 ma p the surface te mperat ure of a lake. it is usually nece ssary to collect som e accurate em pi rica l in .rimlake-temperature measu rements at the same lime the remote sens or data a re co llected. The i,! situ ob se rvations may be used 10 1) calib rate the remote sens or da ta, and/or 2 ) perfo rm an unbiased accuracy assessment o f the tin al resu lts t Cong alton and Green. 1(98). Remote sensing tex tbook s provide some information on field and labo ratory sampli ng tec hniq ues . The in ,~ ittl sa mpli ng procedures. however. are learned bcsr through formal COUfS::m studit's). Scienti5lS who undcrsta nd thc ruk s and syne rgislic rd at io n"hips o f the Icc hno logit's can produ ce OUl pul prod ucts thai COllllllullicatc e tlectively. Those who violatc lh ndam ental rules (c,g., car-

T he National Researc h Coun ci l rt'c ogn ized Ihat thcre is lit ecunomic systt'm at play \loh.:n remote sensor data afe USC! for earth resou rcc managcmcnt ap plications (Figure 1- 16 ( Miller ct al.. 10t)l)_ It co nsists of an infom u tio n dcl i\cf) sys lem wi th thrcc co rnpont'n1s: data co lkctinn. illl3gc pro· cessing. and in l;'lnna tion co nsumer (user ). Thc data colkction system is composcd of commert'ial ven· dors and public agcncies thaI OpC'ratc ren wtc scnsi ng sy..tem s. Privale ind ustry prov idcs inti lflna lion al mllrkcl va lue. Public agenc ies gc nt'ra lly pro v ide rt'mote se nsor d3la al thc cost of fulllilling a use r request (CO FUR ). Rcmolc sensing

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29

Earth Obse r vation Ec on omic s

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Remot e Sensing Ear th Ob servation Economics

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Remote Wfl~ing Earth observation economics . The goalrs 10mimmize the /cfl(''''/f!I1Ke g"p betweentbe Intc...mal i~>n delivery system. n:mo te sen sing experts. and the in form ation consu mer (user). The remote scnsmg-dcrivcd economic. socia l, strategic, environment al. and/o r pohncal mforma tion must be cosr-effecnve. and ('8.~y to use to achieve equilibrium tadaprcd from Miller et al., 2003).

has been around since the 1960:.. There is an increasing number of experts that can usc analog and/or digita l image processing techniques til extract information from the imagery. f inally, then: is the information consumer (user) of the re mote sensing-derived information. The user generally needs information of economic . social. strategic. environmental and/or political value (Liverman ct al., 1998). In orderfor the revenues generated by the information dclivsystem to be sufficient to support the capita l and operating costs of the syste m. there musl be a balance tequslibriumj between the valu e o f the information. as perceived by the user (cons umer). and the revenue necessary to >UpflOn the system {Miller er at , 20tH, 2(03). The equilibrium has been achieved for airborne photogrammctnc a nd UD.-\ R mapping applications for several decades. Time will tell if the balance between perceived value and cost can be maintained in the spaccbomc case. Mergers arc occurring. On January 12. 2006, ORBIMAGE acquired Space lmagings assets and now functions as GcoEyc. Inc.. providing ety

IKONOS, Orbview-z and Orbvicw-S image produc ts, GeoEye plans to launch a new sensor in 2007 with a spat ial resolution of 0.4 I x 0.41 III (Geo Eyc. 2006) .. Tho: equilibrium can also be impacted by remote sensing technology experts that do not have a good understanding of the user information requ irements. In fact. some remote sensing experts.. are often baffled as to why the consu mers don't embrace the remote sensing-derived information. What they fail to consider is that the consumers generally have no motivation to switch to remote sensing-derived infonn ation on economic. social. environmental. strategjc. or political attributes simply beC3U~ it is based on new technology. Furthermore. the co nsumers on the right side of the diagram often hal e lillie know ledge of remote sensing technology or of how it is used 10 derive information. Miller et al. (2001; 2003) suggest that this situation creates a knowledge gap between the remote sensi ng experts and the information consumers (user) (Figure 1·16). Bridging the

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Re mo te Sens ing o f th e Env ironment

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Remote St'I B;II/: fll l ite EIII';rm",U'II / Chlljlh'r I. Rem e re Sl' lI ~i ll ~ !lf the Em'i"uIl 1l1l'ut • 11/ Situ Dura Collection • Rem ote Scusiug Oatf 2. Ra d iation Principll" • Conducnon, Convection. and Radiauon • Energy-Matter lmc racuo ns in III", Atrnes phc rc • En.:rgy-\1aner jnrcracuons wuh the TCITaIll [I tc l rom a~n {"l ic

C hllptt"r J. Jli slor) flf .\ t'fl ll l l' h o t ll~ r a p h)' .JIId ..\ ,' rl llll'llltll,rl11 s • His tory o f I'horograph y • Pho tography from Aerial Platforms • Photo-R econnaissanc e in \V\VI and WW II • Col d Wa r Phuto -Recon nnisvancc • Celestia l Sarcllihc Sentinels • Unmanned ..\ er ial vehicle s

C hap l('r .... Aeria l Ph"l o~rap h) • vemca t and Oblique Vantage Po ints • Aer ial Came ras • Fihration and Films • Planni ng Acnal Phutography Missitlm,

C ha lll... r 5. Ell' ml'nfs of \ 'j"ua l lll1 a!:(' IlItl' rprcl:llioll • Elements of Ima ge lntc rpretauo n • Method s of Search

Ch apter Cl.

Phni ogramlllet r ) • FIi!!htline~ of Acnat Photogra phy • lmag... Nomenclature • Scale Height \ t easurcment on Smg je PhOl o~

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Ch ap ter- 7. :\1ult h pcctra! Renuue Sl' n , l ll~ • Multis pectr al D;1Ia Collec tion • Discrct... Delector-, and Sunning .\1 i rro r~ • \l uh i'l'cclra l Imaging Usi ng Linear Arr ays • Imaging Spectroscopy • Digital Fra me Camcras • Satellite PhOI(lgr.tph ie System s

• Stereosco pic Mcasurcment • Orthophotos and Digital Elevation ~odcl s • Ar...a Measurement

C ha pte r K. Therm al Infra red Rcruute St'n,ing • History • Thcrmullnfrarcd Radiation Prope rties • At mos phe ric Windows • Th erm al Radia tion Law s • Therma l Propert ies of Terrain • Th ... rmullnfrurcd Data Co llection • T IR Enviro nmental Co nsid era tions

Cha p te r 9. Aclh (' and Pa", I,,· ~ lic ro" l1 '" • IIi"tOf) • Acnv c Mic rowave System Co mpone nts • RADA R Environ me ntal Conside rat ions • SAR Remote Sensin g fro m Space

• R.·\DA R lnrertcromctry • Passive .'.1in o"" a' c Rcmo te Sensing

Cha pt er In. I.IUAR Remote St'n ~in J:. • Princ iple s (returns, den suy, iutcusity } • Proc essin g to Create DEM. DS M. DTM ' Accuracy o f LI OA R-d\.'r ivcu pWdUt.' IS

C ha pt er II. Hl'IlI"le Sensl n!: uf \"~('l lIl l o n • Photosynlhl');b Funda me nta ls • Spectral Cbaracrenstics o f vegetanon • Tem po ral C haracteri stics of'Vegctauo n • \ '~elat l o n Indices • Landscape Ecology' Metrics • Hiodiversiry and G A P Ana lysis

• Vegetation Change Detection

,, Figure 1-17

B".. ~ organin llllll,

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Earth Resou rce An al ysis Pers pec ti ve

31

O rgan ization of Remme Sensmg of th e Environment - continued

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R e mo te S('n ,i n ~ of " a ter • Surface Warcr Uiuph)'si,,;al Characteristics • Precipitation

Re mme Se nsing Solils•.'I in e ral s, and (;co nlo r p hulo !:) • Soil Charucrerisncs allli Taxonomy • Remote Sensing Soil Propenies • Remote Sensing RClC b and Minerals • Geology and (iet, m"'1"htlltlgy

• Aerosols and nuu Js

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• Walc:: r-qu;)lity \ loJc1inl!

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C 1H1llh 'r D . R emote S... nsin l: the I 'r -h a n Landscape • Urban-Suburban Resolut ion Considcrunons • Remote Sensing l .nnd Usc -Land Cover • R...sidcunal • Commercial and Services • l ndusmaland Transportation • Communications and Utilities

C ha p ter 15. 1,1 Sil/l Slll'l'tra l I{l'fll'l'tall fl' .\ It'llsu rl'ml'nt • Spectral Reflectance of a Material • llluminanon Considerat ions • Radiometer Con vidcruricn s

• Urban Mo1'l etJrolog ical Data • Critical Envi ronmental Area Assessment • Di~1S1.....rver. light inten' tl}. e~e adapuunm. and oth er factors . ' The wal'e number \ 1jI) is the number uf '" uves ill Hunit kllglh (u-ually p...r ern). There fore. 'r • 1 I ;l.lcmj ~ w .ono I ;l. (jJm )

I OO.OOO. OllO/ A(A ) in cm · l .

netic spectrum i~ commonly referred 10 as a bund, chw lJI"!. or region. The majo r subdivisions of visible light are ..urn rnnrized in Table 2-2 and presented diagra mmat ically in Figure 2-7 a nd COIM Plate 2-1. We ge nera lly th ink of visi ble lig ht as be ing compo sed ofenergy in the blue (0.4 - 0.:" um I. green {O.5 - O. t. u rn], and red (O.t. ~ 0.7 urm hands ofshe electro magnetic spectru m. Reflec ted ncar-infra red energy In the regio n from n.j to I .] urn is common ly used to expose b lack -and -white and color-infrarcd -sens u.ve 111m.

Tho: m idd le-i n fra red reg ion [o ften referred (0 as the short ....avelc ngth in frared, S \VIRI inclu des energ) wit h a wavelen gth of 1.3 to J um. The thermal in frare d reg ion has two ve ry use ful bands at 3 10 5 um and ~ ro 14 u rn. Thc, m ic'ro....ave por uon o f the spectrum co nsists of muc h longer \"01\ elengths ( I rom - I m}, The rad io-...ave pornun o f t he

spectrum may be subdivided into UHF. VI IF. radu ( !-I F). LF, and 1I1.1. freq uencies. The spectral resol ut ion of most remote .....nsing system-, is described in terms o f ban ds of'the electromagnetic spectrum, For cxamp le. the spectral d imc nston s of the four bands of the Landsat Muhispcc tral Scanner ( MSS) and SPOT High Resolution Visible (I IRV ) sen sors arc shown in F igu re 2-8. alon g with the ~ra tial rcsolu uon o f each ha nd for compari. so n. The exert Landsat MSS and S POT hand speciflcancns are provided in Cha pter 7 Electre mugn etic energy may he de scribed not only in te rms ofw avelength and freq uency bULalso in pho ton ene rgy units suc h a s jo ules ( J) and electro n volts (e V). as sho wn in Fig ure 2- 7. Se veral of the more important mass, en11.7 u nn. Our eyes are only M:ll~ i l i ,,: to light fnuu 0.4 1x'> J. Fortunately. II is possible to make remote sensor del ~'Clol'S sensitive 10 ellergy in lh...s... nunvisihl... r... gil'l)'; o f the spct:lmm .

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Refraction in IhTlX" nonmrbulcr u 'lIOl" ,phcric layers. Th e irKldc nt energy is rem Fnuu iL, normaltra jl'Ch l ry liS it travels [rum on e atmospheric layer 1(\ another. Snell's law call be u,."11 10 predict how mud! t>,.-ndin g willtnk c place. hascd on a knowleUI!-":" I the anl,:lc uf mcrdcncc Oil and the mdex or rcfr,1\:till 1' c11 ·(l laJ .)UI;'> WOll O;l UI fi UlSll

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II I ( 'H lIIS) ,' ,Wi d ;'J , CI

m, 11 Imp uo ~pr.JpJJ o 1U1lOLU I! ,1lj l p~ p;'JJ d 01 :'I!'l!s snd S! 11 ,I II

Sl ID :'M.l UlllPl:JP~1

J~nl:'):ll.l

\ 11SU,'P jll;ll :l.lP P .lll 1.) IIIOIIIl III Ulll!P;llU

:>1I(l UIOJ./ s ;ls scd II 11:>1.1 " Illil l].I " ih ll plPq ;1111 lU nl {lI"" ;lIII .10 ;I:>u:>I' I:'lUI .I" -"1;1\11l ,' Ill Plll~ :'" 1'1II~ III lUlllP;llU.1" U(}II :>I:JJ "'J .\o xapu ~ ,11p SMIIII 'I ",UI)J I ' .' JI ~ j :'IJ " tll UO/JOflJ/al:J ~ II

(1: 1-(: )

' n 111S

IA urs I"

'P"'\ \l WJ J oX!

lI:lP ,' ", P°'\J uuo s nljl p uc !tlul S, 1F'uS All al 'i C l,' ~ p,'J U an:

5JOJJ;I Ull~ IC:I0 1 ,;1,,;1111 'J.1\:J\\OI I 'S:JI"1I1' :Jln:>l!

w J, )

S:lpn ll1lr

qllnj 111 p ap;!1;1p A.'ur lsIP ,' lll '( 0 ) I C" ~ l-P \ :'141 t ill"

;lprm :>lilur. ;'O ljl JO UOlpttnJ C S! U.\ .I" lItll' l\ IJ I: ....n l'l' -ord sllll. -uedr 1\,' I';: :>11' 111.':'>','1' ,'Iplll '''lUl,l 0,"1

1'1:1 ""41 U;lF' .I" '1 1'1.\ pw" -11"'IIIl'--I;I \.', \'1 f"" !;;J,,Il·, ;"l1l!Jo\l I,'tJVUluel JoJ,," UI111p' ''' r III s:>P!lJr..J "tll~'l" III ln q.Jn lll tl U I! Jell l ,1:>S ur:'l ;I ¥I fl' t ,1m"!:! lUI'W·1

pcods ,;1 41 4 :'lc.'J J.:I.\."IU u ca ."I.1ucI' 'ln~ e U! ltrfl !l.lll p;l,'ds .11U

saldpu!Jd uO! le!pel::t :m a u fi e w OJ l 3 a l3

.'

=

z

1

11Il'I" Uln l!,,~

1

""0

~'I l

"I

' '1.· I'''.... or " I V'"q 'II"J \tllll."',", J"'l'n~

ul: OJ'I." \:> 1 ;:

.. "''I ,f,J:>tI;> ',"""'1\'

I,V) 'JIll' lim p ;>!" u~

;>;1U"'I) ,,,Pl."!

d mp. l .mdp..\ 1II11 !lltIS P. II! ,""ppJr..-I,)! lUlIl\ lUUJ j Il jilr I JII UII,I II,lJ

" I lJh~ 1

,

/J

~ ,-u.1\

4

g,

H.)

-,

50

0 1,\ )' 11:.1(

2

I n h 'n,il, of Ra, leigh Scatt eri ng Var ies I n\'ero~l'l , " it h I.~

Atm osph eric Scatter ing R:I,J('ilo:h Sca ll er in!:. 10 rime, the \00 avelengt h of the incident electrom ag netic radiat ion (Figure 2-150:). T his type of scattering is nonselec tive, i.e.. al l wave. length.. of lig ht are scaucrcd. nor just blue. g reen. or red. Thu ... the wate r d roplets and icc crysta ls tha t make up clouds and fog ban ks scatter al l wavelengt hs of visible lig ht equally well. causing the cloud 10 appe ar white. Nons ele ctiv e scattcring u f approxima tely eq ual pro po rtions uf blu e, green

"

51

Atmospheric Energy - Mane r Interact io ns

.lrld red light alwa ys appea rs J ~ while light to the cas ua l obsm-er. This is tho: reason why pUlling our nutornobilc high beams on in fi.)g only makes the problem \.I 0 1';

II.

10

wavelengthurn

2UQU

Su la r rad l~ I".m a t the

lOp of the .nmo-pherc

'sa,

Sola r radrauon at

"C3 1C\~1

C' E ISOO ~

,.~ o:•

O~· llfl

10110

II! ) II !) I[ .,()

11,:0 Hf)·CO~

lip . CO,

c Fig ure 2-17

0.2

0.4

06

OR

10

1.2 1.4 1.6 U waveleng th. um

2.0

22

2.4

2.6

2.11

3.0

32

01) -I he ab"'ll'plinn "f lhe Sun'~ incident clcctrceuagncnc CI\cllllt III the atmosphere 31o ne II IllO:, The atmos phere c ssenuatly "dUM'~ "lllering, and reflec tance reduc e Ilw amount or solar irrudi.mcc reachi ng the Earth's surfuc c at sea level.

,

53

Terrain Energy-Maner Interacti on s

, Angle or

AIlgk"r

Angle of

l-._\ ilan«

hlllo

"'..........

dimL"tlsionlcs.s

'"'.

the terra in, it is possible \0 learn impo rta nt info rmation a !'lllul the terrain.

Radiometric quanutics haw been identified that a1l11\\ analysts tn keep a careful record o fthe incident and e xiring radio uut n ux (Table 2-4). We beg in with the simple radiation budge/ ('(/IW /iflll, w hich stmcs tha t the total nrnoum of rad io ant n ux in speci fic wave lengths 0, ) inc ident 10 thc te rrain ( lIl; ) must be accounted for by e valua ting the amoun t of tad i:lnt flux renee-ted fro m the surface (¢I,:1 •

P x. .. re flectance from a neigh borin g area

L• .. tota l radia nce aith... sens or ( W m : Sf I)

L T .. 101.ao.: h u~tts l Figure 3-9). The photograph s were obtained using wet collodion pla tes (Ten nant, 19{)3). Blac k was a pro fcs..iona l photog rapher from the linn of Black & Batbcldcr. King had his ow n photog rap hy bu siness - King & A llen. At the co nc lusio n ofrhc days ' ae rial plnuogruphy, King {I S60 j commented. Th is is onl y the precursor, no doubt, of nume rou s other

expcnmcms : lo r no one ca n 1001.. upon thesc pic tures. ob tained hy aid {If the ba lloo n. with out bein g convmced th at the lime has come \lo he n \~ hal has been use-d .,nly for publi c amusement ca n be made to SC'f\ e some practical end. In Ju ly. IXfl3. Sir Oliver wcndcuHolmcs (a pho tograp hic student of Samuel King) photoin terpretcd the conren« of this phott\l;raph for Til...AI/untie .\Iml1h1~' (f\C \lo hal l. 19(9); Boston . a" thL' L'al;lc and the w ild go.\s ... see it. is a ~ "'I) .li lk r...nl uhj eel ["rom th.....amc place as the solid ci ti/cn loob up .11 its caves and chimneys. The O ld South nnd

... C1IAl'rER

68

3~

History of Ae rial P hot ogra phy and Aerial Platforms

Fi r~ 1 ,\ r rilll I' hulflgra ph from .\ C a ll1iH' 1i;III"ull ill lhl' United Slah',,; Uu'l oll. :\IA

Figure 3·9

A I" ,nilography o f World Waf I trenches in Europe. EuminllllOll of ~tcreoecopic photogra phy re vealed tho: IlX.ltiofl of men. gUll cmpl~... rncn ts, and am munition bunkers. Millio ns or men d ied in lrclk:h .... artarc durinll World War I (used with permission of the Smlth""ni,m tn-murion. washington. DC; Iil H·-1 1711).

facilil ) at Pccncmcodc in World War II. ]\'otl" the large circular earth revet ment around 11'00: launch fa cilit res J~.... igncd 10deflec t the t-iasl du ring lifto ff or 10 min imilO: the d~"l mcti"ll during an acciden t. Th~ ffj I IHI on September :! ~. 1%7 l ,-"U "'~~ L SGSI. :I) ( '''WIl ;l

Image!) acquired by the ~r;II.:e:· ha.~t:d nationa l imc l!igenre rccunuuissancc sys k l11s known .Is the Co rona. Argon. and Lanyard Mis sions shall. \I ithin I S months o r lhe ti'llt: llf l hl ~ order he \ kl.' l a ~ s i lied.

,,had

caplure.

h,'Culj\C Order xumbcr 12951. issued by Pres ide nt WillWIl I'hnton on February 22. 19'-15, changed 111,' world l}f phoc'''~h:llih: reconnaissance. T he or der direc ted:

ny >II,

1':

[)~1"

Ihc We b sire for hrowsin g and ohli1 ini ng d uplil.,;tlCS o r l owna film is fo und in Appcrxhx A. An t.'\Ct.'Jt t"11I overview Or~1r Corona prog ram and the porcminl utilit), of the d ata f,x Earth re~OUTCC analY!i i!i is found in Cl arke ( II.)'-It,l ).

Ongoing Satellite Sentinels

npilaUTVCy

-sca le

nc suc rho wn

&

Ic~

and Kearney '\ rotc in D,:!,'",., ,\'.....1' ( 1991 ): Figure 3·28

Saetlue data and airborne rolJa~ hav e replaced lhe: cavall) scout and the foot patrol a.s the commander's ...) I:S. . .. 1\l lhoul:!h the fog of war was no t chmmarcd. General 5o:hllartL,or fs view ufthe banleficfd ex cee ded anyt hing

A ".tT 200 lorn a nd can stay a loft for many hours . So me UAVs can stay alo ft virtually undetectable due to their size for hou rs o n e nd, constant ly monit ori ng the same geogra phic area.

m ately liam S. ~ Intel -

~

3·30

Panchrom auc (,1 x (,I em image of RosIOll. MA. collected by QllkU~lrd on December 27. 200 1. Circular high -ri st"'i ("I' Cti lllll UIl' [OfI Inner Hamor. The: Wharf a t Ro we can be seen In the Io1A er-rigbr hand

corncr tcouncsy DigilalGlot>.:. lnc.),

Uln:' sed 10

firsl Earth-resource oriented (T~'n'u ) l>atcllitc in 1999 and the second (..11/11/1 ) in ~ 002 . Com merc ia! firms launc hed IKO~ OS 2 in 1l/W . Ima geSal in 14aid and Oliver. 1997; Lock heed ~lani n , 1 0()0 ). Store expensive UAVs arc cont rolled from a ho me base by an ana lyst who jnows exal't ly "here rh... UAV is located at a ll limes throu gh

Desert Hawk W:lS develo ped hy the Loc kheed Martin Skunk works. It is made ofmold-injected po lyp ropy lene foa m and is powered byan elect ric mete r driving a pushe r pro pel ler. It is laun ched hy two pe rson s. w ho attach a bungee cord to it. extend the cord to about 100 III and then simply let the UAV go . Desert Hawk 's operationa l a ltitude is 500 ft. ( 150 m j. It ca n cru ise tor nbout one hou r al a speed o f up to 57 mp h (n kill/h ), and its operationa l radi us is about 6 na utica l miles ( I I km), Desert Hnwk land s on its Kcvlar belly. Its payload consist ing l l f color ca meras fo r day or FUR fo r night -tim e survcillan cc. D es ert Hawk was used in Operation Iraq i Freedo m ( Loc kheed Martin. 2()()6 ).

8.

History 01Aerial Photography an d Aerial Platform s

Predator Cnmanncd Aerial vchlctc (UA\ ") Illla~l'r~ lIf \ ·u~lI ..ca :\ mmun u ion Plaut

,J

1

I

,

a. Figu re 3·3 1

I'r4f1,OOO 0 . .1.

7.4

3. M

::! 15

15.000

n.a.

"

1::!.75

•

~--~

C11 \ rn:R

88

3~

History of Aerial Photography and Aerial Platfonn s

Digital Ae r ia l Ph otogr a phy Obt ained Using An In expen sive Un ma n ned Acr ial ve hicle

Figure 3-32 i\ large-scale aerial photograph of a portion of S"ll lh !'aOM: tv. c types o f c:mul"luns ,II 1.'.\;\ WIl"'. The v ider me angula r field Ill' 11('\0.. the greater the arnountof Earth recorded lin the li lm a t a gi\ C'n alutudc above grou nd level. The high o:r the altuudc. dle greater the am ou nt of Earth recorded on the film by eac h lens. These relationships arc summanz cd in Figure ...· 10. ," It If//t'n',llon/('rer is u ~e;'d to e;'XpllSl' thl' ph" hlgrap hic lil m a t 'i'CCilic intcl"\a ls of tim c Idc pend c nt upo n the ain;rali. al tiIud", aNn c grn und Ic \ ",I and sf'l'Cd) th:lI \\ III resu lt in thc

w ide in m ils 2: 100 10 51)0

n in

le ng th, de pending upo n the

thick ness ofthe film . Ind ividual ~ \ P,hurC~ arc typ ically v x :I,ed S(lk ly o n td uo: light rdkcted fwm tn,' tC'rrJ in. alwtner Ila ~e d o n onl y green light re l1 l'1.· t ~-d from Ihe terra in. ,lIId a li nJI image I'RlJuccd on ly fRlm rcflc ctcd " ..d light , Th e th ree ind iv iJ ua l blad:·and·.... nitc ima ges arc recorded in thl' ea me ra 's randum aCl'es" ffiCll1lll) (R .-\M ) and ca n t>e w lllr-..:umlJOSi k-d us ing add ili\'e wlor theo ry to prod uce a n'lluml .[oo ki ng color pholograph. It is a lso poss iblL' t,) mak e the detl'C,,' l\lrs !'.ensl tive tu near- infra red light. T his ine xp"' llsive VAV sho wn in Figure 4 - 15h con ta ins an inl,'rva l111l1clt.'r to nllla in phot ographs at speci lie inle rval s to obtai n the nccessary end-lap. 'n ,e ima ge s Jrc rdpidly stored on a dJ tJ reellfdcr, The o f'l'ral nr \lII Ihe gro und knows wher e Iht.' plano:" based \ln the use Ill' lin on board G I'S ant enna Inot :;ho" 11). Till"o rbs I>luc light and allows he transmiu.-d (lahll' 4- .'1. ()ur eyes ;me1\'C a mi.,!urc of red and green li~hl a~ yell'I\\ (i.e .. lhe lJfbluej. Due 10 Ray leigh s..:Jtll'rin!! lChaptl'r 2). hlue i. >o,:alll'fed in Ihe atmosphere I" a mut'h gre.ller degrrt either !:!rt'Cn or red Iighl and can thl'rl'fur..: C.lUSl' at'ri al ogr.tl'hy 10 n..'l:ord cons iderabl~ un\\ anted. sca llered light. Thl·rel' lre . il is Cllffirnon Itl usc a yel low lilla to lI:ltcti\ d y remo\e !>()In..: of the seatter..:J rat h radiance

vren and ml fighl \(l

(l'spccially ullr:l\ iotcr and some blue hgh ll before it ever n..aches the emulsion. Thi~ mmus-htne jifl..-r \\ ill be , ho\\ n to be parucularlj important when collecting nca r-in frared aerial rhnlography. 1\ 1""t aerial phu1o.lgmrhy is ac qu ired using at least one sta ndard filter, The spectral-rransmutance charactencncs of selected K, .....;tk wraucn lilters ..»cr the wa velengt h interval 200\tII.lOllllllllO.2 1.1 unu arc shown m Figu rc -t- j t . In mkhnon. a tran-uunauce curve for Ko..lak filters HFJ and wrauc n 12 are show n in Figures 4-11a and 4 -1 ~b. rcspc cl ive ly [ Kn..lak. I9')l) I. The se filters nrc important 10 aerial phlltlll!ra phy. Wh en l'ul ke ting natura ! color aer ial ph" tog: r;;ph y, il is de sirable to elim inate mu ch of the scancrmg o f ultraviolet rad ialion ca used by at mosp her ic huzc. For this PUlp l"': and lU "hWi n a mor e salisl;lChH) ' co lor bala nce. haze fi lters ( Ill') I\,"l'~' dev eloped thai absorb light shorter tha n 400 nm. Si milar!), 1\ hen collecting color-in frared ae ria l r lit>lo gr:tphy. 1I yellow filte r is used. which suhtmctv a lmost all or lhe blue light (wJ\elengths short er than 500 nm ). Th is minus-blue tilrcr reduces the effec ts of at mospheric sca ucring and a ll,,\\, rhc proper l'n..:rgy 10 intcrllct with eac h o fthe film's layers, tu be discussed shortly . If do:~iTl'd. it is possible 10 configure a camera ti lm filt er rombinanon so that it screelively records a \ 1.'1') specific oolld of rct lccred elcctromagnetic l'llerg~ on the film . This is called spectral band-pass (illl·ring. For example, if one wanted tn photograph on ly reflec t•..J green light for a "pccitk aerial ph~lt\lgraphy project. :1 Khul'.n in Figu re 4-2J . When a quanta o f lighl hils :1 non me tall ic surface, tilt' vihra tion in on ly one dlre~'II(ln, or plane. is rdlected com p letely. Co n\..:rse ly. all vilmll ions ;Ire rctlc cled by a bare meta llic sur13Cl·. :\011. dl'pc nd ing upon the angle at which lhe ca mera or ..'ur e~c~ a r~ \'i~win~ the IIhjet·t. \ ibratilln, in olhe r rlmll"S af~' reduet'd or eliminaled ~·nmpldcly. T hi!> renee k'J lighl \ il>ra ting III only onl' plane - is called f'"f(JrI:"d light. The lighl fw rn a h lu.: ~k)' i, polarih-J b...'eaus~' it is rdleeteJ fw m nonmetallic p(lnie1c~ in th..: al lllOSph..:re. Li kewi~. ligh l re tl''l.1 cd fnlm .:I \\ heat 1l.:ld or a hody of water into Ihe field ...1' view ...1' a eamer.. is polilri/ed ~ince \\ heal and \I al 10%

75

J2

Ill] Figure 4 -2 1 Tran smis sio n characte ristic s o f ...:k"':k...J wr.mcn nncrs ( COUI1 ,:~y Eastman Kod ak Co.).

m

4erial Photograph y Film s

109

,

0.1-

-t-

1- ,

"

li n Fil lt'r

"

.~ ~

:'i

"

.

.

·

,

,.

: - "j

·.

'00

,

j

J

· .

.

.

] ]

.. -

.

---

b.

.

· .

·.

-+7(1(1

f>{X1

I~

1

sou ~t

·

,

::'UCl

.

-

. . --

,,

1011

·

son

-! -

.

I

, ,.

Wavelengt h (nlll)

.

,

. .

,I

a. 11.1

II .

. .

,

.. , ·, :;

j

l-t-

.

.... . .

-1

·

11M)

]

,..,.., . ,.

-f

.

~

' 00

' 00

-

..

i-'t-

i600

t

700

~

SIlO

" .l\ l.'lC'nl.",h In mJ

]

~

4-22

o lIr- '11 frat~.,j pfl\>llll?taphy (cour1~"'y Eastman K.'I1T1 lnl/. layc' l Ked l al...l I>hlle 1O use a red "safe light" in a photographic darkroom. The prinuug paper is sim ply not se nsit ive 10 red light- Con versely. black-a nd-white panchromatic film reco rds ultraviulct, blue. green. and red re flected light Therefore, a haze filter [suc h a" the Kodak IIF J prev iously d isc ussed ) is often used 10 ke.:p ultraviolet and blue light from e\posing the fi lm. Panc hromatic film is the mosl Yo iJd) used black-and.... hnc ac nalfilm. as il prod uce s graytones that are expected and recog nized b) huma n beings. i.e .. wa te r is dark. sand Is .... hue . concrete is gray. clouds urc \\ hue . vt uch o f the ae rial

Aer ial Photog raphy -

112

Electro n '-l icroscopc Photograph of Silver Halide C rystals

Two Films with Different Sizes and Densities of Silver Helide C rvsrals

1

Vantage Poin t. Came ras, Filters, and Film

F ilm A

I un it distance

• Film R

QQQQQQQ I'" FlQure 4-26

"' 1

I unit d istance a.

I ) Films A and R rq>reslXlrdl sc:nsili\'il)' ofblack-and-wtrire li lm and paper emulsions o ver the wavcl":lll,:th interval 0.35 - 0.9 u r nl,,:oollcsy Eastman Kodak Co.).

pherography acquired for photogrammetric purpose s 10

make planimetric and topographic maps is panchromat ic aerial photography. Typical panchrom atic aerial photogra-

phy films marketed hy Eastman Kodak Company arc summa rizc d in Table 4-1 .

and Rim

113

AHla l Photography Film s

Table 4-4

I:as tman !\(.tlal. aerial photography Iilms [courtesy Eastman !\(Idor acnal m'f'I',ns and =onna;ed", m-ah,h>dc marrina and

+1H,gh...-p."C'd enlor

I hlP IIIIl.flfMI From nncromercrs to Dr l' 0 1'1 (2.5-1 ~mJlO.OOO From inches to meters: \ 1 I x 0.11 254 h um meters ro inches: I ' I x 3'1.37

\1

meters

Computation of Pixel Ground Reso lutio n: PM "" pix e l ~Ile In meters ; [IF = pixel sii'e in fCi."I; S c pooh. scale Using DP I: 1'\1 (Smr l)/39.)7 1'1 .. (SiI>PI)/ 12 Usini:! micrometers: I'\-f = i s x ~m)ll.OIKK)O I Pf = (S x um) 0.(I0000328 For ...sample. if a I :6.000 scale ae rial photo graph is scan ned at SIlO DP!. the pixel Sill' will be (60110 500 ) 39.37 · 0.30-1)0( meter> per pixel or (t>lIOtJ SOO )' 12 - LOll fOOl per pixel. If a 1:'I.t>OO scale aerial photograph is scann ed at 50.1! um. the pixel ~I /~ will be (9.600 x SO.8)( 0 .000001) - OA'Ime!ers or (9.60lJ x SO.1l l\0 .OOOIl(132lt j " l .to feet per pixel.

sca nners arc: designed tor :-1.:5 x I ~ in. originals. and most aerial photog raphs arc 9 x in. focal.lenglh lens. Dgr.I ph of the Earth obt.1incd b). the aSIrao nautv unb..ard ApuU.. /7. soootl ng through a pMoole: of' tbc spaccerafi. Almolit lhe '''I'Ilil\' colll inrnl d A frica rs visih1e as well as Saudi Arabia and pan Iraq ;Jnd Ind la _ Note the arid Sahara an d the dart. ,egelatct! terrain of the rain f\lrCl'1 alon g Ih", eqU3llf in central A frica. Ama rcnca is especially appa reraa rh... Soulh PIlI... Photograp hs like nus helped I\l3fl ind hi realize how vulnerable and precious iii: Ea r1h is as it rests hke a multicolored jewel in !he blacknes s of srccc (coo" ",sy \'1:.

and "'"3ICr In fl"nth.

d. lliack-and-...hite photograph of near-mtrared rCll('c!l;'(Il'nC''Er:Jph of ~Tl'"n from Hu...Ja mangroves.

c. Blad-and-.... hite photr~ral'h of red reflected encr~) ,

rcfk"I~'\I "nc~)'

e. Stand of pine «'Ierg rccn ) surrounded hy

hardwoods

(h or orthcumagc wh cre all objc...-ts urc in the ir pro pe r planimetric x,y location . It is the n pos sib le 10 measure the Irngth. perimeter. and area of features usi ng several met hco!,. incl uding pola r planunctcr, lat-lel d lg ilil.3li" n, dot-grid analysi~, or dig ita l image ~ ..:m al ic.lriallj!:uIM pattern of B· 52s !It'mll d''ilTl.anl lcd Icoll r1 recorded in kire

photoil12phy

.wurtc~~ ' Cn~

11.:"1,,,'11 ,

d, Pyramitls of Gi"a I C\'lIr1cs~'

"e So" in-

f"'Wlllnik and Acr iallmJl!cs. IIK I

b. Shadows ca' II huun. WIthout rt:"fudin~; Ran b.... , 9.150 km (5,000 nautica l mi)1 ( R,)Cing. 2005 I.

phn es of co lleagues that etten colla borate when ancally sluJy ing a certa in topic.

s~ stem-

While single-date remote sens ing invcstigauons ca n y ield impo rtant "information, they do not alway s provide inform»-

11011 abo ut the proce sses iog«>g' J.phy. wi l SCk:ncC

\ \ 'e: now havc an unde rstandi ng o ft he funda menta l eleme nts o f image interpretation . w e can untize the elements o f image intcrprctauon III care fully analyze aerial photography or other tyJ!"s (If optica l (b lue , green , red . and nca r-infra red ....a\'dcnglhl re mote sensor da ta . Based on this foundat ion , we ar... pr... pa red to pro~n..'1>s to mo re so phist ica ted ima ge ana lys is techniques . incl udin g the extracrion of quanutauve informauon from rem ote sensor d ata us ing pri nl· i plC.'~ of photogramrn... try,

References

( ieodc",,,, ,' S ' ·IIWI}t . It. N. Cul....:II, (E d·l. ucthl.'sl!J : AS I'& RS. 1:103" I r~ () .

residential urban developmen t. ha ve bee n fo und 10 liIldergo pred ictable c ycles tha t ca ll be monitored us ing remote sensor data. A tra ined ima ge anal yst unde rstands the phmolog ical cycle o f the pheno men a he Of s he is interpret lIIg and uses thi .. info rmation til acquire the optimum ty pe o f all

Sem i ng ,m d ( il'/>"'l .~ I 1< dy,\· " , NY.: Tuylor & Fr ancis . 2h X p.

u uc ll. S. J.• 100:... Rcl.·c1Il AJ , a llcc~ in Remote: Sen si ng o f Biophysic al Variables: .vn OH·n il.·... of the Spc cial Iss ue," Re-

"''''t' .'i,'" l. h i~ possible to combme seve ral vert ical photogra phs III the block orphotog raphy tu create an unccmtroltcd photomosaic

n :igurc (>-_'11 1. This exa mple depicts on ly six 1:6.000-!>Ca k photographs. Acquirin g photography of a county, state or country somenrnes requires thousands of photograp hs. depending upon the sill.' of the country a nd the scale of the phllll'graphy .Tahlc 6- 1 provi des several metric and English

ClI\I' I t :H.

152

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Ph otog ram metry

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sured fro m a re ference map . The analy st then mea sures th,,' correspo nding dis ta nce on the photograph (ubI and so lves for .f . F{lr example. consider the ve rtical ae ria l phcrog raph of downtown Colum bia. SC previously show n 10 Figu re (>~ . The titling info nnanon sa) s the origina l pholognlph was obtained lit II nominal scale { II' 1 in. "'- 5UO 11 ( I;/l.OOO). BUI is

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IOCM MIO S co nsidered to be infinitely small, Equatio n 6- i reduc es to an express ion for pho to scale at a specific poin t. Dm ppin g suhscriph, the sca le at a ny po int " host' elevation abov e sea le vel is h and whoso: camera altitu de above sea level is JI, may he exp ressed :I S: (6 -~ )

11

lnou r e xample in Figure 6-9 . different scal e va lues would be compuu..d ", loc ations c and d in the ae ria l photogra ph. One scale value wou ld be a func tio n o f the m inimum elevation ubuvc sea le\ cl within the pho to graph 1, _1 while the oth er would he a function o f the maxi m um elevation abo ve sea level within the photog raph ( ~' .... ):

C..rom..· u) of a vc-n'cal acna l pbotogr...ph .....tamed 0\

er terrain with variable relief.

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alilding protrudes above the average elevati on of I.' loca l erain.jhen the sca le in thai area oft he phot og raph wiltbe ~cr beca use the la nd wi ll ha ve " nlUH:U c loser" to the

erial camera. The geome try o f a single vert ical ec riu1 photograph taken 0\1."1' terrain with variable local relief from exposure station Lis ,hn", " in Figure 6-9 . Po ints A uildlng. 1; is mC3sired as 2.23 in.. and I1mlding relie f dis placem ent, ,I. is 6,1 2Q in, The ph"l ll~ ra l11 m "'lr i c ally CUlTI pUll'J height. h. o f th~ condominium is:

0. 129" x 297X.5' 2.n"

I72. Y.

T he actual heigh t of the building measured \\ uh a ..urve)'or'"

tape is I n,75 n. iii obt ain accurate obj ect hdghl mea surerucnts using this tec hnique. it is imperativ e that the alt itude ( I f th e aircraft abo ve the local dat um no: as precise as possihlc . I\ ll'll_ great care !'oh\IUIJ be e xe rc ised \\ hen measuring r and d on the photogra ph. Keep in mind that r is measured Imm the principa l point to the lop o ft he obj ec t.

CI I ,·\ l'T EI{

162

f1 {'i~ht ,' l ('3 ~ u r(' nlt' n l

or

Hawd o n Shudow Lt'n elh

The height of an object. h. may be computed by measuring the: length o f the shadow cas t. L, nil vertical aerial phoro graphy. Becau se the rays of the Sun are essentially parallel throughout the area show n on vertical ae rial photograph s. the length o f an object's shado w on II hori zontal sur face is proportionalrn its height. Figure 6- 11 illustra tes the trigonometric relationshi p involved in determining object heights from shadow measu rements. No tice that the tangent ofangle jl wou ld be equal to the o pposite side. II. ove r the adj uccnt side. whic h is the shadow leng th, L. i.e..

Ian II

Solving

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6

Photogrammelry

or

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for height yie lds :

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The Sun's elevation angle. ( I. above the lo c al horizon ca n he predic ted using a solar ep hemeris table . This requires a know ledge of the geographic coord male:" of the site [longitude and latitude ), the acquisition dat e, lind time o f day. Alternatively; the sola r alti tude may be c-mpirically cumputcd if sharply defined shadows o f known hei ghl arc formed on the phot ograph. fo r exa mple, we kno w from previou s discussion that the height o f the Senate Condominium in Figure 6-12 is 172.75 It. II cas ts a sha dow onto 1C\'d grou nd tha t is 0,24 1" in length 0 11 the photog raph. The scale of'the photography is 1:5,Q57 or I" ~ -$l)6.4(j·. Therefore. the sha dow length on the ptllliograph is 119 .65 tt. The tangent of angle a can be found using Equation 6- 15: lan a ... ~ .. 172 .75 ' '"' 1.44 . L 119.65' Oth er shadow lengths on the same aerial pho tograph ca n be meas ured and the ir le ngths mu ltiplied b)' 1.44 to determine thei r heights. For example, the to wer on the nearby pa rk ing structure in Figure (l-12 casts a shadow tha t is 0.119", or 59.\' lo ng onto lev el ground in the photograp h. Therefore , the he ight of the tower is:

II = LX la n" - 59. I' x

The: height of ubJccts can be measured from \'ntd aeri al photography based on the length of ShatlO\l.l

1 .4~

o n uulcve! terrain, shade.... s prod uced from lea ning objecii shadows not cast from the true top ofthe object. and SOO\\ II ot her types of grcundcover obsc uring the true g roun d level. ~

Stereosc opi c Measu rem ent of Obj ect Height or Terrain Elevation

A single ae rial phot og rap h c aptu res a prec ise recor d o f the positions (If objects in the scene at the instan t of exposure. If \.\e acquire multiple photographs along 11 tl ighthne. we record im ages of the lands ca pe from different vantage po ints. For example, the top of a ta ll bu ilding mig ht be on Ihe letl side o f pho ro e I and in the middle of overlapping photo ='2 because the aircraft has mov ed hundreds o f ml"tCT> between expos ures . If we ope ned up the ba ck of the aerial ca mer a, he ld the shutter open. and loo ked at the grou ndglas, at the foca l plane while the aircraft .... as Il)'ing alo ng a Hight· line, we would literally sc-e the ta ll huilding first enter tile gro undglass field o f vic .... ami then traverse ac ross tilt grocndg tass umil it eve ntually leaves the camera's field of vrc w.

- S5.1O' .

The actual height of the lower is R6 It measured .... ith a su rvcyor's tape. Care must he exercised when computing the height o f objects base d on shadow length III aerial photography. lrnponant factor s 10 be considered include shade w s fall ing

T he change in position of an object wit h he igh t. from one photograph to the ne, t rela tive to its background, caused b) the aircraft's mo tion, is called ,\/erf'o,\copic parallax. Pam/lax is the appa rent disp laceme nt in the posi tion of a n objeci, .... ith nesJX-"Ct to a frame of reference. caused b)' a shift in tbt positiun ofobse rvation. Pa rallax is a nonna l c harac teristic (If aerial photog rap hy and is the basis fo r th ree-d imensional srer..eoscopic vie w ing , Differences in the parallax of varices

"

163

iMoscopic Measurem enl o f Object He ig hl o r Terrain Elevation

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,

The hc rdaleJ to tlie a = 0 .5 11 in.). Th e differentia l parallax between tcll1l and base o f'the bui ld ing is identical to what was co musing the fiduci al line method. Jp = 0 .211 in .. and • IJ yield the same bu ilding hei ght esti mate. Some image .11I:o'>1$ prefer this simple parallax measurement techn ique.

Figure 6-22

CI~- uJ' \icy.

that we haw the altitude of the aircra ft abo ve ground

I' f a parallax bar wilh lhe- Iloaung and vernie r me asuring mechanism. It is attached to the lens stereoscope and placed over the

(1/ h) and the absolute stereosco pic paralla x (1') com-

stcrco parr io rnukcpa rallax rncusurcm cnts.

11I311.",

for these two photographs, it is possible to measure the " . The differe nce (P,,- Pt» results in the dI/Jell!nliul parvl/(1..{ (dp) measurcmcm required as input 10 Equation 6-17. lt ma kes no differe nce if the obj ect is man-made with vcrtical s ides or if it is a terrain feature. i.e., it can be the top and base o ra build ing or lower, lhe peak of a mountain ur a rive r floodplain. From thc ditfi'Il'/1/ial parafla>: betwee n the two

6

174

meas urement po ims. th...... lcvauon di ff ere nce may be dc nv cd. The principle of the Iloa ting mark can be used 10 map lines o f constant ek\'illi,)n in th e terrain . For exam ple. if'the Il03ting marl (the fused. red three-d irnensjc nal ball] were moved aroun d the stereo model so Ihal it mai ntained contact with the terra in. i.e .. it was not allowed to floa t above the terrain or go down below the terrain (which is possible when viewing in stereo! l. then a line ofconstant stereoscopic .r-pamllax would he iderniflcd. If this were do ne along the side of a mountain. the line of constant .r- paralja x cou ld be determined. \\ h jch cou ld then be converted directly into elevation above sea k H' I. Th is line of constant par-diu is related to actual elc vauon through the use o f horizontal Lr..I' ) and venica l 1=1 g round-co ntrol markers that were surveyed in the field. This i.. !lcl" US( iS topograp hic map" with contour line.. arc produced . Till': stercoplouer operat or places the Iloating marl on the terrain ( representing a specific elevation) and then mow.. the l10aling ma rk about the te rrain in the stereo mood whtle keeping the mark firnuy on the ground. One can convert the .r-paralla x measu rement 10 actual elevauon It) kll:a ting ho rizo ntal- vert ica l ground-control points (e.!:!.. I(10 II. above sea levd al locat ion x.y l in the stereosco pic model and determining its .r-parallax. Any oth er point wit hin the st~t"C'n",-,opic mood w ith the same .r para llax must then lie at l OtI II above sea level, It is also pe ssiblc 10 map buildmg perimeters by placing the ihrcc- dirncnsional nn ating mar k so that it Just rests on the roo ftop. and then trac ing the mark around the ~dg~ o f the roo ftop. This resul ts in a map nft hl: planimetric lX,y ) location of the bui ldm g.

T he si mple parallax bar (stereometer} is the least expensive and one of't he least accura te of all instrum ents that are based 011 the concept of the !lualing mark. Very expensive analo g am! digital stereosco pic plotting instruments arc available that allow precise paralla\ measurements to be made. For CX;II11p k, a Zc i~~ unulytica l stcrccploucr is shown in Figu re (,-13 . When used in conjunction with ground -control infer marion collected in the field . tIll' system ana lytically co rrelatc ~ and co mpulc.. the amo unt of-,-pa rallax tilr c; Bar

Ftgure 6-23 A Zr1S~ PJ Planicom p analytical ~t~'TCtlp lomr anat) , I vic.... s the stereo mod elthrou gh t~ lar I~~ s~ stem and can adjust the Ilcanng mart iny the c urs or "" the table loounl"'~' Carl zess Krwnml'lry published by the Ame rican Society . l' hotogra mm etry a nd Remote Sensin~ ( ~kGlonc, 200·;). Stercns('(lpic photography may a lso he acq uired on gro und. The stc rc..e copic photog raphs 1;3n be analyzed u the principle of' thc floating mar k III produce a detailed dimensiona l rcp rcscruution of the facade o f buildings dc sired (of coursc. field X. > :Z ground-control m....as urem nrc req uire d to scatc the ste reo model ). This is culled clrange I'hmogm m/1/l'lry ( Warne r et al.. I'N ('I; Wolf and [ iu. 10001. Ste reoscopic phorogramm etric tec hniq ues can app licd III terrest rial photogra phy til restore historical bu ings or recons truct a human 's ann. kg. or face. ,~

or

Digital Elevation Models, Orthophotos and Planimetri c Features using Soft- COP)' Photo gram met ry

O n.: the mllsl illlp"r11 b illion colon ) at repe atable spatial resol ut ions approach ing < 10 urn. Seienti sls ca n inexpcnsiv ely sca n hISto rica l images at high sp,lI ia l resolution fur phorogrammctric proje cts ( Koncncy, ::00 ) . The importance ofimage d iguization will become lo s im portant as mo re of the data analyzed in soft-copy phot og rarnrnetric sys tems arc cotlcctcd by dig ita l rem ote se nsin g sys ll'lIls.

Soft-Copy Phologrammetry

remote ly sense d dat a suitable for mediumk pbnogrammctric app lica tions arc a vailab le. For exa mit is possible 10 o btai n stereo panchromatic remote sen data wnh a nominal spa tial resolution of 5 x 5 m from :atSPOT and Ind ia n IRS-I C sensors (re fer to C hapter 7). epanchromanc data may he used to derive med ium -reso (l/l DEMs and or moirnagcs. de-puc the fad that ind i\ idhouses and sma ll buildings cannot be resolv ed .

Soft-copy pho lo gr.JlIln1l'tri.:: so ftware has made it possible for scientists and lay penoons rc create OEM s. pTl'pare on hophowgraphs, extract contours. and map thematic features of inte rest. Th is .::apahility is largely due to unprovcmcms in the photogrammctric so ftware that performs a) inte rior o rien tation, I'll exterior orienta tion , and c) ae ro-t riangu lation .

ager), with a spatia l resolu tiollof tl.25 tu 2 ,5 1Il is requ ired resolve trailers. houses. small buildings. narrow roa ds, . drainage networks. so importan t in many urb an-suburapplicauous (Jens en lind Cowen, 1 9 l)9 ~, Fortunately, iCraJcommercial lirms now provide high sputinl rcsoluI satellite-deriv ed remote sensor dat a that can be used to fide DEr>.ls. orrhoiruugery , lIlId some pluuiructric fe ature 'aCtion. (refer 10 Chapter 7):

tmerior onematiun is the procedure whereby the geometric characrcrisncs of an aeri a l pho tograph an: mathematica lly related 1( 1 the geometric cha racteristics (including de formitics) o f the camera system that took the photograph. Th is means csruhlishmg the Tl'l;ltlon,hip between I ) the camera internal coordinate sys tem and 2) the image pixel co ord inate system [Lind er. 200Jl. T his sk p requir es informa tion abo ut the camera sys tem , which is typically found in the camera ca libration report . Most frame cameras )1;I\-'e ;1 camera calibrarion report that was c rea ted at the time the camera was pro duced or rccahhratcd. Ty pica l info rmation required tor inte rio r orientation that is available in the camera cahbrauon rep\ln incluJ .::s;

De satellite

ieoEydKONOS I x I OJ panchrmnunc duta:

jrhlmage OrhVicw-3 I x 1 m pa nchro matic ,tlta ;

tnt crtor Ortcntatlnn

ligitalGlobc Quit:kBird 6 1 x 6 1 t:1n pa nchrolllut it: data .

iIe sut:h digital satellile re mote M:nwr data may never lace tht: demand for h igh-4 ualit)' lurge-scall.' aeria l phoraphy, there w ill be many appli ealion s where the DE\! s ,ortOO-rel.:tilk d satdli t.:: data an: su llic il' nt Thus. anoth.::r ior ~um b ling blod is bl'inl; Il .... ercoml' as re lati\ cly hil;h

r.y locatilln u f thl' prln .::ipal po int (e .g,. x.r " 0.0; rd er to Figure 6-6);

x,y locat ion ofal lli,lul:ial mHrks (m m ); len s focal length t crn );

178

• deformation ch aracterist ics orthc lens. Th e an alyst ob ta ins this information from the ca me ra calibrauon report and imports it into the interio r o rientation progra m. The image ana lyst then iden tifies rhe r.j- loca tion of the fiduc ial mark s assoc iated ..... ith each phot og raph produced by the camera. For example. consider Figure 6-27 where an analyst ts in the process nf pe rfonn ing interior cod entation for one of the photographs o f Columbia. Sc. Tilt" analyst is collec ting information abou t fiducial mark /12, [OC3 Inj in a comer of the photograph. The coord inates of a ll four fid ucia l mach from the camera cal ibra tio n repo rt a re labeled Fi lm X and Film Y in the d isplay. Th e image coor dinates of all four fidu cia l ma rks measured by the ana lyst are labeled Image X and Image Y in the d isplay. The- fiducia l mark calibrat ion report coordinate, arc then rela ted 10 the coordinates o r the fiducia l mark s measured hy the image ana lyst and res id ual s computed. The relationship between thi ~ partic ula r image and the came ra ce bbruuon informa t ion ha!> a root-mean-sq uared-error (RMSF.) of 1,12 pi'els (5 (,.76 f.lm ) \>, hich is ve ry good , Interior ori entatio n is performed fur each ph otograph in the block of phot ography. It relate s thegeo met ric churactcrisucs o f the aer ial photograph to the internal geometric cha racte ristics of the camera that prod uced it.

[ " e rior Orientatiun All aer ial photographs are t illed somew hat. We need to know how to model this tilt if we arc go ing to ex tract useful meas urements fro m aerial photogr ap hy. There arc s ix eleme nts o f ex terior orientati on that express the spat ia l loca tion and angular or ientat ion o f a tilted aer ial phot ograph at the moment o f exposure (Xl ,1'i .2l ,w,¢ ,,,,). Th e three-dim en sional coordi nates of the a ircraft at the mom ent of exposure arc XI.' Yl,ZI. where ZI. is the altitude of the ca mera above the loca l da tum . Atthe instant o f exposure the cumcm might be rolli ng. pitching. or yaw ing. These three an g les of orientation arc om ega . phi, and kappa (oo-O-K ). All the method s developed 10 det ermine these six param ete rs for eac h ae ria l photograph require pho tographi c images of at least three grou nd-c ont rol points whose X.Y.Z coordinates are kno.... n ( Wolf a nd Dewitt, 2 ()()O). If we can determine these param ctcrs for eac h ae rial photograp h. we ca n use the info rmation to re late image coordinates tu real-world (e x le l"ill r ) ma p coordin ates.

Exterior orientation determines the mathemat ical relat ionship between imag e coordinates (.l,):=) and real-wor ld map coordmate, lX [ X) for select ed ground-contro l points. r\ g rf/lll/d comrot point lCC!') is defined as any object in an ima ge for which real-world .r y.7. gro und coor dina tes a rc

C II.\ PT ER

6

Ph otogra mm etry

known (Linder, 20(3). We need to locate atIeast threc vel distributed GC Ps in ea ch image. Th is means that the y s be distribu ted so that they fonn a triangle in the image , shou ld not be loca ted in a stra ight hne.

High-quality orttficial (or ('III/d) Gel's arc usually rna in the field using a white L'roSS with ea ch o f the four leg! lil t' cross being 50 long and the width of the bars beingU wide (e.g.. 0.(, m) ( Wolf and Dewitt. 200 1). T he color of artificial Gel' sh ould contrast w ith the background rna {c.g., a while cross o n da rk as pha lt). ~ Iost analys ts have a rnfi cia l Gt'Ps at selected street intersections in the So met imes Gel's are located at strategic loc atio ns in countrysi de , The hcrizonrallccation (X. Y) and/or Z eleva o f the (;C P~ arc obtain ed using diff erent ially correc {static or kinematic) (i I'S measurements and the r geoi d mod el. The more horizontal/vertica l ground con points that can be located thro ughout a b lock (If aeria l tugruphy, the bcncr. The most acc urate exterior oriental w ill take place in areas surroun de d by art ific ial GCPs.1I zonta l contro l points arc usually sym boli zed with a tri an~ Vertical control poi nts arc symbolized using a ci rcle. II zonral and vert ical co ntro l at a point is sy mbol ized usingl tr iang le wit hin a circle. In addit ion to art ific ial ho r izontal/ve rtical GCl's. the i an alys t ca n select {'II'" points [som etimes referred to as ura l points ) w ith in thc ove rlap a rea of a ste reo pair. P points should he cle arly visible in each photograph of stereopair te.g .. the corner of a st reet, base nf a tclcph pole. irucrsccuon o f two fences ]. The analy st obtains the locat ion o f these pass poi nts in each image o f tile stcre Pa~s po ints can be used to pass cont rol from o ne phot to the next in a strip of aerial phot ograph y. Tie poifftJ pass points located in the : 0 percent s ide lap area (refer Figure (,-2 ) that ca n be used 10 pass control from one lli line strip of sli" gs " supe rim pose d on a SICrcopair in three -d imens io ns . The analyst ca n edi t indi ..idual elevat ion po stings by moving them so thai they come in C(lIItac t \\ nh rhc ground us ing the "principle of the floating mark," whereby each posti ng becomes a lloaling mark . :11Ic: :lIla lyst may l) correct indiv id ua l posrings. 2 ) select a pol~·· g,>n of rust ings and c hange all of rhcm (0 the same clevauce, or 3 1 selec t a polygon posungs a long a slope and halt them scale d 10 lie between the hig.hesl and lo west poiras encountered w ithi n the polygon. When care fully use d. lilt unulvst cun correct mos t problems enc oun tere d in the OEM, f or exam ple, the D EM in Figure 6-30h was edite d so thattht It'p of each build ing was at the correct e leva tio n. DEfW a depicts a DEM o f a four -b lock rcg ron of the Universit y of South Carolina campus derived tron: I:6.000-scalo: photog ra phy. Tho: hlocky appearance of the I>l :~ is du e III

\ Id hnth Uxetl tu Edil :1 DE\1 Im pa t·t Its Acruracj:

or

~tal

...

-

Elevation Mode ls. Ort hophotos and Planimetr ic Features using Soft-c opy Photogram metry

ede elcvauon informat ion a bou t buildings and tree s may J ofuse if the ana lyst desires to drape a n o rthophoro o n top ~ OEM and perhaps do a "fly-by" through the city. eWT. i f the analyst wanted a DT\1 o f j ust the nominal und terrain ill the four-brock regio n. this is certa inly nor nr in Figures 6-30ab. 10 create a [)E M of the region thut docs 11m have building Jd tree informat ion in it, the analyst must usually manually i!il the clcvmio n "postings' in the DEM that co rres po nd l ith the building s and tre es anti etfecuvety drive OT pu -h f.'tm 10 the nom inal terrain he igh t in the area. Th is c an be iffirull if a buildi ng or stand of trees is large. UOWCWT. if buildings a nd trees arc not too larg e it is possible to iden" the general tre nd of th e terr ain bctw ecn b uildings and I.ge trees such that th e -postings" of bu ildin gs and trees ca n mov' ed to the nominal terrain elcvauon. Ca reful editi ng o f original DEf\1 in this manner ca n p roduce a revised OEM depicts j ust the local re lief ofthe area, withou t build ings trees. as shown in Fig ure 6- 31k;, A percent slope dataof the reg ion (important ill ma n)' cnviro nrncnta l and ~~'drol()gic slUJ ies J cannot accurate ly be computed from the OEM with buildi ngs and trees in it. II can be pro duced from ~ OEM with bui ldings and tree s removed. as sho wn in Fig -

k

~

b

m 6-3Od. l.Ttbanil c-d areas wi th buil d ings and trees ma y hav e to be laIlually edued to obtain a OEf\1 (If j ust the nominal terrain . fbi;; can be a labo rious process and is subject to error bei ng LKc-d by the ana lyst. Th e larger the scale o f aerial pho~ ph~' and the greater Ihe hei ghl (If the bu ild ings and res in the study area. the greater the di fficulty of ibtaming an ac'curate OEM o f the terrai n. OE f\ls are most curare ami requ ire the least ed iting w hen prod uced for 11:1111 areas that do not ha ve sig nificunt "l eaf-on" tree cover II!man-made struc tures (bui lding s, bridges. ctc.). for example, consider the high-quality DEM ex tracted from kge-!lCale aer ial pho tograph y with few trees or bu ildings iIIown in Figure 6-3 I . These four te st pads (In the Savan nah l iler Site ncar A iken, SC a rc used to evaluate the effe ctiveess of various haza rdous wa ste site clay ca p ma terials . Iege-scalc ste reoscopic ae rial photography of the test pads Illesplace rout inely w tha l any subsidenc e [i.e., dep res sion I i1lhc clay cap!> can be documen ted immediately. Figure 6l la OOcumen ls the sck-clion of sround-e(lntrol raint ;:5 d uro i;g the exterior or icntat ion ph ase \If the project. Cu ntrol p.>int 1:5 is a IS-i n. plastie pipe e_\ tendi ng 30 cm alxlVc the pnd, whic h was sUr\cyed to wi th in ::!:.3 em using (iPS. The digital elevation mo\leI t'x tra~· ted a ner aero- tnangu l,lIed lI\ i1 h Orlhn im a 2:er ,. Dertv ed U:ooin g So fH.'Op" l' holugranullcl r ,.

The accuracy of a d igital onhoimage is a function of the quality of the imagery. the ground co ntrol. the phorogrammet ric triangu lat ion , and the DEM use d In create it (Fig ure fi-2fi), An onhoirnage m ay be produced from the original DEM . a DlM with bu ild ing roofto ps cleaned up, or even a [) EM .... ith buildi ngs and trees removed . A DE r-. t produced from th.. collection of li e ld surveying or even digi ti/oo contours ma~ also be used 10 create the orthoimagc. Th erefore. th c an;llyst sho uld al.... ays have ac cess to the metadata (history ) of h.)\\, the DEM .... as c reated, In Ihis '>\a~ on ly the most approp riate DEM data .... 111 be used in the creatio n o f the orth ruma gcry . Large-scale te.g.. I :6.0(0) urban unhoimagcs de rived from uncorrec ted DE1o.ls etten ex hibit severe distortion of bui ldIng edges [ Nal... I'I94 l. For e xample, the orthoimagc in Figure ()·J -ll was derive d using ;:111 unco rrected [) [ M whi le Figu re 6-J 4h wa s prod ucc d usin g a D EM wi th I'ouild ings and

186

( "HAPI t:R

3.

Orthop hoto derived from uncorrected OEM. Figure &34

Pho togrammetry

b. Orthophoto derive..rd from corrected

D E~ 1.

The qu;l1ity orth.: OEM i nll u'.·l~(~ tbe quality of the onhopboto.

a. OnhopholOdraped ove r uncorre cted DE\ t. FIg ure 6·35

6

b. Onhopho to draped over corrected OEM.

The qu;alily of Ilk- DfM influences the - J 7a . T he roof will be sho .... n wh ere there shou ld be gro und at III..: bad .. of the bu ildi ng. and the ~ i dl;' ofthe building will he shown where the roor sho utd he . 11\4' ground behi nd the huiMing will not he sIK1\\1l ill all. Th ese disp lacements arc relat ed to the hci gh r of the bu ilding and the pos ition o f tho: bui ldi ng in the origi na l pholo . The greater the ht'i ght of the buildmg and the closer u i, 1(1 the side of the o ng mal photograph. the worse the displacc rncm

11.

Conventiona l orthoohoro.

will he. An elegaru sol ut io n 10 the above onhophotu proble ms wa s deve loped ( Walker. 11)Q·k B:\E Sysle ms. ~Oj) 5). In Figu re 6-J 7b \ H" see th ree tnan gutated aeria l pholl}graph s and a DEM cov ering the e ntire Ioorp rim of the projeel a rea . L: si n~ tradirional ihrcc-drmcnsiooat stereoscopic feat ure ext ract ion tools, the ouuines of hu ildi ngs. bridges. and other obsuucnon s arc identifi ed. Howe ver. the bri~h lness value or gra) to ne fo r p ixel /I is interpo lated fro m rhc mos t nad ir (direct ly overhead ) Expllsurt' SIal io n (=3 in Figure b- 37h ) that has the be st \ icw of the ground at location (I. The a lgori thm then exa min es the DEroo! an d feature d ata a nd determines that the \ ie\.'. of the ground for pixel h is obscured by the bu ild ing at Exposu re Srauon #1 and automatica lly sele cts image ry frum Exposure Station # I to ob tain the proper p ixel color for pixel h. The application o f these algori thm s results in a trueorthnp ho /I! whe re :

building rooftop, arc ShUll n iuthcir correct planimetric X ..I ' Iocauou: the ground on all sides of a ll buildings is shown in ils prope r location: tops and honoms of O\i~'rp;hSl'S arc shown in their proper locat ion s: o nhopluuov anJ map sheers can be made that are larger than an )' o f the input illlilgCS. A comparison be tween a rraduional o rthopho logrl1ph an d 11 tNI') and lomp-'rat"' '' dinCrCII ".' Ii" the' thermal Ull"a,,,d ....",,1, t " r,\ fl. ~ \l ~ S h"nd, 4, 5, 1>, and 7 " ,'r" rc" ,,"' ......rcd Ix""l, 1. 2..'- ." ,,14 Landsat, 4 ~ "d~. ' ~ SS bond ll ..... a. ptc"'1\1,.nl>" nl ...",I, .1t ,

.lmrling interv al or MSS J;e~

Land.nJ .lIO.5 . 0,1i ~ml_

Figure 7·1 0

r

995

Rd atil.nshir bt'1...een tho: original 79 x N m rroJCl.'1t'n C; ru u nd r r"j ,'Cl jnn or Sca n r al1rrn

•

s• :

i

A['Cn un: sunslude

~

. :

L UII,J""t

groundtrack

Fig u re 7- 12

Major com p onents orthe Lnndsnts 4 and 5 The mat ic Mapper ..cnsor system. The senso r is sensitive to th..- sewn hands oftit dCdfOlllagnctic spectrum sununanzcd in Table 7-1. Si'I. (lfth.: seven bands have a spaual resolution 01"3Ux 30 m: the I infra red hand has a spatml resolution o f I:!n x 120 rn. The lowe r dia gram depicts the sensor in lis ope rational po,i lillO,

parallel act io ns, Congress fundc-d Land sat 7 procurement and stipu lated that data fro m publicly funderd rem ote se nsing satellite syste m, like: La ndsa t must be so ld 1,1 United States government agencies and their affiliated users al the cos t of fulfill ing user requests .

Wilh the passage of the Land Remote Sensing Policy Act of 1 Landsat Multrspcc tral Scanner (MSS1. t alllh als 4 and 5 l h... mane Mappe r (Tl\t ). Landsat 7 Enhanced Thematic Mapper Plus ( ET M ' ), SPOTs 1,2, and 3 High Resolution Visible OliN), and SPOTs4 lind 5 High Reselution Visihle Infrared /II RVIR) sensor systems. The SPOTs 4 and ) ~hf,'I, mon sensor ChaTHe' lcri, tics arc not shown / it eonsists of four I ,I S x l .I S krn bands).

mrintain data co nt inuity by providi ng data that are consisten t in terms of geometry, spat ial resolution. calibration. cov erage char;ll; ter i, ties, and spectral characteristics w ith p rev ious Lands at data: generate and periodically Tefn:sh a global archive o f ;ubslantially cloud-free. sunlit landm ass imagery ; conti nue 10 mak e Land sat-type da ta ava ilable to U,S. and ecmanonal use rs at the cost o f fulfillin g use r req uests and 10 expan d the use of suc h data for global-cha nge research and co mmerci a l purpo ses.

Landsat 7 IS a three-a-c is stahi lized plntform ca rry ing 11 si ng le nad ir-po inting instrument. the I:T\1' (Figure 7- Hi). The ETM - instrumen t is u derivativ e of'thc Lnndsar a and 5 Themat ic Ma pper sensors. Th ere fore , it is pnssih le to refer to Figure 7- 12 fN a rev lc.... of its mi rro r and detector design . T he ET ~I' is based on scanning tech no logy (Figure 7-3b) despne tho: ta ct that linear ,IITay " pushtlroo m" technology has been com me rcially available since the launch of the Fre nch S POT I satellite in 19S6 . Neverthel ess. the El M " instrument was an excell en t sensor with seve ral notable imp ro vements o ver its pred ece ssors landsat ~ and 5. The characteri stic s o f the La ndsat 7 ET :vl' are found III Tab le 7-3. The ET ~r band s I through 5 and 7 are ident ica l

( 'IL\ PH ;K

208

7

Mu lti spectral Remote sen si ng Systems

l ,andsal5 tnemauc .\ Ia llpl'r Dat a uf Charleston, SC

d.

&I n.!~ .

c. Band 5.

Rgu re 7-14

f. Hand to (thermal infrarcdt,

Landsat Jbe mauc Mapper data of -i /\ SA )

De partm ents of' Commcrcc. Defens e, the Interior and NASA are to rake the fo llow ing ncar-term act ions:

iccrion. archiv ing. prne.:ss ing, and distribmion of the lane cnrtacc d ata to U.S. rto vcrmn cnt and other users:

• Proc eed w ith the NPOESS prog ra m w ithou t inco rpo rating a Land sat-type instrum ent:

• The agenc ies \\ ill seck III impleme nt an approac h for thi;

• NASA .... ill acqu ire a single La ndsat da ta contin uity mission in the form (If a tree- flyer vpucccnul 1\\ collect the required land surface data and deliv er i t ~ da ta 10 the Department o f the Interior U.S. Gl'tl log ical Survey {USGS); • DO l. throug.h the USG S. will he respo ns ible for the operations of the Landsat dat il con un uuy m ission and for th... col-

mlssi"n in a ma nner that l!nes nOI preclude it long- term ,;olt, non li ' r con tinu ity ,If Landsa t-type da ta. II remains the glIal o f the U.S. ctovemme nr tc tran sit ion tIE Lan dsat prog ram limn a series o f inde pen de ntly planned miss ions to n s usta ined operational prog ram funded ~ mallagcll h~ a tf.S. Gov ...mm em operat iona l age ncy or agend es. international consortium, and/or co mmercia l partnership. Concurrent wit h the actions ci ted above , th e :-':atiOllll

Ta

.... MuIllspecl ral lm ag lng Using mecrete Detect ors and Sca n n in g Mirror s

Table 7-3.

Landsat Enhanced Thcmanc Map per Plus t E T ~l

'.

.•

2 11

compared with ttl," Eart h t jbserver ( Hl. 1) sensors.

EO-' Advanced land Imager (ALI)

Landsat 7 Enhanced Themat ic Mapper Plus (El M' )

Spectra l Resolu tion

Spa t ial

S patia l Res olution (m) at Nadir

Spectral Resol ution

Resolution

l~ ml

(m) at Nadir

Band

0.4 50 - 0 .5 15

",0 x 30

~ S- I

OA.13

- 0.~ 5J

30>< 30

0 .525 - O.N IS

30)(30

~IS-I

OA50 - 051 0

30 >< JO

)

0.630 - O.6l)(j

30 x 30

~ S- 2

0.525 - 0.6115

30 >< JO

\I S-7

2.01< .'0

Panchromatic

OAIIO - O.toW

10>1 recent gcncrutiou n f'gcos unionary satellites bcg.au ( iO ES-X, which w as laun ched in April. 1 l)~4 , GOF.S-Q launched on I\lay 23,1 O scans pe r minute. ,\ tota l of2.(H8 sam ples (p ixds ) arc ohtamed per channel PL'r Earth scan, w hich span~ an an gle o f ± 5 5.-.1 ~ off- nadir , Tho.' IFe)\ ' ll f each hand is npproxinuncly 1.-.1 nulliradians leading to a rcsolu-

tio n at the satellite subpoint o f 1.1 x 1.1 kill (Fil! ur~ 7-21 The more recent "V I IRR sys tems have li ve channels IT 7·5 ; Figure 7-2 1b l.

Fu ll reso lution AVIIRR d.ua obtained at 1, 1 x 1.1 kID ca lled Im 'a l IIIl 'iI ('oV/'rage ( L4C) data . It may be resam I tu4 x 4 km glo f,a/ /.)/"I:iI Cf)l't.'ro~t' I GAO dat a . The 0:\( contai ns on ly one o ut of' thrcc origin al AVIIRR lines a~ data volume and resolution are further reduced hy s .... ith the thi rd sample a lullg the scan line . a\crdging the four samples. and skip ping the ne:\.t sa mple. The sequence a verage four. skip one is conum«..-d to the end of the: line. Some studies use GAC dat a .... hile orhcrs lise the reso lution LAC da ta. The AV)IR R pro vides region al info nu utimr on vcgClaOO:

condition and sea-surface tem peratu re, For example. a JXf' rion of an AVHRR image of the So ut h Ca rolina Cl\ll: o btained on ~l ay 13, 1993, at 3:(JO p.m. is ..ho ..... n in Figtrr 7-22 . Band 1 is approximately equivalent til Landsat nI band 3 , Vegetated land ap pea rs in dark ton es due to chlctph) 11 absorption o f red light . Band 2 i s appruximatc ly eq.r.. aleu to TM band 4 . Vegetation reflects much o f the infrared rad iant I1U\. yid d lng bright tones. .....hile .... absorbs much of the mcidc nt energy , The land -water I fa ce is usually quite dis tinct . The three therma l band s vide informatio n about Earth 's surfa ce and Vi temperatu re. Th o.' gray sca le is inverted for the therm al infrJ. red data wit h cold , high clouds in blac k and warm land mI water in lightt"r lunc s, '1his particular ima ge captu red a large lobe ofwarm G ul f Stream wa ter.

M

"

~

217

llltispectral imaging Using Discrete Detectors and Scanning Mirrors

~ol3r

s;'lcll, IC ' ... \oo;al Lc'flil h

'(II

~

I'r,lar

J'l'fluh

.,n~k

Z,,"h line:

Orhilr r

Il...d

"'\lUII( B~nd I

~un

angle

~

/

• 211

S,IL'lIilC /

o

);:II1l11~k

,( 10

~ 1:1(1.. and warm IJm.! J IlU'" arcr ill ligh....r I"UO:S . A large lob.: u f " arm Gulf Stream water is easil} identified ( I m'lg,·~ COI.mC~} of l'\(l,\A I

SeaWi FS observations help scrcnusrs understand the ~namics of ocean and coasta l currents. the physics of mixmg. and the relauonships between ocean p h) ~i t:li and largescale patterns o f producti v ity, Tho: data fill tho: gaps in ocean

biolog.il'a l observations betwee n 100. and -I [ncar-in frared , red. and gre en ) is show n in Color Plate 7-5 1'1 . :\ear-infrarrtl band 10 ima gery o f the :>ame reg ion co llected o n April :!3. 199 :!. is show n in Color Plale 7-5e . Co lt)r-Plal e 7-5d is a color co mpos ite of I>and~ 10, tl . a nd -I. T he nna l dU uent wa.s nm

7

Multi spe ct ral Remote Sensing Systel'l'!

Multi s ~

allow ed ro enter Four Mill.' Creek ette r I9X5. Examina the image/) reveals that revege tation has taken pb.l many o f the wet land sloughs.

:"IAS.\ Airlmrll c -li: r r\'\ l ria l A p p l icli l iu n~

St' n~ur

:-':A SA'~ ATLA S multispectral scanner is operated ~ Ste nnis Space Ce nter. ~1S . ATLAS has 1-1 channels '/I spectral range from 0..1 5 10 12.2 urn . Th ere are six vi and ncar-infra red bands, two short-wavelength in band s (ident ical to Thema tic Mapper bands 5 and 7) mi therm al infrared b ands . Th e ba ndw idths arc summ arizer Table 7- 7. The se nsor ha s a total fiejd of vie..... o f n~ ui IFQ \' o f :!.O m rad. ATLA S is flown on a Learjet 23 from {,ooo to -11 .1100 11. abovc g round level, yielding wit h a ground resoluuon ofappro ximatdy :!.5 x 2.5 mte x 25 m, depend ing upon use r spcc jflcatio ns. There art rna lly !U1 r~IMl"T'o scrvatiuns can be mad,' on successi\t~ days such that the Iwn images are acquired at angles on either ,iJc of the vertical. rcsulung in ~t,Te,>rle imag,·~,. Such imagery can be used tll prud uco: topographic and planimetric maps (,ldapt"d fwm SPOT ImaJ;':. llle.l.

228

C II .W I F R

7

Mult ispectral Remote Sen sing Sys tems

Com pa r tsou or Landsat '1':\1 (30 '\ .'\0 ru] and SltOI' 1I1t\' (Ill x 10 m )

a. Landsat Tbemanc

\hr~

n allJ J I3 U \ :;O m) un Fcbru.rry .•. 1994. Figure 7·29

("~mr"ri ""n ",I" the dCI"il in .' 0 x ~O m l...ndsat T~I ":JIlt! J d"IJ and ~ N)T lOx 10 II I 1"lIIdn,'mooy, n in Color Plate 7-7 .

The Ind ian ;-.Jatillllal Remote S~ l1> i ng Age nl') ( ~ RSA ) has launched several Ind ian Remote Sens ing lI RS) satellites: IRS- I:... o n " lar ch 17, I Q.~ !I. IRS· I B on Aug us t 29. 199 1. IRS- I t' in 1995. and IRS-I D in Septe mber. 1997 (Table 710). IRS-PJ and IRS-N were launched o n x tarc b 2 1. 1996. and vt ay 2n. IQQIJ. resp cc uv ety. IRS -1'5 (C \RTO SAT- Il w as lau nched on May 5. 2005 . IRS-Pb I RESOURCESAT- IJ

.... 230

C"l1\rTE R

r I•

Figure 7-30

Multispectra l Remote Sens ing Systems

J,u!i;lll Re m" l"

S"nsi n~

Multi s pe

Sah'lIilr IlIIa!:,' ur Sa n Dic~o,

Landsa t T hem at ic :\ Ia ppc r a nd :\l ulthpcct ra l Sca nne r ima~e a rea

60 km

J

1

S POT HRV image rrrca

60km

185krn

•I

G':O\:lT.aphic co verapc of ee SPOT IlR\" and Land '1.31 'i ll hi ~{I('(' lral Sca nne r and Thematic 'lapl"t'T 1\'mot e !oCn~m g sys tems.

was launched on October 17. 200 3. The sensors onboard the satellites usc linear array sensor technology (t\ RSA. 20(6).

Figure 1·31

IRS-I A . · IU. - Ie. li nd - I n

The IRS·] A and IRS- I B s.uellites acq uired data with Linear Im ag ing Self-scanning Scnsors (L1SS· [ :IlIJ USS-II) at spatial resofuuon s o f 72.5 x 72.5 m and 36.25 x 36.25 m. respectively (Table 7· 10), Th e data w ere collected in four spectral bands 1[1l1i were ahnosr iden tica l to the Lands at Tt-l visible an d ncar-infrared hand s. Th e snrellne altitude was lln4 km. the orbn was Sun -synchro nous. repea t coverage was every 22 days at the Equator rll-day repe at co verage with two smcllucs }, and orbua l incl inat io n wa s ()().5 ~ . The swath width was l-1fl to I-IX km . The [RS-IC al1ll IRS- 1[) satellites carry three sensors (Tab le 7- 10): the Ll SS- ll l mult ispeelral sensor, a panchromat ic' SC'I1sor, and a Wide Field Sensor l Wi r S). T he L1 SS·l1l has four bands with the g reen . red. an d ncar-infrared bands at 23.5 x 23 .5 m spatial resolution und the short-wave leng th in frared (S\V[R ) band at 70.5 x 70. 5 III spatial rcsohnion. The swath widt h is 1-11 km for ha m!, 2, 3, and 4 an d I-IX krn 1111' the SW IR band . Rcpc:l1 coverage is e very 2-1 J ay " at the equ ator, T he panchromatic se nsor has a spatial resolution of npproximately 5.2 x 5.2 m and ste reos copic imag ing capability. T he pa nch romat ic band has a 70 -km swath width with repea t coverage every 2-1 days at the Equato r an d a revisit t ime ofS da ys with ±16° off-nadir \ il."v. ing . An l.".,. .un ple o f the 5.2 x 5.2 III panch romat ic data o f dOV.llloV. n San Diego, CA (resamp led to 5 x 5 rn], is sho wn in Fig-ure 7-3[ ,

Indian Rcnw te SS l. whi ch collects data li t three Sfii' tial resolutions (M OS A, It (' = 1569 x I W5 m: 523 x 511 11l; and 513 x (,-l-l 111, respect ive ly ) in three ba nds (MOS B. C "" (USS - O.761l urn: 0.40,'\ - 1.01 um: 1.5 - 1.7 unu Th..' IRS-P-I satclluc is de voted 10 oc eanographic applies tio ns base d pri marily on its Ocean Color Mo niter (OC~11 sensor, whic h collects data in 11 hands from -102 to Sf:5 nm. a ~ r .. rial resolution o f 360 x 1311m at t z -bit radiomcuic reelution. T he swath wi dth is 1,420 km. T ile IRS-I' -I alsoce ries a \ !ul lIfrcqllcncy Scanning Microwave Rad iomee ( ~ I S f\ I R ) (:'>IRSA. 2006).

I R~-I '5 leA R l(}SAT- I ) ('ARTOSAT- I wns designed to provide imagery for I~ scale ca rtog raphic applicil l illn~. Th e satellite is in a Su n-s~1l-

chrc

cnn

CA

"m nn e 100 om

,m

'me eo im

"" oc

"

R

0'

11 t s s

a

23 1

IWispectral lmaging Usi ng linear Arr ay s

:-.I AS:\ Ad~an~~'d S['iIl:chllrTlO: Thcn nal Emiss ion and R".rkcl i" n Ra,Jj"mm)

I (nadir)

0.52 - 0.60

,

1.600 -

2 (nadin

0.63 - 0.1,1,1

s

2.1..15 - 2. 18S

Ltnadir )

O.76 -0,l'I6

6

3 (backward)

0.76 - 0.1,(1

7

, ,

u no

TIR Spectra l Resolution Band

(Jlrn )

10

11.1 25 - 11.475

2.1&5 2.215

"

8.475 - 8.825

12

11.925 - 9.175

2.:m - 2.2S:'

13

10.25 - HI.95

2.295 - 2.3M

14

10.95 - 11.6 5

:U6O -1.4JO

Pushbroom

Pusbbroom

WhisLbroom

Si

PtSi:Si

Ii ~ Cd : Tc

Spalial rr-oluliUlI (m)

IS ;ot IS

; 11 x 30

l )"t'w-.l sa tellite; and DigualGlobe. foe .. Vlliun-synchronous 1:4UHlori,,1 erus~ i ng \'ariahle

.~ JlriI 2 7, 1

sunuuurizcd ill Table 7· 1J ,mel the hlgic 100\\1\ in FigH r.., 7-.1 7. Three of'thc linear array s collect pan womal ic data : one lo"ks forward 2i1A"'. nne hhlks ur nadir, sdone lucks aft - I..!..:!" [there .rrc ac tuall y two l2 .o0n clc:amt linear a rray s :11 ea ch of the se three locations stag ge red II} half a pixel (3.25 nun]. which are ;Inaly/ l;'u together to \'JddpanchMllalic dal a ] t x tccronc. 2 110~). Tk blue. green , and red scnsiuve linear array s collect data Ie off-nadir. TIle blue, gre en. and red measu rements arc okJi~lI lI' i lh a trich roid opticnl SYStl'l11 that splits inco ming h!ht uno n..d . green, and blue com poncms us ing cascaded IfidJrotic flhcr s. Th is res ults in pe rfectly rc giste,c:J blue. peen. and red in formation . A nea r-in trurcd ......nsiuv c linear may 100",", 2' otf- nadrr ..oi lhin the pillcll rOy

Figu re 7-37

Ch aracteri srirl. R~a 1c couce. anJ ro.>d ~u r fac ~' extracted from :! x :! m (\.11a .... hmined near Bakersfield. CA

7 linear array CCDs

8lwtur ~ilC'

0IHI~(J1~

Crop ~ pccl ra Oh tllillnl

WOIl

Applani x !' OS IM U with m-s and INS

~JIlCC data w ith suffi cien t spectral resolut ion tor the direct *nliticalion of those mate ria ls with d iag nOSl ic spectral m rption features . For example. Figure 7·3S depic ts high ~lr.I l resolution crop spectra ove r the interval ~(lO to lOHH oblained using an imaging spec tromete r for an agricul'lIll ~rca ncar Bake rs field. CA. The absorption spectra for k Pima and Royale colton diller from one another from twinS om. \I here th..." red edge" is located, 10 aOllul 90 0 leading to 10c pos sibility that SIX."l,: io:S .... ithin the same I1tf type might he dist inguishable (S BRC, It,lt,lol). T he UIIlbJl scanners and Sf'OJ' II RV s...nsors, .... hich ha ... e rete) lall;': ban dw idth s, may IUlt be able to resolve the se ~I duferences.

Simultaneous imaging in many contiguous spec tra l ban ds requires ant'.... approach to remote sensor system design. O ne approach is 10 increa se th... reside nce time of a detector in each IFO V using a linear army or detector clements (F igure 7-.k I. In this con figurauon. there i-, a dedicated detecto r clcmcnt for each cross-tra ck pixe l. .... hich inc reases the rcsidc ncc t im e III the interval required til mo ve one II'DV along the n ight direction.

T.... ll more pmcucalapproachcs 10 imaging spectrome try are shown in Fig:ures 7· J d und Je. The .... his kbroom sca nne r lincur a rray app roach (Figure 7·3 d ) is "ll aloguus 10 the sca nner approach used for Land sat " ISS and ETJ\l ', except that radiant flux from within the IFOV is passed to a spectrometer, whe re it is dispersed und foc used onto ; 1 line ar array o f detectors. Th us. each pixel is simultancouvly sensed in as man y spe ctra! band s as there are dctector c temcms in the lincar arr ay, For hig h spat ial resolution illl.,en', lIio,,-,

/1'''111

Shulllt·· J/ ir J /in iom ,

:'LY.: Ju hn \Vi h,:y. 2M! p.

NAS .'\ Arrbom.... 2(lU(,. .vASA ,4" ho" m: S..,n ,," Facihty. MulTc lt Fie ld. C A: I\AS,\ Alii ...,. Airborn e S c nsor Fac ili ty. hltp:llas ap-

data. arc.nas a.gov /. l" AS A AS TE R. :!fl(lo6. ,4,1,,,,,,,,,,01 Sl'd,·e"'. m~' TIt,',.-m,,1 £ mi.uilln ,mol R,:f/t ..tion RoJ","', ·I,'''-, htt p:l'astt:'rw et'o .jp l.na sa .gov/. ;';AS,\ AVI RIS. 2006. .4irb." " ,· li.,ihl.· I"/ ,,,red 1"',lgi " g S".,c/...uneter. hn p:f1a\ irss. jpl.na(,1.(:llvf. l"A SA r O - I. 2()o(" E."..,1t 0 1>se,....,,.- 1. hltp:f1eo l .gs fe ,nJsa.go\· NASA ~ S l::. :!OOt>. t:"",n $("1"'" e t:III"rpri~ .:. hllp:flscience .hq.nasa.gov /!>t rale ~}". l"ASA La nds at 7. 2(lU6. I..mJ,,,, 7. h tlp:l/landSllt.gsfc. noiSll.g U\

NASA I fl C \ l . 2OtIn. f .1 an d S. Kulyanuratnan , 20\lti. "Indian Re mot e

Stllsinl1 Satclfnc L'artosut- L: Technical Featu res und Datu rrodueb : ' GIS 0 "1'

aluminum . ',111

0. 0 5

aluminum. polished

O.OR

aluminum. paun

0.55

polished metals

O. IIl - U.2 1

Th is rela tionship is im portant because il describes objects ap pea r as they do on therm al infrared i Because the terrain tllt'orr.'lic"/~\" does nor IOJ(' (Illy i et!e'Xv I" trunsminance, " II t"/lt''X~' leaving lilt!' object rn.. acconmedfor h)· Ih.. t'l:luti'J/1!ihip b..tween rept'c!u1/Ct and emluil'ity (fi) ' l f re tlecnvity increases. t hen emis mu-t decrease. If emissivity increa-es. the n reflectivity dec rease . Fo r example. water absorbs almost all energy and reflects very tinte. Therefore, water is a good em itte r and has a high emisshi!y dose to I. C vcrscty, a shee t-meta l roof reflec ts most of the i energy and absorbs very link', yiel ding an em issivity kss than I. Therefore . metal ubjl"Cb such as cars. ai and me tal roo fs USUJ lly appear very co ld (da rk) on i nfra red imagery. For example. the metal hangar and ai in the nighttime thermal infrared imagery in Figure appear cold. No te that se\ l'ral a ircraft haw th....ir engines whi ch arrear bright . and that their jet blas t is w arming . tarma c. When measuring lnud or water surface tempe ratu re. the glII o f Ihermal infrared remote ~cnsi ng. is to be able 10 poiln radiometer at an object and have the recorded ap parent ant tempera tu re (T......I equalthe true kinet ic temperature the o bject ( T i m )' Unfortunately, th... radi a nt nux from a rQ. world .. bjcct at a given temperature is not the lk1111e as tic radiant Ilu\ fro m a blackbody at the same temperatlllt. lurgcly due toth c ctl c cu... o f f'l1II.'.\ ·ivily. Kno w ing the emisseit)' of an object mak es il po ssible to modify the Src fan-Bok zmann law orig inally applicable In blackbodies (.\.1, -; so that it pertains til the tota l spec tral raJian t tl ux of real worl d materials (.\f, ):

r»

ur

oxidized ste..l

0, 70

gra nite

o.es

dunitc

n.71!

basalt. ro ugh

0.95

'lhe equa tio n takes into accou nt the tem perature of the

(un - 11.111>1

of

. \ r ro ",,·T r a r k

Tht

Thermal infra red scanning system s (actually all ~)'~lt'ms l introduce num erous t)pes of geometric eTroI' mu- abe understood because lite) imp act 1) the qualilyol imagery lo r vi sual o r dig ital imag e procc-s.s ing and a~ and 2 ) the creauon ot plarnmetnc maps trorn the I infrared data . 111... most important considerations indlll!t gro und "" ath w rdth;

CUlling in ha lf the di stan ce o f a remote sens ing detec tor from a point source qlladnlples the mt rarcd energy rece ived hy thaI detector. The inverse-square law stales that " the inten sity of radiauo n emit ted from a po int source var ies as the Inverse square ofthe dist ance betw cc n source JIll.J receiver," Thus, I l l' can ob tain a more irucnse . ~Irong therm a l infra red signal i f we C;III gel the remote sensor detector ns close to the ground :l~ prac tica l. For exa mp le. con-ader a bl;lc"hud~ point ~t,urn: , S. and two remote detectors (D I and D 1 ) \.f\'qU'll sensitive area. say, I elll~ . Det ecto r /), IS a dis tance drm from S, and detector I): is at a distance 2 the ,>bscrvauon. i.e.. II is lhe altitu d e o ft he aircraftabove groun d level (.\t i l);11 na,lir ami 11 w,. ~(llr-nadlr: h) the mstanumeous field Ill" \ leW (If th... "';1lS\)r.I ~, m...a s urc...J in nulhrudians. and c) the scan ang le off-u.nlir. o. "l1lUs, pixels t>tT-n,Il.lir ha\ e semi-major ami sem i-mino r aM.OS (J i;lmc Lers) that de finc rh... r.-sn llllin n cell Si7,'_ ( )nlrJ

l'I

ilh

Ont·f) imt'n ,iuna l Rl'Iid Displa cem ent anti T an~t'nlilll S13I11C,J over le ve l terrain. Four 50· 1\ tanks ill! tributcd lhn'ugh,l\ll till' lambc3pe and experience \: Irylllg .lcl!TCI'S of radia! relie f d isplaceme nt thl' further they aTC fro.. pri nci pal pI,inl (1'1'). b ) Across- truck sca nni ng S}SIC IllS introd uc e onc-dimcusinua l relie f displacement pcrpcndiculer e line or nigh t and tangenunl SC;11e distortion and colll pn'ss ion the farther the object i~ away from nadir, Linear features ing aallS> the terrain arc often recorded with s-shapcd or sigmoid c urvat ure chaructcnsucs due III l.mgenl iOlI scale JI\ and compression.

Thus. the size (If the ground reso le no n cell increas es as the angle increase'S away from nadir. The nominal {average) dia metc... of the elli ptical resolution ce ll. Do. at this angular locat ion from nadir has the dimension : (l'i-19j

in the d irection of the line o f flig ht. and

inrhe onhogon altpc r pendicula r) sca nning di rect ion. Scientists using therma l ncross-rrack scan ner data us ua lly o nly co ncern the mselves \'. ith the spat ial gro und resolution o f the cel l at nadir, D. If it is neces sary to pe rform precise qua nrirarive work on pixels some ang le Q off- nadir. then it may' be important to remember that the rad iant nux recorded is a n inte gration ofthe rad iant 11u-1l: fru m all the surface mate ria ls in a ground resol ut ion cel l w ith a constantly changing dia meter, Using only the ce ntra l 70 pe rcent of the swat h width reduces the imp ac t o f the large r pixels found at the extre me edges of the swath, Oil l'-J) i nll'lI~ io/1l11 Relief nisp lac(' lJ1cllt : Tru ly vert ical ae rial pho tograp hs ha ve a sing le principal po int directly

beneath the ai rcraft .11 nad ir arr he instan t of exposure. perspective geometry causes all objects that rise above local terrain elevation \0 be d isp laced from their p lanimetric posuion radially ou tward from the prj point (discussed in Chapter (,). For example, the four rcrical tanks in Figure K-14a are eac h 50 It high. The till' d ista nce from the principal po int, the greater the relief dis placement ofthe top of the tank away from iu The rma l infra red images acquired usi ng ,111 -lrnel. sc annmg system.

temper ature characteristics (I f til.' side of these build ings. 1I11""'l' w r. if We wanted to e valua te the thermal chamc tcristics of the rood o r obj ects un rncdiu rcly beh ind the build ings, lhe) are obsc ure d fro m view. Ae rial photography and predawn the rma l infrared imagery o f dowmow n f'\ew York C ity provi de an even g reate r app re-

ciuuon 01" unc-dnne nsioual rel ie f displaceme nt [Figure 8Ill). In this case. the rad ial relief d ispl acement in the aerial photograph makes II di flicul t 10 obta in mfo rmauon abo ut the

I

~

( 'Il..\ I'n:R

268

8

Th ermul Inrrared

Th e rma l Infr ared Remo te Sensing

11I111 ~e

of x ew York

Ci l~

The n

toni c one

hyp< Thi~

non! utili tort

8-1-

pen

rno

Srn gel

e.'\l va

im tic

pe

d

" ct

b. FIgure 8-16

al l'l·r'p.;:'I:!llt' a 1024 x 1024 ele ment s are 00\1. a..-ailable and offer low noise and state-o f-the-a rt sc nsiu vity fur ex treme ly low -bac kg round applications. Star ing array detec tors made of platinu m silicide (Pt:Si ) are a lso popular.

(8-23 ) and h arc co nstants that can be e stim ated from model simulanons ( Bec ke r and Li. 199 5 , 1' 1' co rrel ation wnh !JOUIld observations. Six split- wind ow equatio ns are slim-ued in Ouaidrari et al. ( ~OO2) and in C7aj ko wski cr al :00-;). Coli et al. (201).31 describe land-s urface temperature \' ht.'l'r II

Linear and are a staring arrays allow improved thermal in fmred re mote sensing w ta ke place because t FU R. 20(6 ); the solid-state micro-elec tronic detectors are small er in sile t e.g.• 20 x 20 Jlrn ) and " e ight require less pow er to operate, hav c fe wer mo vin g pa rts, and arc mo re re liab le;

C H,\ I" t:l{

272

Figure 8-19

8

Thermal Infrared Re mo te Sensing

r t erm

A helicopter wnh a lorward· louklll ll mti"otrnl tf LIR) scnsce system IOC3IL-d under lhe nose (coer10:"') H J R :-'y,l.-rn'i.. lncl.

Fig ure 8·20

each detec tor in Ih... a rray can \ k\\ the grou nd resolu tio n d em ent rU T a longer lim... (i.c.• it has a longer dw el l time), allowing more photons oft'nl'r},!Y fro m \\ ithin the IFOV 10 be recorded by the indi vidual dcicc tor, resulting in improved radi om etric resolution Ithc ability to rcsolv ...

'1I/.hl1llll.: thermal mfrarl"d image of a tC'lUrt\.,,~·

f UR

~}sl~rns,ln~ .I ,

array technology. An exumpl... of a FU R system h under the nocc Ill' an ai rcr all is shtw. n in Fig ure }i·ll).

sm at lcr temperature d i ncrences I:

each detector clement in the linear or are a array is fixed relative 10 all other dement.., therefore. the geome try of the thermal infra red image is m uch imp rm ..-J relative 10 an ac ross- truck sca nning sys tem: that prod uced

"y

HIme lmcar an d urea thermal dd.:clllrs 110\\ USI,.' a min iature Sterling clos ed-cyc le co oli ng system that doc s not require the com pres sed gJs-t' ()oling appa ratus (a rgon or Iiquid nitroge n ) previously discussed . Forward -l .lIul;in l:, Infrllrt'd (F I ,I R ) SySh' nJS Du rin g the lW I Gu l f Wur aml till' War in lraq hegi nni ng in 20n4. the public S;l\V day and nig httime .Iiwli'{// yJ-J,m ki llg i" (m ll'd (FUR) nnagc-, o f the te rrain and various ta rgets. Fo r decades. mi l itnry nrganilatio ns th ro ughout the world ha ve funde d the dev elopment o f FU I{-Iy pc sys tems that loo k obliq uely ahead ufth... air craft and acquire high-q uality thc rmal inf rared image/), I::spl'd all) at nig ht. In fact.thei r goa l is usuall y ""10 own the nigh t ' So me H II{ systems collectt he infra red encT!:!) based un thc same prim::ipk s as an aero-istrack sca nner t prc vic usly d isc usscd), except that the mirror po ints / orwa nl about 45° lind projects te rrain energy during if single SWl~P \ 11' the mirror on to a linear arT.IY of thermal infr.:m:d de!l~ltlrs. Some systellls usc staring focal-plane

FUI{ and other thermal infrared sysh:ms arc routinely h~ ltllld IIII

r

8

274

Thermallnlra red Re mo te Se nsill!l

Tl

l3 .().l8 m) AS L. Gcomcrric recuficaucn is performed us ing

onboard (i rs and I ~ S data making rhe collection of gro undcontrol points unnecessary. Characteristics of the [Ires TAB I -3~O arc fmmJ in Table 8-6 [Itres TAB!, 2006 ). The T herm al ..\irhorm.'

S pt'c l rll~ ra phic Ima ~er

Ta ble 8-6.

hrcs. lnc., Thermal Airborne Broadband I (T'\BI -320) and Therma l Air borne Spectr •

Imager (TASI-hOO l characteristics

(T.-\SI I

TABI·320

The: Therma l A sr borne SpeCTrographic 11I1(IKI,,.(1 A 5 1) is one of tho: li N true hypcrsp ..-cua l thermal-infra red remer... sensing sys tems based lin linear array n-c hnology . It collect s data

Spec lral "" n>ili> i~ {I' m

I

in 32 therm al ch anne ls in the region from 1\.0 - 11.5jJm . The pixel sile is 30 x ) 0 urn and the IFOV is 1.15 mRaJ. The lin-

Spatial

rt~>" luli"n

I~ m la t

' ad ir

ear arra y co ntains 600 pixels. TIl": 10131 field of view is 40 ~. The data are quantized to 14-I:>il'O. Characte ristics of the Irres

:'\umh('r of thermal hand>

TASI-SOO 8 - 11.5 Ill!

\ariabk based on the aircraft aI above ground level (AGll

TAS I-ftOO an: summarized in Table X-o (Irrcs lASl. 2(06).

linear am) eCD

Thennallntrared Environ mental Con sideration s

In"

2.l'i mrad

4So

When inlerp r": ling a thermal infrared image , it is usefu l to unde rstand the diurnal cycl e and how it relates to the temperature of objec ts on the Earth's surfa ce.

n..h·( I"~ In

Diurnal Tempe rature Cycle of Typical Materials

RlIdl"llll.'lr k

1.25 mnd

""

320 pixels

t.(l(l plxcl~

SOx50 J.lm

30xJO IlJIl

320

600

12· oil

J4 ·b it

liuur ll rrll~

f{'~"lu t ion

The diurnal cycle encom passes 24 hours . Heg in ning at sunnse. the Earth Ixgin" intercepting mainl y short-wavelength energy (0..1 0.7 1J.1lI) fWIlI the Sun (Figure ~ ·:!2a ) . From dawn to dusk . the terrain intercepts the incoming short wavelength energy und refl ect s much of it back into the atmosphere. where we can usc optical remote sensors to measure the re flected ene rgy, However. some o f the inc ide nt short-wave length ene rgy is absorbed by the terrain a nd ichthyolog ists a rc interested in spatia l di stribut io n of thermal plumes IDd how they relat e to the am bien t river temperatur e. If a ~ume exists. it is im po rta nt to determine where the plu me is ~atl.'T than a specified numbe r of degrees abo ve river ambimt tempera tu re. Depending on the nm c of year. thermal plumes may attract ce rtai n species of a... uatic o rgan isms and mimic othe rs. L'nfo nu nutcly, a hut plume extending across

-.e temperature a nd

the land tsoil a nd vegetano n! to make su re it was confu scd v ith the thermal plume :

not

the am bient river temperature: the spatial di stnhut ion of th e p lume temperature > 2.8cC above rive r nmhicntrcmpc rarurc.

I I

•

8

280

Therrn all ntrared Remote sensing

The

Table 8-8.

Rela tionsh ip of Class to Ambient River Tem pe rature, 12 ' C

f Clas s 1 Dark blue a mbient

Trlm'l'cl "

A

"r

Clas s 4 Yellow

Clan 5 Orange

R. ,

1.2"- 2.B'·C

3.0·- S.O·C

5 .2' - 10'C

10 .2 "- :i!O°C

G_"

Li ght b lu e

. 1"C

J\ n rlt ~l'

W id th

Class 3

Class 2

Class 6

Class7 White ,,20'e

Bril:ht nc ' . \'111 111' H.1tnl:t' fo r t: III'h C I:". l nte r vul

Il l -IN



177-; 5~

I '2.!l

1r.!.8

2/5.6

1':!.11

5/14

38..-

15.6

2/5.6

:J5.6

6116.1I

3/8.01

Ri \lor b

7-1-76

71-4!O

J ll"hcls -

I,··[!"

17f47 .0

25/70

1')/53.2

IN ,6 III

R

3~

C

3-1 I"I\cl , -

pixels '" IObA m

9 5.2 m • F.a.:h .. "n...."el.tnn lnfrared Thermogr aphic Services: Stock ton Infrared: :!/M IOI ,

show n in Figure 1\·) 1h. A preda wn th -rrnal infrared image is show n in Eipun- K-J 1c and a cumjnu -r-aidc d-dcs ign (CAD I map of the extent (If the subsu rface moist ure is shown in r igure K-31d. Th is information is used to csurnarcthc amount Ill" roo f lhal must be replac ed or repaired.

Analysis of rhe Urban Heat Island Effec t

remot e sensing sys tems III document the urban heat i.lllllt ctl ...-cr. In j,\l' nl'r;ll, they foun d that du ring the da yt ime l10lIi commercial land cover ex hibited the highe st tentperamm follow ed by services, transpo rtatio n, and ind ustrial lar.t USl'S. The lowest dayt ime temperatur es were found 01'4 wa ter bodie s. vegetation, and agric ultu ra l la nd usc, in l"order. Rcsldcminl hou sin g being com pose d of a hetcregeneous m ixture of buildings. g rass. and tree co ver e.\hibit()- 111,2 '1111 1 image of Atlanta, (i A Prominent urban fcaurres arc annota ted for o rientat ion. h f :"i i~hllHTl('. predawn rhcrrnalrnfrarcd image of Atlanla. GA (coe ncsy U Quallrochi and J . l.uvall. Pm /,':., /'rtx:,'HUl1:. .f 3rd Ed. , Upper Saddle Rive r:

Prmticc-Hall. 525 fl.

· J. R.• Ludcrs. J, K.. Schill . S. R. and

C~

T. Raber, 2004.

'1dmtifying Riverin e Sand and GraH·1 I kl'O, i l ~ L:~ ing A f1i,h Resolution Day-nighl Temper-nun: Difference Map a nd !>Igll il~d Ae ria l Photography," Ct·"..·"" o Intt·m,m"",,'.

191 2/: 49-5n. E.. C hriste nsen . r.. J•• Macke y, II f... TInlIr). L. R. and R. SharilT. l sessm..nt for tht' AVIIRR, Land f'al h lindo:r II lJata Sel. - R,,·mul.· S,'''' IIIX Hf E" "" lm m..'III, loll : I I" - 12l!.

Pctitcohn. F ant! E. \" 'f1I HlI C. 2002. "land Surface Rdk ,·lanc c. Emls. h ily .. nd Ternrcr..luTl.' fro m ' lO OIS \1 ,d dll' and The rmJ l Infrared." Reml>l,''k-nJ~'Cts.

The former Soviet Union launched the r\ LMAZ· ] Scband ('J.6 em ) radar in 199 \, The European Space Age ncy ( ESA )

launched tho: Enroprun Remote 5('/l.I'i l/l: Satcltite ERS·! with us Ccbnnd (5.6 em) imag ing rad ar in 1')9 ] lind ERS-] in 1995. The [SA launched Env isar on Murch I , 2U{)2 with its Ccband (5,3 cmt A"WII/Ct' J SyllthCfiC Aperture Radar (AS A R ) to prov ide contin uity with the I:"RS-/.2 radars. Japan la unched the Lcbund (23.5 Col) Japall!',\"(' 10"(//"111 R £',I'VIIIH 'S .'la rd/if. The tran smuted pul-e e lectromagnetic energy inte rac ts with the terr ain and >OOl. of it is bac kscancred at the speed o f light towa rd the eire or spacecraft. \\ here it OIKe again must pass throug h a fill: If the antenna accepts the backscauered ene'¥). it recorded V:Ui.1US Iype s of bac ksca ue rcd p...lari zcd Illy huriw lltally Iwlar izcd

R gu re 9-7

l i ~ hl

lu pas,.

a) A vertically polarized filter placed in front 01" a cam...ra le ns a llow, unly vertically polarized light 10 pass through. bl A h"ri UlII la lly polarized filler allows only horiz ontally f':

1>7-

c.

b.

rr>;

/I

+4

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f\Z\T4 rs:zv---------1 I 1- - 1 1- 'I

7

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Figure 9· 17

(1.5

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7

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7

c.

;\ long antenna (;,111 tc synthesized l1y a ~h "rt all(CI1 11;1(c.g.• I In long) by taking advanl ;1 l;Wof lhe earn" idth

Figure 9 · 19

,\ syn tbetic ant ..'nlla ntlength t. is produced by llp1ica ll~ llr ,jig itally pr'h;cs~ i n g the phase tnstortcs ot'microwa vc l1loJatfdtni se nt aml rccci \ c5,"','(

A

h-.- .

{tI-2JI

4,4sm y

itutmg the same wavelengt h and depression angle into equation yields:

"

." se ,d

h»

3cm ~.4 x O. 70 7 11

(.

yl

II > 0.96 em .

,-

ca se the only para meter changed was the wavelength . If we c hanged both the wavelength a nd the dep ressitln angle (0 be lhat o f the Scasat SAR [Table Q•.4J. we see that the snrne 0 .5 em local re liefw ould produce a smooth (da r"') ret urn inthis l-band imagery. T he slgniflcancc o f this rel at io nship is that rh.. same terra in w ill appea r diffe rcruly in rada r image ry as a fu nctio n (\1' the sensor's depr css jon angle a nd wuvcjcngth (H enderson and Xia. 1998 ). Therefo re, it is diffic ult to create "radar imago: interpretat ion keys" o f selected phenomena. An analyst mu st co nstantly keep Ih i ~ in m ind" hen interpreting rada r imagery. Late r we will !>e-e tha t air cra ft. or spacecra ft look dire ction ab o impacts the bac ksca uc rcd energy. \il ikhai l CI al. 120011 suggest that the follow ing criteria can a lso he used 10 predic t whether a surface will yield a weak , intermediate. or strong radar rerum: A surface wi ll produce a relatively wea k return if its local relie f is less than one- eight the incident radar waveleng th. In this case much of the incident microwave energy is scattered or spcc ula rly reflect..-d a ll ay from the antenna resulting in a we ak return .

An inte rme dia te return i\ produced w hen thc' loc al rel ief ranges from on e-eight to one-hal f the inci dent radar w it \ cfength. These d iffuse reflectors disperse energy at 0.96 em ( Figure q·1OcI . then llJOng retu rn from the terra in wou ld he expected and oold lie recorded as a bright lone in the radar imag e.

eallcl fromthe ground. and (I ·Jis the dou ble-bounce ~ (cring berweeu th", tree trunks dud ground(ad.JJ'4ed from Ka , i, .:hle aud B(lu rgcuu -C1HI\'CJ~ 1997)

face Toug lllles,). 2 ) the wa ve length and poluri zanon of fir inc ident mic rowav e e nel)!Y. J ) the diel ectr ic co nstant of \hl: vcgc tnnou. and 4) the dielectric co nsta nt o f t he ground sur· face. The , c a lt e rin g and a tte n ua tio n in the eq ua tions an::111 dir ectly propor tional to the die lec tric constant. L ive VCj;l1!' tion . w ith a highe r wate r content ( tu rg id ity ) has a higher dielectric constant Ihan drie r or d ead vege tation . The presence of dew or moistu re acts 10 increase the d ie lectric constunt o f vegetated surfaces I Kcs isch kc an d Hou ~'I.'au­ Chav ez. 1997), O n eil, the prima ry q uantity governing the uncuumion coe fficient o f a vegetation cuno py is the wne content pl'r un it vo lume. not necessarily the act ua l scuctee and gel'lIletry (If the leaves. sie ms. and trunk o r the planIs. The co nduion of the grou nd laye r is also ve ry important il microwave scattering fro m vegetation surfaces. There art IWI) properties of'rhis layer that arc important. includin g: II the micro- and mesoscale surface ro ughn es s [relative 10 the radar .... avelcngth pre\ iotlsly d i-..:usS('J ), 311\1 2) th.: reneelio n cod liciellt. In ge nera l. a grcalcr surfact: roughn~s I)

319

leAR Environmental Co ns iderat io n s

' 'I' y

py

h)

"er

'r -

"s

,.

er

d

• ses the amo unt of micro .... uvc energy backsc ancrcd asing 0 °,). and 2) decrea se.. the amo unt of energy scatin the forwa rd d irection (dec reasing 0 °.. and o "J). T he ion coef ficie nt is dependent on the die lectric co nsta nt conductivity] o fthe gro und layer, A d ry gro un d layer has ~"" dielec tric co nstant and there fore has 3 low reflec t ion ffic icnt. A ~ soi l moist ure inc rea ses. SoU doc s the diel ec tric t and . hence . the rc tlccnon coefficient. Given a co nsurface roughness. as the soil dielectric cons tant s. so dUL~ bot h tho: amou nt of backscaucrc d and forscattered micro.... ave energy (resulting in increases in ..0',. and o OJ) eerc is a laye r of wa ter over the grou nd su rface of a vcglandscape ... uch a.. in wetl and environments, t.... o •s happen: I) it c1 iminaIL~ any sur face roughness, and :!) signilit"antly increases the reflectio n coetfcieru. In terms microwave sca tteri ng, the elimination of a ny surface ~n~~ means tllut all the energy is forward scattered, if\31ing the surface backscnttering term (0 ',) in the eq ua: and. the increased forwa rd sca ue nng an d higher ion coctficicm lead to sign ilicunt increases in the !lUUnd-lrunk and grou nd-ca nopy interaction tenus 0 °,J and ~J'l'rect i\"C ly IKasischke and Bourgeau-Chavcc; 1997 J. Proetra t inn Depth a nd h Nlu rn Q ' The: longe r tho: micro .... a ve wav ele ngt h. the greater the pc ncnlion into the planl ca nopy ( ESA A SA R. 201Io ). For examFigure 1)-23 \kpicts the respnnse or a hy pothetical pine ~t to m icro wave energy, Surface scattering takes place at lbe lOp of the canopy as the ene rgy interacts with the leave s or needles ! and sterns . Volume scuttenug by the lea ves. serus. branches. and tru nk takes place thmughoutIhc stand. Il1d surface scattering can occur aga in at the soi l surface. A e mpans on (If the respo nse o f X-. C-. and Lban d microsave energy incid ent to the same ca no py is presented in fi glIIe 9-24a - c. Th e sho rter wave length X-band (3 em ) energy s anenuuted most hy su rface scatter ing at the top ofthe cancpy by foliage anti sou l! branc hes. T he Ccband (5,1\ em] energy experiences surface scatte ring at t he top (If the ca ncpy as we ll as some volu me scattering in the heart o f the 5UJld, Liule energy reac hes the ground. Lcband (23 .5 cm) ecrowavc energy pcnctrates farther into rh... ca nopy. where \tIlume sca neriug among the leaves. sterns. branc hes. and eank cause thc bea m to becom e depolarized. A lso. nu mcrCllS pulses may be transm ute d to the groun d. where surface sancring fro m the soil-vegetation boundary layer may ta ke place. Lon ger P-bund radar lllo t shown) wo uld alTord the greatest pcn~...ration thro ugh the vegetation and ma in ly

*.

\ surface scancrmg from lhe lop of lheeallOJ'y

surface and volume scattering from the ground

Figore 9-23 The types of ..(l ive microwave surface and volume scauenng thai might loIle place in a hypothetical pine fores t stand (after Carver. I QIl !l ).

re flect off large ste ms and the soi l surface (Waring cr al..

19951.

Radar bac kscatt er incre ases ap proximately linearly w ith increasing biomass unti l it saturates at a bio mass leve l that dep ends on the radar freq uency, Fo r exam ple. Do bson et al. ( 1992 ) found that the biomass satura tion le\ cl wns about 200 tons/ha ofl.ohlnlly pine usin g Pvband and 100 tons /ha for Lban d. anti tha t tho: Ccba ud backscuue ring coefficie nt showed mu ch less sens itivity to to ta l abov eground biomass. Wa ng et al. (141)41 evaluated Loblolly pine usi ng EH. S- l SAl{ backscatt er data. They a lso fou nd tha t tho: Ccbund func tioned poo rly d ue to its high sensitivity to so il mo isture and the steep local incide nt ;mgle o r the sensor (23 °). Gene rally. backscatter 31 lowe r frequen cies (P - and Lba nds) is do minated by scatto:ring processes involving the maj or woody l'Iiomass co mponents t tn mks and branches], while scat tering at high freq uencie s (C- a nd X-band s) is dominated by scarIcring procc'fos~"S in the top crown lay ("rof I1ran ches and toliage . Radar canopy meas ure men ts have also bnicall y oriented C;lII" PY com pouem, (lct ·IX·SA R imap e of the I.O$A~ basin uhlain..-..J on Octo ber 3. I 'N~. The 1000k dirlt non is fmm thcztop to the bottom of lhe image-Icc. l..~) I\ AS..\ Jcr Propulsion La boraro ryj.

A S IR·C/X-SA R ima ge of'Lo s Angclcs, CA , is found i n r~. lire 11-2(, It ha, ap prox imately J(J x 30 m resolution. TIr rad ar look d ire..' lio n is from the w p tp'"(:if~ ing a beam position. one of scwlllOO 100 km images wi th in a 500 km accessible swath 'oI-iD Ire co llec ted. Factors influencing the choice of beam incl ude the sensitivity of the application to incident ang.'t. type o f terrain , stereo req uirements. spat ial resoluti.:J desired. and how often co ve rage of the area is required. RADA RSAT's (lm it ha s a 2-1. day cycle. meaning it Tel'Jr:III to the same loca tion every 2-1 d ays . Ilo.... ever. it caD poin ted to provide a mo re freq uent revis u cycle. The ~ also has the op tion o f collecting imagery based on two dlitcrent look directions . As RA DA RSAT descends from IX Nenh Po le (a descending or bita l pass ). it views the Eanha a westerly direction . As it asce nds from the South Pole I. ascen d 109 orbital pass ) it views the Earth in an easlelt! direction , This ca n be .... cry useful when wor king in ara; w ith high relief, when we arc interested in high lighting: fer tures with a parti cula r orien tatio n. and/or when the stud)req uires imagery acq uired in the early mo rnin g or earlj evening . RAD ,\RSAT-2 ls to he bunched in 2006 or 2007 (MD,-\, 200(,n). It is has ma ny speci fications that are identical t~ ]{,\[)ARSAT. how ev er. the re .and alli..\ SA JPL I'N( 13 (115.5 GIIz )

74 )( 4 3 (6. '1 GHl ) 14 )( II (36.5 Gill) 6)( 4

"cold" to a passive microwave radiometer. Fortunat ely, rain dro ps appear 10 have a temperature that eq ua ls the ir real ternperature and appear "w arm" or bright to a passive microwave rad iometer. Th e mo re ra indrops. the wa nner the wh ole scen e appears . Research over the last three decades has made it possible to obtain relatively accurate ra infa ll rates based on the temperatu re o f the passive mic rowave scene . Land is very d ifferent from oceans in that it emits about 90 pe rce nt o f its real temperat ure al microwave freq uencies . Thi s red uces the con tra st Ixtv. ee n the rain droplets and the land. Fort unat ely. high - frequ ency microwaves (R5.5 Gllz) are stro ng ly scaucrc d by ice pres ent in many m ining clouds. Th is redu ces the m icro wave signal of the min at the satellite and provides a con trast with the wann land bac kgrou nd. allow ing accu rate rain fall rates 10 be co mputed over land as wel l. A n example o f ra infall measu reme nt using the TR ~1 \1 Mic rowa ve Imager is presented in Chapter 12 : Remote Sens ing of Water.

The Adv anced M icrowave Scanning Radiomete r (A M5 R-E) is one o f s ix sensors onhoard AqulI (NASA AMS R-E, 2006), A MS R-E is a coopenuive e ffo rt betw een NASA and the Nationa l Space De velo pment Ag ency o f Japan. A MSR-E was mod ified fo r II 'II/(j based Oil the design o f A MSR nn the Jap anese A/) f:( ),)-] sarellue. AM S R-E is fl own in a pol ar. Sun-sy nchrono us orbi t. II is a six freq uency pass iv.: microwa ve radiometer that me asure s frequencies at 6.925 . 10.65. 18.7. 23 .8.36.5. a nd 89 ( IIV po larizatio n ). II has a mean spat ia l reso lution ufSA km at X9 G Hz and 5l PUI! J;lIlIl USUCJ I

:JO J:lU;>fu .;> \I P UJ C""ll~C [ 1I! .l!d ,(" C ' l a V

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'llI.iU C IV ·U!f:.U:l1 reu JOJ W

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= "'~'(/d

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l»\m UCI..UI eqr j o J;ll;lLU C!p " 1.1.1 ·(tl b66 1 -..r.! \~l l rH) p,;IJ:J1 '~UJ ,';q d r.J:l ot:!o l :'1 111 pur. J It!Ul1 1I11;)S :> ljl 1/11.\\ ~:>!J I!,\ PUI! l"Il(l.l~ aqtuo JI!llI,' JIJ ,(I;)U,IUIXOJUUI: S! /ll,1./(!JOU./-I,) ,W/ JI ll.

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posn UOO'> ,JJ.:o 1\\ S\U;lWIll ISU! J,"'Cl

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IIII ~ ' x f l l ll:i ll.l 0 p,,;xl ~ :JIll '.) Ir. ~F' '' I!JI IljSl 1 .I:l" PI J(l V ·,uu. mh,vf U"-III I,I(/.U .J·9IlJ ~ r 0 1 P.)JJJ.I.).I U:ltl " ·J.)S

- UlIU'iiOIOlj,1 '.(4d llJ tI"' IOl ld ICU:>C .}!dO:.lso:>J:lIS LUOJ.I ,(11.xlJ lp P:>j:JCJIX.J :>Jr sppOW U(1 IIr.,, :>p Il!Illl lp 'I\Otl P""J'IJRIUWn S

O$jOO (J(M)"OO I < S.' 11!J Ir. l.-\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

,,, -50"0

raJ idHl RJ ~

~

5 l\ 4>, - (,2,5% Transmirtcd radkun 111,1 ,\ . !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. 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

1._+..... . .._.1

«)

Relativ e wate r content

or \faw w li'l 1ing 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.~~'0°) • Spectra l SeTlsilh-ity O. l ' IFO V (m ilhr.l 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.:- 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~

IIcaI,,~ ... 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.op 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

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:'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 11lge 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.

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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).

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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 \

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/'Icpcnd 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

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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.

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

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Figure 12-5

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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 " a1trie 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

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l )(}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. 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):

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"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(lmPOT 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~' S1 ) :4. A. S i cg ~· 1. 200 5. "C o nsis tent Me rg ing (If Satellite Oc ean Color I>ata Sds Usin tj A Hie -optical Model : ' R~mol" S"IH iIiX or EIIl'm m""' /It. 'J4 :-ll'J·-4 4ll. !I1ark h ~ IJ1 , It l.. and

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: u

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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 eOIsifi. 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 C1 . k> ' ....... l abloo F..:,bl"'"

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1>21: ~~'I« 11:~ 11"' ..e m!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

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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! seal

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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

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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 ( IlOj,.'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 phtltugrh 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:. 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 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. ("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 frIlR.'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!. 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'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

501

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

C HAI'r ER

13

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.

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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

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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

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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; =

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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 .

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c . Very thin 0 horizon OWl subsotl and weathered bedroc k,

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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 - 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 : ha w been fo und in ueSl;' n s throughout the world Jnd play an im porta nt role in desen ,;',;'osyslems in soil form.ati(lI1. sta hi lity and tC ni lity an d pre:","nt so il .:rosio n (Bdnap. 200J ). The speclral re l1eetan..:c e harac ter islics lJf thrce types of hiologic:lI soil emst :lrt' shown in Figure 14+1ll.

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..

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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_

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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 li'lU "f U .S. (ico]"gic;.tl Surv11 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.

;\~\\

Z t'a la nd

'. ~J:",()lI(

'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 lt!r1 Ecosys tem Progr am and Space lm apin g, lnc.). Taklima k .. n lllu\bd hill i n X i nJ ill nf;: Prev i nu'. Ch in ll

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 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 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

. 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 OVtTeldlfO-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~IJlils 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 [(:-.. 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 C'lJX·n syste ms and neu ral nd\l.urb . 'J gcmelric coerecnoe. 26 hypcrspecua ! data ana lysi s. 'J, 27 mdchtlg. '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>isastwgr" 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>Ossufpl 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 phv1-4U 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 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 instrum ents . 7 logic. ~ milestones in. I) (Table 1- I) process. 11 - temporal. 17-111 statement of the pr" hlcm. lI

Ik prl_m.u i\ c traction. 155-160 Residen tialland use. mllTjl rCI--4M Cnt:T~Y ..Icmand ami conscrv unon, 4tH single- an d muhi-tam ily, 45f>--4 SX Rock s and min,-rals, remote sensi ng of. 5 111 -52\ imag ing spectroscopy, 51 X- 52 I

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,'din1rthoimal!-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~ lk spec trum. 4 .~" Socioecononnc lIlfnnn8l iol1. -161----4M

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 grtt-- 16lS anllglyphic or polari zmg gla sses. 164 cruocd-cycs. 1(,5 parallel-ey es, 165 us ing a SIC IC;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 canopy model ing or. 371-372 chang .. detection of 3\l7--WO nn aging sf"l'Ctrumctry 0 1: 372 -373 inu lC"':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.. Spa\r llM n~ lIIl lluolu ",1.l r"" rl'rmb. l'I street centerline l>l l'he l~alU r~'S e \ lrdekd are J r"pla yed ill 111pa 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~'. 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 :\mcnSt"Tl{,,'i.C...-d Swec lgum leaf thai "a~ on the gTO\ll1d. Speceruradrometer pe rce nt re flec tance mCd"un:rncl1l" ove r ttll: wavelength inl &. F....-e""l1- 10 inh-ntUf} the ill;Jild-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 Sit: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'''1_

;\,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.m/null·urhan landco vcr Berkeley. Dorc heste r. and C h;u ksh lll ,uunlks cente red Oil Charlceron. SC Jsi, 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>.