温度反演经典文章(11)

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Z.-L.Lietal./RemoteSensingofEnvironment131(2013)14–37

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12μmformostterritorialsurfaces.Otherwise,alargeretrievalerrormaybecausedbyvariationsintheemissivity.Alloftheseuncer-taintiesmaypreventanaccurateestimationoftheLSEfromCBEM,thusdegradingtheaccuracyofLSTretrieval.

3.2.1.2.NDVI-basedemissivitymethod(NBEM).ThismethodisbasedonastatisticalrelationshipbetweentheNDVIderivedfromtheVNIRbandsandtheLSEintheTIRchannels.VandeGriendandOwe(1993) rstfoundaveryhighcorrelationbetweentheLSEintheTIRchannelscovering8–14μmandthelogarithmicNDVI.Subse-quently,ValorandCaselles(1996)appliedthismethodtoestimatetheeffectiveLSEofaroughrow-distributedsystem.StartingfromthemethodproposedbyValorandCaselles(1996),SobrinoandRaissouni(2000)reducedthecomplexityandformulatedanopera-tionalNDVIthresholdmethodtoderivetheLSEfromspace.Thismethodassumesthat:1)thesurfaceisonlycomposedofsoilandveg-etation;2)theemissivityofthebaresoilcanbelinearlyrepresentedbythesurfacere ectivityintheredchannel;3)theLSEchangeslin-earlywithrespecttothefractionofvegetationinapixel.Therefore,theLSEofTIRchannelicanbeestimatedusingthreelinearfunctionscorrespondingtoconditionsinwhichapixeliscomposedoffullveg-etation,offullsoilorofmixedsoil/vegetationcontent.

Becauseofitssimplicity,thismethodhasalreadybeenappliedtovarioussensorswithaccesstoVNIRdata(Momeni&Saradjian,2007;Sobrino&Raissouni,2000;Sobrinoetal.,2002,2004b,2008,2003).SimilartotheCBEM,anaccurateatmosphericcorrectionisun-necessary.However,theNDVIthresholdsthatindicatebaresoilandfullvegetationcover,thevegetationfraction,anycavityeffects,andtheLSEsforbaresoilandfullvegetationmustbeknowninadvance.SinceNDVIisusedasaproxyforthefractionofvegetatedsurfacewithinthepixel,itcanbereplacedbymoreaccurateestimatesofthisvariable(e.g.,Trigoetal.,2008b).Nevertheless,oneofthedrawbacksofthismethodisthelackofcontinuityintheLSEvaluesofregionstransitioningfromsoil-typetovegetation-type,becausetheLSEsinthoseregionsarecalculatedusingdifferentformulae(Sobrinoetal.,2008).Usingnumericalanalysis,Sobrinoetal.(2008)foundthatthismethodcanonlyprovideacceptableresultsinthe10–12μminterval,becausetheNDVI-LSErelationshipforbaresoilsamplesdoesnotprovidesatisfactoryresultsbeyondthesespectralintervals.Inaddition,thisrelationshipmayholdforsoilandvegetationmixingareas,butsurfaceslikewater,ice,snowandrocksmustbetreatedseparately(Sobrinoetal.,2008).Becauseitrequiresaprioriknowledgeoftheemissivitiesofsoilandvegetation(Sobrino&Raissouni,2000),thedeterminationofthesoilemissivitymaybetheprimarysourceoferrorinthismethod(Jiménez-Muñozetal.,2006).

3.2.1.3.Day/nighttemperature-independentspectral-indices(TISI)basedmethod.BeckerandLi(1990a),andLiandBecker(1990) rstproposedaTISI-basedmethodtoperformspectralanalysisintheTIRregion.Subsequently,assumingthattheTISIij(iistheMIRchan-nelandjistheTIRchannel)inthedaytimewithoutthecontributionofsolarilluminationisthesameastheTISIijinthenight-time,LiandBecker(1993)andLietal.(2000)furtherdevelopedaday/nightTISI-basedmethodto rstextractthebidirectionalre ectivityinMIRchannelibyeliminatingtheemittedradianceduringthedayinthischannelbycomparingtheTISIijinthedaytimeandthenighttime.Oncethebidirectionalre ectivityinanMIRchannelisretrieved,thedirectionalemissivityinthatMIRchannelcanbeestimatedtobecomplementarytothehemispheric-directionalre ectivity,whichcanbeestimatedfromabidirectionalre ectivitydataseriesusingeitheranangularformfactor(Lietal.,2000),asemi-empiricalphe-nomenologicalmodel(Petitcolinetal.,2002)orakernel-drivenbidi-rectionalre ectivitymodel(Jacobetal.,2004;Jiang&Li,2008a;Lucht&Roujean,2000;Roujeanetal.,1992;Wanneretal.,1995).Finally,basedontheconceptoftheTISI,theLSEsintheTIRchannelscanbe

obtainedfromthetwo-channelTISIandtheemissivityintheMIRchannel(Jiangetal.,2006;Lietal.,2000).OncetheLSEsareknown,theLSTcanberetrievedusingthemethodsdescribedinSection3.1.

Becausethesingle-channelmethodissensitivetouncertaintiesintheatmosphericcorrections,themulti-channel(SW)LSTretrievalmethodsarerecommendediftheLSEsareestimatedusingtheday/nightTISImethod.LiandBecker(1993)indicatedthattheuseofanapproximate(standard)atmosphereinsteadofanactualatmosphereleadsto3%orsmallererrorsintheLSEand0.5KintheLSTusingtheSWalgorithms.

Becauseofitsphysicalbasis,theday/nightTISIbasedmethoddoesnotrequireanyaprioriinformationaboutthesurfaceandcanbeap-pliedtoanysurface,eventhosewithstrongspectraldynamics.General-ly,thetime-invariantLSEassumptionappearstobereasonableinmostsituations.TheLSEswillremainunchangedoverseveraldaysunlessrainand/orsnowoccur.Itisworthnotingthatnighttimedewformationmayaffecttheassumption,especiallyforlow-emissivitysurfacesindryareas(Snyderetal.,1998).Althoughthefrequencyofdewoccurrenceisnotsohighinmostsemi-aridandaridregions,itisworthtotrycheckingtherelativehumidityvalueinthelowboundarylayertoavoidheavydeweventsbecomingaseriousproblem(Wan,1999).Therefore,thismethodissuperiortothe(semi-)empiricalstepwisere-trievalmethodsabove,especiallyonbareandgeologicsubstratesthatexhibitcontrastemissivities.

However,severalrequirementsmaylimittheusageofthisalgo-rithminLSTretrievalfromspace.Firstofall,approximateatmospher-iccorrectionsandconcurrenceofbothMIRandTIRdataarerequired(Sobrino&Raissouni,2000).Then,accurateimageco-registrationmustbeperformed(Dashetal.,2005).Additionally,thesurfacesmustbeobservedundersimilarobservationconditions,e.g.,viewingangle,duringbothdayandnight(Dashetal.,2005).

3.2.2.SimultaneousLSTandLSEretrievalmethodswithknownatmosphericinformation

BecausetheaccuracyoftheretrievedLSTisprimarilydependentontheaccuracyoftheLSE,simultaneousdeterminationoftheLSEandtheLSThasbeenproposedtoimprovetheretrievalaccuracy.Manysimulta-neousLSTandLSEretrievalmethodswithgivenknownatmosphericin-formationhavebeendevelopedsincethe1990s.Thesemethodscanberoughlygroupedintotwocategories:themulti-temporalandmulti(hyper)-spectralretrievalmethods.Themulti-temporalretrievalmethodsprimarilymakeuseofmeasurem …… 此处隐藏：5159字，全部文档内容请下载后查看。喜欢就下载吧 ……