温度反演经典文章(10)

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

withazenithalanglefrom0°to21.6°,andtheotheristheforwardviewwithazenithalanglefrom52°to55°.AssumingthattheLSTandSSTareindependentontheVZAandthattheatmosphereishorizontallyuni-formandstableovertheobservationtime,Prata(1993,1994a)derivedadual-anglemethodtoretrievetheSSTandtheLSTfromATSRdata.Sobrinoetal.(1996)laterproposedanimproveddual-anglealgorithmthatincorporatestheemissivityεnatnadirandtheemissivityεfatfor-wardview:

LST¼T

nþp1Tn Tfþp2þp3ð1 εnÞþp4εn εf;

ð17Þ

wherepk(k=1–4)arecoef cientsrelatedtotheatmospherictransmit-tancesandmeanairequivalenttemperaturesinthenadirandforwardviews;TnandTfarethebrightnesstemperaturesmeasuredinthenadirandforwardviews,respectively.ThisalgorithmincludesonlyemissivitydependenceandhasnoexplicitWVdependence.Anon-lineardual-anglealgorithmhasbeendevelopedbySobrinoetal.(2004c)toreducethein uenceofatmosphericWVontheLSTretrieval:LST¼Tnþq

2

1Tn Tfþq2Tn Tf

þðq3þq4WVÞð1 εnÞ

þðq5þq6WVÞΔεþq0;

ð18Þ

whereqk(k=0–6)ingsimulatedTIRdata,SobrinoandJiménez-Muñoz(2005)comparedtheLSTsretrievedusingthedual-anglealgorithmgiveninEq.(18)andthenon-linearSWalgorithmincorporatingLSEs,WV,andVZAdescribedin3.1.2.2.Theresultsshowedthatthedual-anglealgorithmissuperiortotheSWalgorithmprovidedthatthespectralandangularvariationsoftheLSEsarewellknown.

However,itshouldbenotedthatalthoughthemulti-angle(dual-angle)algorithmprovidesbetterresultsthantheSWalgorithm,thedual-anglealgorithmhasseveralpracticaldif cultieswhenappliedtosatellitedata(Sobrino&Jiménez-Muñoz,2005).Acriticalphenome-noninthemulti-anglemethodistheangulardependenceoftheemis-sivity,astheangularbehaviorofnaturalsurfacessuchassoilsandrocksisnotwellknownatthescalesofsatellite'sspatialresolution(Sobrino&Cuenca,1999).TheangulardependenceoftheLSTisalsoanissue.Inadditiontotherequirementthattheatmosphereisfreeofcloudsandhorizontallyuniform,themulti-angularmeasurementsmusthavesigni cantdifferenceinslantpath-lengths.Otherwise,themeasurementswillbehighlycorrelated,andthealgorithmwillbeun-stableandextremelysensitivetomeasurementnoise(Prata,1993,1994a).Furthermore,“thesame”objectobservedatdifferentviewinganglescancoverdifferentsensorareas(intermsofpixels).Eventhoughthesamepixelsizemaybeobtained,anobjectobservedatdifferentobservationanglesmayalsoappeartotallydifferentbecauseofthethree-dimensionalstructureoftheobject.Finally,mis-registrationofpixelsunderdifferentviewinganglescanresultindrasticerrorsintheLSTretrievalresults.Consequently,multi-anglemethodscanonlybeappliedtohomogeneousareas(forexample,thesurfaceoftheseaordenselyvegetatedforest)inidealatmosphericconditionsbutnottoheterogeneousareas.

3.2.LSTretrievalwithunknownLSEs

AllofthemethodsmentionedaboveestimatetheLSTbyassumingthattheLSEisknown.Inpractice,theheterogeneityofthesurfaceandtheangularandspectralvariationoftheLSE(Lietal.,2013)makeitchallengingtoexactlydeterminetheLSEatthesatellitepixelscaleinadvance.Theemissivityofland,unlikethatofoceans,candiffersigni cantlyfromunityandcanvarywithvegetation,sur-facemoisture,roughness,andviewingangle(Salisbury&D'Aria,1992).Therefore,theLSEsmeasuredinthelaboratorycannotbearbi-trarilyusedatthepixelscale.Generally,anuncertaintyof1%inthe

LSEwillresultinabout0.5KerrorsintheLSTundernormalcondi-tions.Toensurethetargetof1KaccuracyinLSTretrieval,methodstoestimatetheLSEfromspacemustalsobedeveloped.Todate,thereareatleastthreedistinctmethodstoestimatetheLSTfromspacewhentheLSEisnotknown.The rstisastepwiseretrievalmethodthatdeterminestheLSEandtheLSTseparately.TheLSEises-timated rst,andthentheLSTisretrieved.Thesecondisasimulta-neousretrievalmethodthattreatsboththeLSTandtheLSEasunknownsandresolvesbothofthemfromtheatmosphericallycorrectedradiancesorwithapproximatedatmosphericpro les.Thethirdisafurtherdevelopmentofthesimultaneousretrievalmethodthatsimultaneouslyretrievestheatmosphericpro les(oratmo-sphericquantitiesintheRTE)withtheLSTandLSE.

3.2.1.Stepwiseretrievalmethods

ThistypeofmethodretrievestheLSTusingtwoconsecutivesteps.First,theLSEis(semi-)empiricallydeterminedfromvisible/near-infrared(VNIR)measurementsorphysicallyestimatedfrompairsofatmosphericallycorrectedMIRandTIRradiancesatgroundlevel.Then,theLSTisestimatedusinganyofthesingle,multi-channel(SW)ormulti-angle(dual-angle)retrievalmethodsde-scribedinSection3.1.Representativestepwisemethodsincludetheclassi cation-basedemissivitymethod(Peres&DaCamara,2005;Snyderetal.,1998;Sun&Pinker,2003),thenormalizeddifferencevegetationindex(NDVI)-basedemissivitymethod(Sobrino&Raissouni,2000;Valor&Caselles,1996;VandeGriend&Owe,1993),andthetemperature-independentspectral-indicesmethod(Becker&Li,1990a;Li&Becker,1993;Lietal.,2000).AsidefromthepreviouslydiscussedadvantagesanddisadvantagesoftheLSTre-trievalmethodswithknownLSEs,stepwiseretrievalmethodspresentspeci ccharacteristicsthatwillbebrie ypresentedinthefollowingsections.

3.2.1.1.Classi cation-basedemissivitymethod(CBEM).Thismethodas-sumesthatsimilarlyclassi edlandcoversexhibitedverysimilarLSEs.TheLSEcanbeassignedfromlook-uptablesbasedonconventionallandcoverclassi cationinformation.Snyderetal.(1998)reportedthattheLSEvaluesof70%oflandcovercanbeestimatedwithinsuf cientaccuracy(about0.01)usingthismethodbyconsideringseasonalanddynamicstatechanges,thusmeetingthegoalof1Kac-curacyofLSTretrieval,intheory.

Generally,theCBEMisthesimplestmethodintermsofprocess-ing,anditcanprovideaccurateLSEsforLSTretrievalaslongasthelandsurfacesareaccuratelyclassi edandeachclasshaswell-knownLSEs(Gillespieetal.,1996).Evenfordataatcoarseresolu-tions,suchasgeostationarysatellitedata,theCBEMcanbeapplicableusingalinearmixingmodel(Peres&DaCamara,2005;Sun& …… 此处隐藏：4627字，全部文档内容请下载后查看。喜欢就下载吧 ……