温度反演经典文章(17)

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

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TheoptimalmethodtoretrievetheLSTfromspaceinpracticecanbese-lectedbyconsideringthecharacteristicsofthesensor,theavailabilityofemissivitydataandatmosphericinformation,thecomplexityofthemethod,andotherconsiderations.

BecausetheSWalgorithmsaresimple,effectiveandgenerallysuitableformostsensors,manycomparativestudiesevaluatingtheperformanceofthesemethodshavebeencarriedout.Vazquezetal.(1997)foundthatmostSWalgorithmsarestatisticallyindistinguish-able.Kerretal.(2000)performedanalgorithmcomparisonandcon-cludedthattheselectionofthebestLSTalgorithmmaydependonaprioriknowledgeofthewatervaporcontentandtheLSE.SòriaandSobrino(2007)reportedthattheRMSEofretrievedLSTinSWalgo-rithmsgenerallydecreasesasmoreinputsparametersareexplicitlyincluded.Howevermoreinputsparameterswillintroducemoreun-certaintiesanddecreasetheaccuracyoftheLSTretrieval.Yuetal.(2008)haveevaluatedninepublishedSWalgorithmstodeterminewhicharemostcapableofgeneratingaconsistentLSTclimatedatarecordacrosssatellitesensorsandplatforms.TheresultsshowedthattheSWalgorithmsthatdependonboththemeanandthediffer-enceofchannelemissivitiesarethemostaccurateandstableoverawiderangeofconditionsiftheemissivitiesareaccuratelyknown.However,Yuetal.(2009)reportedthattheuseofboththemeanandthedifferenceofchannelemissivitiesmaybetoosensitivetotheemissivityuncertaintyandshouldnotbeusedinoperationalpractice.Asacompromise,theSWalgorithmsthatonlyusethemeanemissivitiesarerecommendedbyYuetal.(2009).

BecausealloftheassumptionsandrestrictionsinvolvedintheLSTretrievalmethods,suchastherequirednumberofTIRchannelsandtheknowledgeregardingemissivitiesoratmosphericquantities,can-notbemetsimultaneously,comparisonsareseldommadeexceptforSWalgorithms.Toprovideaconciseoverview,theassumptions,ad-vantages,andlimitationsofeachofthesemethodsaresummarizedinTable1tohelpusersselecttheoptimalmethodinpractice.

4.ValidationofsatellitederivedLST

Validationisaprocessofindependentlyassessingtheuncertaintyofthedataderivedfromthesystemoutputs.Withoutvalidation,nomethods,algorithms,orparametersderivedfromremotelysenseddatacanbeusedwithcon dence.AstheretrievedLSTsfromsatelliteTIRdatainvolvecorrectionstothesatellite-observedradiancestoac-countforatmosphericeffectsandnon-unityLSEs,itisnecessarytoas-sesstheaccuracyoftheretrievaltoprovidepotentialLSTuserswithreliableinformationregardingthequalityoftheLSTproductandtoprovidefeedbacktothedevelopersofLSTretrievalalgorithmsforfu-tureimprovement.AlthoughmanyalgorithmshavebeenproposedanddevelopedoverrecentdecadestoretrievetheLSTfromsatelliteTIRdata,farfewerstudieshavebeenundertakentovalidatethesatellite-derivedLSTsduetothedif cultyofmakinggroundmeasure-mentsoftheLSTthatarerepresentativeatthesatellitepixelscaleandalsoduetothelargespatio-temporalvariationsintheLSTitself.Inrecentyears,severalstudieshavebeenperformedtovalidatetheLSTsderivedfromavarietyofsensors,fromlargelyhomogenoustargets.SensorvalidatedincludeTM/ETM+(ThermaticMapper/EnhancedThematicMapperPlus),ASTER,AVHRR,AATSR(AdvancedAlong-TrackScanningRadiometer),MODISandSEVIRIdata(Colletal.,2005,2010,2012b;Hooketal.,2005,2003,2007;Hulley&Hook,2009a;Niclòsetal.,2011;Prata,1994b;Saboletal.,2009;Sawabeetal.,2003;Sobrinoetal.,2007;Sòria&Sobrino,2007;Trigoetal.,2008a,b;Wan,2008;Wan&Li,2008;Wanetal.,2002,2004;Wang&Liang,2009).ThreemethodsaregenerallyutilizedtovalidateLSTvaluesretrievedfromspace:thetemperature-basedmethod(T-based),theradiance-basedmethod(R-based),andcross-validation.Thefollowingsectionswillintroduceeachvalidationmethod,discusstheiradvan-tagesanddisadvantages,andshowthattheyshouldberegardedas

complementarystrategiesfortheassessmentofsatellite-basedLSTproducts.

4.1.Temperature-basedmethod(T-based)

TheT-basedisaground-basedmethodthatdirectlycomparesthesatellite-derivedLSTwithinsituLSTmeasurementsatthesatelliteoverpass(Colletal.,2005;Pinkeretal.,2009;Prata,1994b;Slateretal.,1996;Wanetal.,2002).However,performingLSTmeasure-mentsinthe eldisacomplexanddif culttaskduetothedifferenceofthescalesprobedbysatellitepixels(afewkm2)and eldsensors(afewm2orcm2).Moreover,naturallandcoverandthecorrespond-ingLSTandLSEvaluesarequitevariableatthescaleofkm2.Snyderetal.(1997)pointedoutthathomogeneousand atsurfacesthatcanbeeasilyinstrumentedandcharacterized,includinginlandwater,sand,snow,andice,canserveasvalidationsites(Colletal.,2005;Guillevicetal.,2012;Sobrinoetal.,2004c;Wan,2008).Thesizeoftheareathatneedstobeviewedbythevalidationinstrumentdependsontheinter-pixelvariabilityofthesurfaceandonhowwellmeasurementsofseveral“endmembers”canbecombinedtoobtainarepresentativevalueforthesatellitepixel.Thisprocessremainschal-lengingduetothedif cultiesinherentto ndingadequatesurfacesintheimageandperformingarepresentativethermalsamplingontheground.

BecausemostoftheEarth'ssurfaceisheterogeneousatthesatel-litepixelscale,high-qualitygroundLSTvalidationdataarescarceandarelimitedtoafewhomogeneoussurfacetypessuchaslakes,siltplayas,grasslands,andagricultural eldscollectedduringdedicat-edcampaigns(Colletal.,2005,2010,2009;Wanetal.,2002,2004).Onceathermallyhomogeneousareaisidenti ed,ingthismethod,manyau-thorshaveperformedvalidationstudiesoftheLSTvaluesproducedusingdifferentsensors(Colletal.,2005,2010,2009;Peresetal.,2008;Saboletal.,2009;Wan,2008;Wanetal.,2002).

ThemainadvantageoftheT-basedmethodisthatitprovidesadi-rectevaluationoftheradiometricqualityofthesatellitesensorandtheabilityoftheLSTretrievalalgorithmtocorrectforatmosphericandemissivityeffects.However,thesuccessofT-basedvalidationsdependscruciallyontheaccuracyofthegroundLSTmeasurementsandhowwelltheyrepresenttheLSTatthesatellitepixelscale.Be-causethespatialandtemporalvariationsoftheLSTatdaytimemightbe10Kormoreoverafewmetersorovershorttimeintervalsdependingonthenatureofthesurface,thesolarirradiationlevel,andthelocalmeteorologicalconditions,T-basedvalidationactivitiesareoftenrestrictedtonighttimeandhomogeneou …… 此处隐藏：4806字，全部文档内容请下载后查看。喜欢就下载吧 ……