温度反演经典文章(18)

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

otherauxiliarydata,andmeasuredatmosphericpro lesovertheval-idationsiteatthetimeofthesatelliteoverpass(Wan,2008;Wan&Li,2008).Thismethodusesthesatellite-derivedLSTandtheaforemen-tionedinsituatmosphericpro ingthedifferencebetweenthesimulatedTOAradianceandthemeasuredradiance,theinitialLSTwillbeadjustedandthesimulatedradiancewillbeiterativelyrecalculatedtomatchthesatellite-measuredradiance.ThedifferencebetweentheadjustedLSTandtheinitialsatellite-derivedLSTistheaccuracyoftheretrievedLST.MoredetailsabouttheR-basedmethodareprovidedbyWanandLi(2008).

TheR-basedmethoddoesnotrequiregroundLSTmeasurements,anditcanthereforebeappliedtothesurfacesonwhichgroundLSTmeasurementsareunfeasibleandextendedtohomogeneousandnon-isothermalsurfaces.ThepromisingperformanceoftheR-basedmethodoffersthepossibilityofvalidatingsatellite-derivedLSTvaluesduringthedaytimeandnighttimeoverhomogeneousandnon-isothermalsurfaces.However,thestrongestlimitationsoftheR-basedmethodaretheuseofmeasuredorestimatedLSEsrepresentativeatpixelscale,howtochecktheactualatmospherereallyfreeofclouds,andhowwellthepro lesusedinsimulationsrepresenttheactualat-mosphereatthetimeofobservations(Colletal.,2012b).ThesuccessoftheR-basedmethoddependsontheaccuraciesoftheatmosphericRTM,theatmosphericpro les,andtheLSEsatpixelscale.4.3.Crossvalidationmethod

Thismethodinvolvescross-validatingtheLSTvaluesretrievedbythemethodundertestwithwelldocumentedandvalidatedLSTvaluesretrievedfromothersatellitedata(Trigoetal.,2008a).ThistechniquerepresentsanalternativemethodforLSTvalidationiftherearenoatmosphericpro lesorgroundLSTmeasurementsavail-ableoriftheT-andR-basedvalidationscannotbeconducted.

Thecross-validationmethodusesawellvalidatedLSTproductasareferenceandcomparesthesatellite-derivedLSTtobevalidatedwiththereferenced(wellvalidated)LSTderivedfromothersatellites.DuetothelargespatialandtemporalvariationsintheLST,geographiccoor-dinatematching,temporalmatching,andVZAmatchinghavetobeperformedbeforethetwosatellite-derivedLSTproductscanbecom-pared(Qianetal.,2013;Trigoetal.,2008a).ThemainadvantageofthismethodisthattheLSTcanbevalidatedwithoutanygroundmea-surements,anditcanbeusedanywhereintheworldifwellvalidatedLSTproductsareavailable.Asmentionedabove,theaccuracyofthismethodissensitivetospatialandtemporalmismatchesofthetwoLSTmeasurements.Theobservationtimeintervalbetweenthetwomeasurementsshouldbeasshortaspossible.ConsideringthattheLSEalsodependsontheviewingzenithangleandthatthepixelsofthetwosensorscoverdifferentareasandcontaindifferentlandsurfacein-formationunderdifferentviewingangles,onlypixelswiththesameornearlysameviewingzenithanglesshouldbeusedforcross-validation.5.Futuredevelopmentandperspectives

AccuratelyacquiringLSTsattheglobalscaleiscrucialtomany eldsofstudyincludingtheEarth'ssurfacewaterandenergybal-ances,materialandenergyexchangeinterrestrialecosystemsandglobalclimatechange.Variousmethodshavebeendevelopedtore-trievetheLSTfrommultispectralormulti-angularTIRdata.Becauseofthelimitedspectralinformationprovidedinmultispectraldata,allofthesemethodsrelyondifferentapproximationstotheRTEandondifferentassumptionsandconstraintstosolvetheinherentlyill-posedretrievalproblem.Thoseapproximations,assumptions,andconstraintsmightnotholdtrueundercertaincircumstances.There-fore,usersmustchoosetheoptimalapproachtoestimatetheLSTfromspacebyconsideringthesensorcharacteristics,therequired

accuracy,thecomputationaltime,theavailabilityofatmospherictemperatureandwatervaporpro les,andtheLSEs.Consideringthesigni cantprogressmadeinrecentdecadesinLSTestimationfrommultispectralTIRdata,therewillbenosigni cantfurtherprogressinLSTretrievalfrommultispectralsatellitedataiftherearenoinno-vationsintheacquisitionofremotelysenseddata.ToovercometheshortageofmultispectraldataandtoradicallyimprovetheaccuracyofLSTretrievalfromspace,itisnecessarytoexplorenewideasandbreaknewpathsinremotesensing.

Undoubtedly,hyperspectralTIRsensorswiththousandsofchannelsarebetterabletoextractatmosphericandlandsurfaceparametersthanmultispectralTIRsensors.Ahugenumberofchannelswithnarrowbandwidthscanimprovetheverticalresolutionofatmosphericsound-ings(Chahineetal.,2001)andextracttheatmosphericquantitiesusedinatmosphericcorrections.ThehyperspectralTIRdatameasuredwith-intheatmosphericwindowcanprovidemoredetailedlandsurfacein-formation,particularlytheLSEspectrumratherthanthediscreteLSEsinmultispectraldata,aswellasmorereasonableassumptionsorcon-straintsusedtoradicallyseparatetheLSTandtheLSEs.Thesereasonshavedriventhedevelopmentofquantitativeremotesensingandotherrelateddisciplines.TheexplorationofhyperspectralTIRdataforLST/LSEseparationandtheretrievalofatmosphericpro lesoratmo-sphericquantitiesinvolvedinatmosphericcorrectionswillbecomeoneofthehotspotsinquantitativeremotesensing.

ProgresscanalsobeexpectedinthedevelopmentofnewmethodsforextractingtheLSTfromacombinationofmultispectralandmulti-temporalTIRdataacquiredfromthemultispectralsensorson-boardthenewgenerationofgeostationarysatellites,suchasSEVIRI,GOESandtheFY-2series,whichcanprovidediurnalcoveragedataandcanscanthesurfaceatleasthourlywitha xedVZA.ExceptfortheTTM,day/nightTISI,andphysics-basedD/Nmethodsinwhichdatameasuredattwodifferenttimes(oneindaytimeandtheotherinnighttime)areused,allofthemethodsdevelopedtoretrievetheLSTfromspacearebasedonmultispectraldatabutdonotconsidertemporalinformation.Itisthereforeveryattractivetoutilizethemulti-temporalinformationtoderivetheLSTfrommultispectral,multi-temporalTIRdata.

Inaddition,mostofthecurrentavailableLSTmethodsretrievetheLSTinstantaneouslyfrommultispectraldataacquiredbypolar-orbitsatellitesunderclear-skyconditions.Therearenolong-termLSTprod-uctsderivedunderallweatherconditions.Consideringthecomplemen-tarityofpassivemicrowaveandTIRdata,aphysics-basedmodelforretrievingLSTsfrompassivemicrowavedataandaneffectivemodelofcombiningLSTsretrievedfromTIRandpassivemicrowavesatellitedatamustbedevelopedinthef …… 此处隐藏：5062字，全部文档内容请下载后查看。喜欢就下载吧 ……