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基于Radarsat2与Landsat8协同反演植被覆盖地表土壤水分的一种新方法.docx

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基于Radarsat2与Landsat8协同反演植被覆盖地表土壤水分的一种新方法 Title:ANewMethodforSynergisticInversionofVegetationCoverageandSoilMoistureontheEarth'sSurfaceBasedonRadarsat-2andLandsat-8 I.Introduction Theestimationofvegetationcoverageandsoilmoistureplaysacrucialroleinstudyingthedynamicsoflandsurfaceprocessesandinwaterresourcemanagement.Remotesensinghasbeenextensivelyusedfornon-destructiveandlarge-scalemonitoringoftheseparameters.ThispaperproposesanovelmethodforthesynergisticinversionofvegetationcoverageandsoilmoistureusingacombinationofRadarsat-2andLandsat-8satellitedata. II.Background 1.Radarsat-2:Radarsat-2isaC-bandsyntheticapertureradar(SAR)satellitethathasthecapabilitytopenetratevegetationcanopiesandmeasurethebackscatterfromthegroundsurface.SARdataissensitivetosoilmoistureandallowsfortheestimationofvegetationcoverageevenindensecanopies. 2.Landsat-8:Landsat-8isamulti-spectralsatellitethatprovideshigh-resolutionopticalimagery.Thecombinationofvisible,near-infrared,andshortwaveinfraredbandsallowsforaccuratemappingofvegetationcoverage. III.Methodology 1.DataAcquisition:Radarsat-2SARdataandLandsat-8opticaldataareacquiredforthestudyarea.ThesedatasetscanbeobtainedfromvarioussourcesliketheCanadianSpaceAgencyandtheUSGeologicalSurvey. 2.Pre-processing: a.RadiometricCalibration:TheSARdataisradiometricallycalibratedtoconvertthemeasuredradarbackscattervaluestocalibratedradarcross-section(sigmanaught)values. b.GeometricCorrection:BoththeSARandopticaldatasetsaregeometricallycorrectedtoensureaccuratespatialalignment. 3.SynergisticInversionModel: a.VegetationCoverageEstimation:TheopticaldatafromLandsat-8isusedtoestimatethevegetationcoverageusingestablishedvegetationindicesliketheNormalizedDifferenceVegetationIndex(NDVI)orEnhancedVegetationIndex(EVI). b.SoilMoistureEstimation:TheSARdatafromRadarsat-2isusedtoestimatesoilmoistureusingestablishedsoilmoistureretrievalalgorithmsliketheWaterCloudModelortheIntegralEquationModel. 4.DataFusionandIntegration:Thevegetationcoverageandsoilmoistureestimatesobtainedf