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基于时间序列的MODIS遥感数据的辐射定标 Introduction: Remotesensingisthescienceofobtaininginformationaboutobjectsorareasfromadistance,typicallyfromaircraftorsatellites.Remotesensingdataneededtobefurtheranalyzedtoextractusefulinformation.Radiometriccalibrationisoneofthemostcrucialprocessesinremotesensing,whichaimstoconvertthedigitalnumbers(DNs)oftheremotesensingdatatoradiometricunitssuchasradianceorreflectance.TheaimofthispaperistodiscusstheradiometriccalibrationofMODIS(ModerateResolutionImagingSpectroradiometer)remotesensingdatabasedontimeseriesanalysis. RadiometricCalibrationofMODISData: MODISisakeyremotesensinginstrumentontheEarthObservingSystem(EOS)TerraandAquasatelliteplatforms.Itprovidesearthobservationsin36spectralbands(throughvisible,near-andmid-infraredregion)ataspatialresolutionof250m,500m,and1km.TheMODISdataisavailableinrawcountscalleddigitalcounts(DN).TheDNvaluesarethenconvertedtoradianceusingpre-launchcalibrationcoefficientsandonboardcalibrationdatasetstocreateacalibratedradianceproduct.However,theradiometriccalibrationofMODISdatasuffersfromsensordegradation,atmosphericeffects,andotherfactorsovertime.Therefore,itisnecessarytoperiodicallycalibratetheMODISdatatoimproveitsaccuracy. TimeSeriesAnalysis: Timeseriesanalysisisastatisticaltechniquethatdealswithtimeseriesdata,orsequencesofobservationsthatarecollectedovertime.Itisusedtostudyandmodelthebehavioroftime-varyingphenomena,includingenvironmentaldata.Timeseriesanalysiscanbeusedtodetecttrends,seasonalpatterns,andirregularfluctuationsinthedata.Itcanalsobeusedtoforecastfuturevaluesbasedonhistoricaldata. RadiometricCalibrationofMODISDataUsingTimeSeriesAnalysis: RadiometriccalibrationofMODISdatacanbeimprovedusingtimeseriesanalysis.RadiometriccalibrationerrorscanbecorrectedbyassessingchangesintheMODISsensorovertimeanddevelopingacalibrationmodel.ThetimeseriesofMODISdatacanbeusedtodeveloptrendmodelsusingmultiplelinearregressionoratimeseriesdecompositiontechniquecalledSeasonal-TrenddecompositionusingLoess(STL).TheSTLmethoddecomposes