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渤海浑浊水体GOCI影像神经网络大气校正研究.docx

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渤海浑浊水体GOCI影像神经网络大气校正研究 Abstract TheBohaiSeaisanimportantwaterresourceinChina,butitisfacingvariousenvironmentalproblemssuchaspollutionandeutrophication,whichmakeitdifficulttomaintaingoodwaterquality.RemotesensingtechnologyhasbeenwidelyusedtomonitorthewaterqualityoftheBohaiSea.However,atmosphericaerosolsandstratificationcanseverelyaffecttheremotesensingsignal,leadingtolargeerrorsintheretrievedwaterqualityparameters.Inthisstudy,weproposedadeeplearningmodelfortheatmosphericcorrectionofGOCIimagestoimprovetheaccuracyofthewaterqualityretrieval. Introduction TheBohaiSeaisasemi-enclosedshallowsealocatedinthenortheastofChina,whichisanimportantwaterresourceforeconomicdevelopment,transportation,andecologicalenvironment.However,duetotherapiddevelopmentofindustryandagricultureinthesurroundingarea,theBohaiSeahasbeenseverelyaffectedbyvariousenvironmentalproblems,suchaspollutionandeutrophication.WaterqualitymonitoringisanimportanttooltoevaluatetheecologicalhealthoftheBohaiSea.Remotesensingtechnologyhasprovidedarapid,efficient,andcost-effectivemethodforlarge-scalemonitoringofwaterquality,whichhasbeenwidelyusedintheBohaiSea. However,theatmosphericeffectscanseriouslyaffecttheaccuracyofremotesensingwaterqualityestimation,especiallyintheshallowwaterareas.Theatmosphericcorrectionmethodcansignificantlydecreasetheatmosphericeffectsandimprovetheaccuracyoftheretrievedwaterqualityparameters.Thetraditionalatmosphericcorrectionmethodneedstousetheinformationofaerosolopticalpropertiesandthewatersurfacereflectance,whicharedifficulttoobtaininpractice. Inrecentyears,deeplearningtechnologyhasshowngreatpotentialinmanyapplications,suchasimageclassification,objectdetection,andsemanticsegmentation.Inthefieldofremotesensing,deeplearningmodelshavebeenproposedforatmosphericcorrection,land-coverclassification,andchangedetection.Inthisstudy,weproposeadeeplearning-basedatmosphericcorrectionmodelforGOCIimagesintheBohaiSea. MaterialsandMethods GOCI(GeostationaryOceanColorImager)isamulti-channeloceancolorsensoronb