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塔里木河流域绿洲土壤盐分遥感反演模型研究 Abstract: TheTarimRiverBasinislocatedinthearidandsemi-aridregionofnorthwestChina,whereoasisagricultureplaysasignificantroleinthelocaleconomyandecology.Thesalinizationofoasissoil,however,posesamajorchallengetosustainabledevelopment.Inthisstudy,weproposedaremotesensing-basedmodeltoestimatesoilsalinityintheTarimRiverBasin.WeusedLandsat8OLI/TIRSdata,spectralindices,andfieldmeasurementsofsoilsalinitytodevelopapredictivemodel.Theperformanceofthemodelwasevaluatedusingtwostatisticalindices,coefficientofdetermination(R2)androotmeansquareerror(RMSE).OurresultsindicatethatthemodelachievedahighaccuracywithanR2of0.82andRMSEof1.26dS/m.Thespatialdistributionofsoilsalinitywasthenmapped,whichrevealedtheseverityofsoilsalinizationindifferentoases.Ourresultscouldprovideimportantinformationforpolicymakersandlocalfarmerstodevelopeffectivestrategiesforsoilmanagement. Introduction: Asoneofthelargestinlandriverbasinsintheworld,theTarimRiverBasincoversanareaof1.02millionsquarekilometers,withapopulationofover10million.Theregionischaracterizedbyanaridandsemi-aridclimate,withalimitedwatersupply,andhighevaporationrates.Despitetheseharshconditions,oasisagriculturehasbeenpracticedforthousandsofyears,providingastablesourceoffoodandincomeforlocalcommunities.Inrecentyears,however,thesalinizationofoasissoilhasbecomeamajorchallengetosustainabledevelopmentintheregion.SoilsalinityisawidespreadproblemintheTarimRiverBasin,andithasbeenestimatedthatabout80%ofthecultivatedlandintheregionisaffectedbysoilsalinization(Wangetal.,2017).Highsoilsalinitycanreducecropproductivity,causesoildegradation,andaffectlocalecosystems. Traditionalmethodsofsoilsalinityassessmentaretime-consuming,labor-intensive,andoftenlimitedtoafewsamplelocations.Remotesensing-basedapproaches,however,haveshowngreatpotentialinprovidingtimelyandcost-effectivemeasurementsofsoilsalinityoverlargeareas.Anumberofspectralindiceshavebeenproposedtoestimatesoilsalinity,suchasNormalizedDifferenceVegetationIndex(NDVI),SoilAdjustedVeget