基于高光谱数据的黄河流域水体提取方法研究.docx

基于高光谱数据的黄河流域水体提取方法研究
摘要
本研究旨在探究基于高光谱数据的黄河流域水体提取方法，并对其有效性进行评估。在高光谱遥感影像的采集和处理过程中，我们采用了最小二乘法（OLS）和最小二乘支持向量机（LS-SVM）两种方法进行反演。结果显示，LS-SVM方法能够更好地提取出水体信息，准确率达到了91%以上。此外，我们还研究了影响水体提取准确性的因素，包括光谱响应曲线、水深、降雨量等。综上所述，本研究为黄河流域水体资源的有效管理提供了一种可靠的技术手段。
关键词：高光谱数据；水体提取；最小二乘法；最小二乘支持向量机；黄河流域
Abstract
TheaimofthisstudyistoexplorethemethodofwaterbodyextractionintheYellowRiverBasinbasedonhyperspectraldataandevaluateitseffectiveness.Intheprocessofacquiringandprocessinghyperspectralremotesensingimages,weusedtwomethods,ordinaryleastsquares(OLS)andleastsquaressupportvectormachine(LS-SVM)toinvert.TheresultsshowedthattheLS-SVMmethodcanbetterextractwaterbodyinformation,withanaccuracyrateofmorethan91%.Inaddition,wealsostudiedthefactorsthataffecttheaccuracyofwaterbodyextraction,includingspectralresponsecurves,waterdepth,andrainfall.Insummary,thisstudyprovidesareliabletechnicalmeansfortheeffectivemanagementofwaterresourcesintheYellowRiverBasin.
Keywords:hyperspectraldata;waterbodyextraction;ordinaryleastsquares;leastsquaressupportvectormachine;YellowRiverbasin
Introduction
Waterresourceisavaluablenaturalresourcethatplaysanimportantroleinhumansurvivalanddevelopment.Inrecentyears,withtherapidgrowthofpopulationandeconomy,thedemandforwaterresourceshasincreasedsignificantly.Themanagementofwaterresourceshasbecomeanimportantissueforsustainabledevelopment.Therefore,itisveryimportanttoaccuratelyandquicklyidentifyandmonitorthewaterbodyresources.
Hyperspectralremotesensingtechnologycanobtainhigh-resolutionandhigh-precisionspectralinformationoftheearth'ssurfaceandhasbeenwidelyusedinthedetectionandanalysisofwaterresources.However,waterbodyextractionbasedonhyperspectraldataisstillachallengingtaskduetovariousfactorssuchasthecomplexityofwatersurfaceandtheinfluenceofatmosphericscattering.
ResearchMethods
Inthisstudy,wecollectedhyperspectralremotesensingdataoftheYellowRiverBasinasexperimentaldataandusedthetwomethodsofordinaryleastsquares(OLS)andleastsquaressupportvectormachine(LS-SVM)toinvert.
OLSisatraditionallinearre