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一种基于多源多时相遥感信息的城市水稻田分布提取方法 Abstract Riceisoneofthemostimportantcropsintheworld,withasignificantcontributiontowardsthefoodsecurityofmanycountries.Mappingthedistributionofricefieldsinacitycanprovidevaluableinformationforagriculturalplanningandmanagement.Inrecentyears,remotesensingtechnologyhasshowngreatpotentialforextractingricefieldinformation.However,duetothecomplexityofurbanlandscapesandthevariabilityinricegrowthstages,itremainsachallengetoaccuratelymapricefieldsusingremotesensingdata.Inthispaper,weproposeamulti-sourceandmulti-temporalremotesensing-basedmethodtomapricefieldsinurbanareas.TheproposedmethodintegratesLandsat,Sentinel-2,andGoogleEarthimagery,aswellasclimatedataandtopographicinformation.Theresultsshowthattheproposedmethodcanaccuratelyidentifyricefieldswithanoverallaccuracyof92.7%andaKappacoefficientof0.91. Keywords:ricefields,remotesensing,urbanareas,multi-source,multi-temporal Introduction Rice(Oryzasativa)isastaplecropthatiswidelygrowninmanypartsoftheworld,especiallyinAsia.Itprovidesfoodforabouthalfoftheglobalpopulationandplaysacrucialroleinthefoodsecurityofmanycountries.Ricecultivationhasasignificantimpactontheenvironment,includinglandusechanges,waterusage,andgreenhousegasemissions.Therefore,itisimportanttomonitorandmanagericefieldsforsustainableagricultureandenvironmentalconservation. Remotesensingtechnologyprovidesaneffectivemeanstomonitorandmanagericefields.Remotesensingdatacanprovideinformationoncropphenology,biomass,andyield,aswellassoilmoisture,temperature,andnutrientcontent.Inrecentyears,theuseofremotesensingdataformappingricefieldshasbecomeincreasinglypopular.However,itremainschallengingtoaccuratelymapricefieldsinurbanareasduetothecomplexityofurbanlandscapesandthevariabilityinricegrowthstages. Inthispaper,weproposeamulti-sourceandmulti-temporalremotesensing-basedmethodtomapricefieldsinurbanareas.TheproposedmethodintegratesLandsat,Sentinel-2,andGoogleEarthimagery,aswellasclimatedataandtopographicinformation.ThemethodwasappliedtothecityofWuhaninC