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应用MODIS遥感数据反演棉花水分信息 被引量:1

Cotton Water Content Estimation with MODIS Vegetation Index
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摘要 明确适宜的水分信息表征参数类型以及植被指数类型是提高MODIS遥感数据作物水分含量监测精度的关键。本研究获取了棉花叶片尺度(EWTleaf和FMC)、冠层尺度(EWTcan和VWC)水分含量信息,以及观测点的6类MODIS植被指数(归一化植被指数NDVI、绿色植被指数VIgreen、差异红外指数6NDII6、差异红外指数7NDII7以及增强植被指数EVI),对水分含量表征参数与植被指数之间的相关关系进行了全面对比分析,筛选确定了最适宜的水分含量参数类型、植被指数类型以及各水分含量参数的估算模型。结果表明:①EWTcan与各植被指数之间的相关性普遍优于其他3个水分含量表征参数;②6类MODIS植被指数中,NDVI以及EVI与各类水分含量表征参数之间的相关性表现最佳;③EWTcan的最佳估算模型是由NDVI构建的一元线性模型(REP=45.38,r=0.681)。 Identifying the suitable water content parameter and the suitable MODIS vegetation index for crop water content estimation by MODIS data is crucial for improving the precision of water content remote sensing.In the study,cotton water content information at leaf(i.e.EWTleaf and FMC)and canopy(i.e.EWTcan and VWC)scales was obtained,respectively.The vegetation indices based on MODIS data were calculated,including 6types of indices,i.e.Normalized Difference Vegetation Index(NDVI),Green Vegetation Index(VIgreen),Normalized Difference Infrared Index 6(NDII6),Normalized Difference Infrared Index 7(NDII7),and Enhanced Vegetation Index(EVI).Based on a comprehensive analysis of correlation between water content parameters and vegetation indices,the suitable types of water content parameter and vegetation indices were determined,and furthermore,the estimation models for water content parameters were developed and the estimation precision were validated.The following conclusions were drawn:1)Comparing with thecorrelaitonship between other three water content parameters,i.e.EWTleaf,FMC,VWC,and vegetation indices,the EWTcan was significantly related to all vegetation indices;2) among six vegetation indices,NDVI and EVI have the strongest correlationship with water content parameters;3)the optimal estimation model for EWTcan was linear model based on NDVI,with REP=45.38,r=0.681.
出处 《遥感信息》 CSCD 2014年第2期106-113,共8页 Remote Sensing Information
基金 国家自然科学基金资助项目(41104130 51109183 41371393) 中国科学院"西部之光"博士资助项目(XBBS200902)
关键词 MODIS数据 植被指数 棉花 水分信息 估算模型 MODIS data vegetation index cotton water content information estimation model
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