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ASAR和TM数据协同反演植被覆盖地表土壤水分的新方法

, PP. 532-540

Keywords: 微波光学遥感,MIMICS,PROSAIL,土壤水分

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Abstract:

?考虑到主动微波和被动光学遥感数据反映地表土壤水分的各自优势,提出一种ASAR数据和TM数据协同反演植被覆盖土壤水分的半经验耦合模型.该模型通过简化MIMICS模型,将研究对象分为植被冠层和土壤层两部分,模拟了冠层叶片含水量与单位体积内植被消光系数,后向/双向散射系数的经验关系,减少了模型的输入参数,使模型最关键的输入参数为光学易于反演的叶面积指数LAI.LAI采用PROSAIL模型进行反演,实现微波和光学模型的耦合,并引入植被均方根高度(Sveg)来修正冠层重叠造成的雷达阴影效应,然后对半经验模型的系数进行了参数敏感性分析,发现在LAI较小时(LAI≤3),模型更为适用.最后,选用甘肃黑河试验区的TM,ASAR数据,利用耦合模型生成了研究区土壤水分布图,并利用地面实测数据对该耦合模型和MIMICS模型进行比较验证.结果表明:通过对雷达阴影效应的校正,该模型反演的地表土壤水分与实测值的平均相对误差Er从17.6%减小到10.4%,RMS从0.055降低到0.031g/cm3.同时,耦合模型的反演效果明显好于MIMICS模型单独反演的结果(Er=22.7%,RMS=0.068g/cm3);表明在LAI较小的区域,该主被动遥感耦合模型能有效的反演土壤水分,取得较好的反演精度.

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