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在可见光和近红外遥感中，地物阴影通常认为是提取信息的噪声或干扰．而 在热红外遥感中，发现地物光照面和阴影的信息差是提取热量平衡参数的重要信息源． 通过实践，建立了以地物光照面和阴影的表面温度差为基础的土壤水分含量的遥感模 型，为利用多角度信息提取遥感土壤水分开辟了新的途径．在中国科学院禹城综合试 验站遥感试验场开展了模型论证试验．试验资料很好地支持了模型的验证．所用方法 与现有的热惯量方法和作物缺水指数方法进行了对比，分析了本方法的优越性和局限 性．
In visible and near-infrared sensing, the shadow of a feature is usually thought to be noise or interference that extracts the information. In the thermal infrared remote sensing, it is found that the information difference between the light surface and the shadow of the object is an important source of information for extracting the heat balance parameter. Through practice, the remote sensing model of soil moisture content based on the surface temperature difference between the light surface and the shadow of the object is established, which opens up a new way for extracting the remote sensing soil moisture with multi-angle information. The model demonstration test was carried out in the remote sensing test site of Yucheng Comprehensive Experimental Station of Chinese Academy of Sciences. Experimental data well support the model validation. The methods used are compared with the existing thermal inertia method and crop drought index method, and the advantages and limitations of the method are analyzed.