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干旱的严重程度可以通过土壤水分含量和下垫面植被状态来反映,在对旱情发生程度的遥感反演过程中,土壤和植被的光谱特征是进行旱情程度判断的重要因子。为了更好地通过遥感方法对土壤水分含量进行准确的反演,在基于地表含水量指数(SWCI)模型研究的基础上,根据不同土壤质地的光谱特征对SWCI模型进行修正。在研究中假设壤土的修正系数为1,根据不同土壤质地的光谱特征分别设定沙土地的修正系数为0.8,沙壤土地的修正系数为0.9,黏壤土的修正系数为1.3,黏土的修正系数为1.4。通过与SWCI的反演结果对比分析,发现在修正后的土壤浅层水分含量反演精度显著提高。这有助于在实时干旱动态监测中根据不同的土壤质地进行调整,提高监测精度。
The severity of drought can be reflected by the soil moisture content and underlying vegetation status. During the remote sensing inversion of the degree of drought occurrence, the spectral characteristics of soil and vegetation are important factors for judging the extent of drought. In order to accurately retrieve the soil moisture content by remote sensing, the SWCI model was modified based on the spectral characteristics of different soil textures based on the study of the surface water content index (SWCI) model. According to the spectral characteristics of different soil texture, the correction coefficient of sandy soil is set as 0.8, the correction coefficient of sandy soil is 0.9, the correction coefficient of clay soil is 1.3, and the correction coefficient of clay is 1.4. By contrasting with SWCI inversion results, it is found that the accuracy of retrieval of shallow soil moisture content is significantly improved after correction. This will help to adjust the soil texture according to different soil quality in dynamic monitoring of real-time drought so as to improve the monitoring accuracy.