MODIS温度变化率与AMSR-E土壤水分的关系的提出与降尺度算法推广

土壤水分参数是陆面过程与水循环的重要影响因素。不同的遥感平台可提供不同时间和空间尺度的土壤水分，它们分别具有各自的优势与不足。利用被动微波辐射计AMSR-E土壤水分和MODIS地表温度、植被指数产品，作者探讨了地表温度变化率和土壤水分的关系，并借鉴地表温度T_s和归一化植被指数NDVI的特征空间理论，构造了温度变化率和土壤水分的三角形特征空间。随着地表温度变化率的增加，土壤水分的分布范围缩小，同时土壤水分的数值降低。作者由此提出了变温植被指数（TVVI），并指出该指数与土壤水分呈稳定的幂指数函数关系，建立了土壤水分与温度变化率的经验定量模型。之后作者通过上述函数关系和高分辨率MODIS数据，实现了AMSR-E土壤水分数据的降尺度处理。与地面实测数据的比较表明，该降尺度方法的准确性较高。

The Relationship Between the Variation Rate of MODIS Land Surface Temperature and AMSR-E Soil Moisture and Its Application to Downscaling

Using AMSR-E soil moisture, MODIS land surface temperature (T_s) and vegetation index product, the authors discuss the relationship between the variation rate of land surface temperature and surface soil moisture. Selecting the plains region of central United States as the study area, the authors propose the distribution triangle of the variation rate of land surface temperature and soil moisture. In the present paper, temperature variation and vegetation index (TVVI), a new index containing the information of temperature variation and vegetation, is introduced. The authors prove that TVVI and soil moisture show a steady relationship of exponential function; and build a quantitative model of soil moisture(SM) and instantaneous surface temperature variation (V_Ts). The authors later achieve downscaling of AMSR-E soil moisture data, through the above stated functional relationships and high-resolution MODIS data. Comparison with measured data on ground surface indicates that this method of downscaling is of high precision.