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土壤水分是一个重要生态参量,以被动微波反演土壤水分,不受天气影响,且其算法成熟。但是星载被动微波数据的空间分辨率较低,可适合大区域尺度研究。本文将1km分辨率光学数据MODIS和25km分辨率被动微波数据AMSR-E2级土壤湿度产品结合,利用NDVI-Ts特征空间,去除植被影响,结合前人提出的裸土蒸散模型,将研究区被动微波土壤湿度数据分解,得到1km分辨率土壤体积含水量。将其反演结果与1km温度植被干旱指数(TVDI)进行趋势和数值比较,其相关性达到0.569。同时,利用实测样点的土壤重量含水量,与得到的1km分辨率土壤体积含水量数据进行比较,其增减趋势一致,结果具有可信度。但对定量结果尚需进一步验证和提高。
Soil moisture is an important ecological parameter, with passive microwave inversion of soil moisture, weather-free, and its algorithm is mature. However, the spatial resolution of spaceborne passive microwave data is low, which is suitable for large area scale research. In this paper, the optical data MODIS of 1km resolution is combined with the passive microwave data AMSR-E2 soil moisture products with a resolution of 25km. By using the NDVI-Ts feature space, the influence of vegetation is removed. Combined with the previous bare soil evapotranspiration model, Soil moisture data was decomposed to obtain 1km resolution soil volumetric water content. The correlation between the inversion results and TVDI of 1 km temperature was 0.569. At the same time, using the measured soil moisture content, compared with the obtained data of 1km soil moisture content, the trend of increase and decrease is the same, and the result is credible. However, the quantitative results still need further verification and improvement.