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中文摘要：
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。
英文摘要：
The water held in the top few centimeters of the soil is a key variable in many hydrological, cli matological and ecological processes. These data are difficult and costly to acquire through in situ meas- urements, especially at high temporal frequencies. Different types of remote sensing systems are currently used to infer soil moisture at different spatial and temporal scales, each with its specific characteristics and limitations. The soil moisture retrieval from passive microwave is not affected by the weather, and the al- gorithm is mature and reliable. But the spatial resolution of spaceborne passive microwave data is too low for many local applications, and the data are suitable for large scale studies. Optical sensors complemented with thermal infrared channels have, in spite of the strong atmospheric attenuation and the limited pene- tration depth of the used signal, received much attention as a source of information on soil moisture con- tent and surface evaporation. The way the high spatial resolution surface evaporation information con- tained in optical/thermal sensors can be combined with relatively low resolution soil moisture. Selecting lkm resolution the Moderate Resolution Imaging Spectroradiometer （MODIS） optical data and 25km reso- lution the Advanced Microwave Scanning Radiometer for EOS （AMSR-E） passive microwave data 2 level of soil moisture product, the authors used NDVI-Ts feature space to remove the vegetation effect, and de- compose the passive microwave soil moisture through a soil evaporation model. At last the authors got the lkm resolution soil moisture. Through building scatter diagram, it could be found that the relevance be tween the inversion result and lkm Temperature Vegetation Drought Index （TVDI） reached 0. 569. The quantitative results of the study still need further validation and improvement.
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