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温度植被干旱指数TVDI（Temperature Vegetation Dryness Index）是一种基于光学与热红外遥感通道数据进行植被覆盖区域表层土壤水分反演的方法。当研究区域较大、地表覆盖格局差异显著时,利用TVDI模型来反演陆表土壤水分,精度通常较低。对Sandholt的TVDI土壤水分反演模型进行了改进：利用云掩膜校正和多天平均温度合成来减少云的影响;同时对研究区域地形起伏、覆盖类型差异的影响进行了消除;对TVDI模型干边的模拟方法进行了改进。最后,使用铝盒采样等方法利用新疆地区观测得到的地面数据来拟合改进后的模型参数,并对2009年5月和8月的土壤水分进行了反演实验。与实测数据的比较分析表明,该模型能基本满足大区域土壤水分反演的要求,改进后的模型对新疆地区的土壤水分估算精度有较显著的提高。“,”Temperature Vegetation Dryness Index（TVDI） is an extensively used method for land surface soil moisture retrieval from optical and thermal-infrared remote sensing data.This study adapts the typical TVDI model that was proposed by Sandholt（2002）,to retrieve soil moisture information from TERRA/MODIS data in Xinjiang,west China.Improvements mainly include：① cloud-mask correction and 16-day averaged temperature composition approaches are used to reduce the impacts of clouds in TVDI-based soil moisture inversion;② the problems caused by the topographic,thermal radiation and land-cover differences over a large area are also addressed in the adjusted TVDI model;③ the modeling of TVDI dry edge is also adjusted to reduce the errors in soil moisture retrieval from MODIS data.In-situ measurements in the study area were collected with the soil sampling instrument,and used to derive the model parameters and verify the adjusted model outputs.The result shows that the modified TVDI model can give better estimation of land surface soil moisture from MODIS data in a typical arid area,Xinjiang.