Precipitation is a significant part of the hydrological cycle and so the investigation of changes in precipitation characteristics is normally the first step in investigating the impact of climate change on water availability. However,high-resolution precipitation datasets are seldom available,which,to some extend,limits our understanding of spatio- temporal patterns in precipitation regies and basin scale hydrology. Since regions around the globe with sufficient precipitation gauge networks that are up to the challenge of this type of research are few and far between,precipitation estimations from space borne sensors are often applied to supplement the information collected from existing low-resolution precipitation gauge networks in near real-time applications. Based on observed daily precipitation data asreal datafrom 42 stations covering a period of 2001- 2010 in the Inner Mongolia,China,TRMM (Tropical Rainfall Measuring Mission) precipitation data with spatial resolution of 0.25°*0.25° was downscaled based on statistical relations between NDVI,meteorological variables,and DEM using LOO (Leave-One-Out) cross evaluation method,spatial autocorrelation analysis methods. The lag time between NDVI and precipitation changes was also considered in this study. The results indicated that: 1) On annual scale,TRMM data can be used for estimation of annual precipitation amount in the Inner Mongolia Region and linear relations can be identified between annual TRMM and observed precipitation data; 2) The analysis of the effect of lagging on the vegetation response to precipitation indicates that a period of 10 days accurately is the lag time,showing the relatively rapid vegetation response to precipitation. Morans I indicates that the vegetation index is spatially correlated and identified spatial heterogeneity in the transitional zones between different types of land use and land cover and the unused land area;3) Significant relations between TRMM and observed precipitation can be detected at moderate spatial scale with spatial resolution of 0.50°*0.50°; 4) Temperature is found to be an important factor influencing downscaling of TRMM precipitation data due to high sensitivity of NDVI changes to temperature variations in the Inner Mongolia Region. Inner Mongolia is topographically levelling and hence DEM is not the significant factor having impacts on downscaled TRMM data; 5) Downscaled TRMM can well reflect spatial patterns of annual precipitation changes. Less precipitation can be found in west Inner Mongolia and more precipitation in south and southeast Inner Mongolia. This study provides another possibility in evaluation of spatial patterns of precipitation changes,and hence provides and right precipitation dataset for conservation of grassland and also irrigation management in the highly eco-environmentally fragile region.