The Yili Valley in Xinjiang,China is a developed zone and an important base of oasis agriculture and animal husbandry. Climate change,overgrazing and inadequate investment in construction have led to the serious destruction of grasslands and it is now important to study grassland dynamics and precipitation sensitivities to ensure sustainable management. However,the temporal-spatial dynamics of vegetation variation in Yili Valley grasslands are poorly understood, especially using remote sensing methods. Based on variation coefficients and linear regression methods at the pixel level,MODIS NDVI datasets from 2000 to 2010 were used to analyze vegetation dynamics of Yili Valley grasslands. Integrated with a precipitation dataset from 2000 to 2010,correlation coefficients and the precipitation sensitivity index were computed to characterize temporal-spatial variation in precipitation sensitivity at a yearly scale.We found that significant degradation occurred in Yili Valley grasslands from 2000 to 2010. Significant spatial variation was discovered for degradation from different grassland types:the NDVI of alpine meadow and mountain meadow showed remarked degradation and vegetation improvement mostly occurred in temperate desert grasslands,temperate grasslands and temperate deserts. The spatial variation of precipitation sensitivity was significant. The precipitation sensitivity of grassland increased with improvement degree in vegetation dynamics. Precipitation increments led to vegetation improvements from 2000 to 2010. Temporal-spatial variation in precipitation sensitivity depended on grassland types and precipitation variation. Sparse vegetation,such as temperate grassland, temperate desert and temperate desert grassland showed greater sensitivity to precipitation. Spatially,variation in precipitation was negatively correlated with precipitation sensitivity:vegetation in drier places was more sensitive to precipitation. Temporally,grassland vegetation was more sensitive to precipitation in years with less precipitation.