Tibet is one of the five largest pasturing regions of China. Grassland classification is significant for its utilization and protection, but few correlative studies have been done in Tibet due to its rugged natural conditions, which make it difficult and time-consuming to conduct extensive field measurements. The remote-sensing technique is helpful for grassland classification in such regions. In this study, high temporal resolution of a moderate resolution imaging spectroradiometer (MODIS) is used to construct temporal profiles of enhanced vegetation index (EVI) during the grass growth period in Tibet. By dividing the large study area into individual regions based on altitude and latitude, we classified the grasslands of Tibet into six types-meadow steppe, typical steppe, desert steppe, alpine meadow steppe, alpine typical steppe, and shrub herbosa. Based on the 1:500 000 scale maps of China's grassland resources, the validation process indicates an overall accuracy of 68.02 %, and a Kappa coefficient of 0.52. Land managers are provided with maps and area values of each grassland type in Tibet in 2005. In addition, regional average EVI reflect the relative biomass of each types of the grassland, which will provide evidences for coordinating plans for grassland developing. MODIS_EVI provides a simple and rapid method to classify the grassland in regions that are hard to reach, which offers an effective means of investigating biological resources on a large scale.