Abstract: Phenology has been considered as a sensitive and intuitive indicator to reflect ecosystem’s response to the climate change. Conducting spatial-explicit phenology studies in Central Asia will improve our understanding the responses of the terrestrial ecosystems in the region to rapid climate change in recent years. Based on GIMMS （Global Inventory Modeling and Mapping Studies） data from 1982 to 2006，the vegetation phenological data was calculated using 20% minimum-maximum threshold method with the Timesat software. The Mann-Kendall trend analysis and Theil Sen slope methods were used to determine the spatial-temporal change of three phenological metrics：start of season （SOS），end of season（EOS） and length of growth season （LEN）. After analysis the pattern of M-K trend and Theil Sen slope plot for three phonological metrics，there is no significant phenological change detected in the result for the whole study area. For further explorer the potential change and its reasons，the paper combined land cover data with phonological metrics for examining the phonological change in different land surface condition，and varieties of phenological metrics were analyzed for different vegetation types. The result shows that different land cover type displayed remarkably different patterns in phenological change：the start of season （SOS） of cropland advanced mostly，and the EOS （end of season） of mix forest delayed significantly. Excluded for the open shrub and closed shrub，most vegetation types showed a slight extended length of growth season （LEN）. this result suggest that the national vegetation phenology，especially of the desert vegetation，may not change obviously. The result is different compared with other conclusion in most area in the world. The unique climate or vegetation types in this area may be involved to cause this result. The method used in this paper need to be compare with others to supply more precise phenological information. The availability of longer time series in the future will also allow more focused studies on the sensitivity of the metric to changes in climate.

Key words: remote sensing, vegetation phenology, Timesat, Central Asia