Vegetation phenology is the most compelling evidence that ecosystems are being influenced by global climate change. The response of vegetation phenology on climate change in Central Asia, which is one of regions with the most fragile ecological and hydrological system, has become a hot issue in global environmental research worldwide. Based on GIMMS (Global Inventory Modeling and Mapping Studies) data from 1982 to 2006 and SPOT vegetation S10 data from 1998 to 2012,the vegetation phenology information was extracted by dynamic threshold method with Timesat phenology extract software. Mann-Kendall trend analysis method was used to assess spatial-temporal change trend of Start of Season (SOS), End of Season (EOS) and Length of Season (LOS). Moreover, combined the 2 d scatterplot and linear regression algorithm of least square, The three metrics in the overlapped 8 year was compared for examining the difference between two set of vegetation phenology data derived from GIMMS and SPOT vegetation. The result indicated that, (1) vegetation phenology characters in 90% and 95% area of Central Asia did not shown a significant change trend for 19822012; (2) agriculture land was found as a main land cover type with a significant change of SOS, EOS and LOS; (3) there are obvious difference between two set of phonological data based on GIMMS and SPOT vegetation; the range of correlation coefficients between tow set of SOS,EOS and LOS are [0.36,0.56], [0.32,0.49] and [0.28,0.45], and in the area with sparse vegetation, two set of the three metrics show a lower consistency than the area with higher vegetation coverage. It suggested the consistency can be influenced by different scale and soil background.