Vegetation, as the main body of terrestrial ecosystem, is closely related to natural elements such as atmosphere, soil and water through photosynthesis and respiration. It plays an irreplaceable role in regulating global material and energy cycle, maintaining regional climate stability, and indicating ecosystem change. Climate change is an important driving factor for vegetation variation in arid areas. Exploring the temporal and spatial changes of the relationship between climate change and vegetation in arid areas is beneficial to understand the evolution characteristics of ecosystems. Altay region of Xinjiang is a typical arid and semi-arid region of inner Asia, where significant climate change has been observed over the past several decades. Meanwhile, vegetation activities have shown sensitivity to climate change, especially the vegetation and desert complexes. However, previous studies have seldom examined the spatio-temporal variation characteristics at the monthly scale in Altay region. In order to address this issue, based on the climate factors (precipitation, average temperature, maximum temperature, minimum temperature, vapor pressure and evapotranspiration) of the CRU TS multivariate climate data set and MODIS-NDVI, the temporal and spatial variation characteristics of the Normalized Difference Vegetation Index (NDVI) and its response to climate change in Altay region are investigated and compared at the monthly, seasonal and annual scales by using Sen+Mann-Kendall, Hurst index and correlation analysis methods. The results show that:(1) at the annual scale, the NDVI exhibited an overall upward trend with weak anti-persistent characteristics. In the past 20 years, about 56.29% of the total vegetation area presented a trend of annual increase, which was mainly distributed in Altai Mountain Reserve, Irtysh River Basin and Ulungu River Basin. However, there was serious vegetation degradation (12.11%), and the degraded areas were fragmented and distributed in river basins due to the impact of human activities. (2) at the monthly and seasonal scales, the NDVI was positively correlated with precipitation, temperature, extreme temperature, water vapor pressure and potential evapotranspiration. Further analyses indicated that the NDVI had the most significant correlation with temperature and extreme temperature, followed by vapor pressure and potential evapotranspiration, and the weakest correlation with precipitation, but the correlation of precipitation was higher at the seasonal scale than at the monthly scale. (3) the lag effects between the NDVI and climate factors under different land uses were manifested as short-term positive effects and long-term negative effects. This study can be conducive to predict and evaluate the vegetation dynamics in the context of global climate change and provide a theoretical reference for the management and conservation plan of regional natural ecosystem.