Abstract: Time-lag effect of vegetation refers to the growth and distribution patterns out of sync with the varying climate. Vegetation cannot adapt immediately the climate change, leading to adjustment time. Previous research has focused mainly on the overall growth of vegetation under climate monitor or changes in a single type of vegetation. It is still lacking in the time-lag effect of vegetation types and their response to the climate. Therefore, this study aims to determine the vegetation activity and its response to climate change. The lag time of different vegetation types was also clarified in response to the hydrothermal changes. The Normalized Difference Vegetation Index (NDVI) and meteorological grid data were monthly collected from 1982 to 2015. The GIMMS NDVI dataset was also selected, together with the CRU precipitation and air temperature dataset. Sen + Mann-Kendall trend analysis was then conducted to obtain the interannual change rate of vegetation NDVI in over the past 34 years. At the same time, a significance test was carried out on the NDVI change trend, in order to distinguish the significant improvement and degradation areas. The growth and degradation of different vegetation types were statistically determined after the test. The lagged partial correlation analysis was used to calculate the partial correlation coefficients between vegetation NDVI and precipitation and air temperature in the current month, the previous month, the first previous two months, and the first previous three months. Then, the partial correlation coefficients were also synthesized to obtain the maximum partial correlation coefficient. The lag time was set as the maximum partial correlation coefficient. The dynamic characteristics of the vegetation pattern change over the past 34 years were presented to determine the relationship between vegetation NDVI and climate response. The lag effect was obtained in the different vegetation types on climate response. The results showed that: 1) A spatial distribution pattern of vegetation was achieved in the higher vegetation in northern Xinjiang than that in the southern, and higher in the west than that in the east. There was an overall "greening" trend in the study area. Specifically, the significantly improved and stable unchanged areas accounted for 20.6%, and 65.7%, respectively. The areas insignificant improvement and degradation accounted for 3.3%, and 10.4%, respectively. There was no area with significant degradation. In the spatial distribution, a significant NDVI increase was found in the oasis around the Tarim Basin and the northern section of the Tianshan Mountains, whereas, the Ili region showed a trend of degradation. In vegetation types, the cultivated vegetation shared the largest improvement area, accounting for 75.3%, while, the degraded area of coniferous forest was the largest, accounting for 24.2%; 2) There was a lag response of 72% of vegetation areas to the precipitation at the monthly time scale, with an average lag time of 1.1 months, while the lag response of 70% of vegetation areas to air temperature, with an average lag time of 1.4 months. The higher the lagged correlation coefficient between vegetation and climate elements was, the higher the response speed was. Overall, the vegetation was much more sensitive to the precipitation. 3) Different types of vegetation varied greatly in response to the precipitation and air temperature. Precipitation was the main promoting factor for the grassland, shrubland, and coniferous forest, while air temperature shared the strongest impact on the broad-leaved forest. The lagged partial correlation coefficients between different vegetation types and precipitation were higher than those of air temperature. The response time of different vegetation types to air temperature was longer than that of precipitation. There were lagged effects in the response of different vegetation to both precipitation and air temperature. The correlation between vegetation and precipitation was higher in Xinjiang, indicating a more rapid response of vegetation to precipitation than that to air temperature.