Remotely sensed data provide the only long term, large scale record of vegetation changes in natural terrestrial ecosystems. Changes in the spatiotemporal pattern of vegetation alter the structure and function of landscapes, consequently affecting biodiversity and ecological processes. Climate and human activities are the basic drivers to control the spatial distribution and change of vegetation. Disentangling human-induced vegetation changes from those driven by climate variations is critically important for ecological understanding and management of landscapes. The main objective of this study was to detect spatial distribution of human-induced vegetation changes. The Residual Trend, or RESTREND, method is applied to satellite observations to detect vegetation changes. Based on the rainfall and the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time series from 2001 to 2018, we analyzed the temporal and spatial variation of NDVI in Shaanxi Province, China. The influence of climate factors, rainfall, was separated by Time Series Segmentation and Residual Trend (TSS-RETREND) algorithm and we got the areas and magnitude of human activities on vegetation change. The results showed that (1) during 2001-2018, the NDVI value in Shaanxi had significantly increased and the average increase rate was 0.006/a. (2) Compared with the average NDVI value of the 18 years, 77.29% of the areas were greater than the mean value. Yulin and Yanan in northern Shaanxi had the greatest areas with 97.52% and 89.03% respectively, followed by Qinba Mountain Area (73.91%). After 2012, the high value of NDVI tended to be northward year by year. (3) Human activities had a great influence on vegetation change and the total increase areas of NDVI by human activities was 71.77%, while the increase in northern Shaanxi was significantly larger than that in Guanzhong Plain and Qinba Mountain area. The increase area of NDVI in Yulin and Yanan were 72.11% and 86.44%, respectively, which exceeded the average level of the whole province. (4) Based on the rules of greenness level, the changes of NDVI in the province were qualitatively divided into increase (INC, I1, I2 and I3), decrease (D1, D2 and D3), and no obvious change (NSC). The greenness levels in Yulin City and Yanan City were higher than those in Guanzhong Plain and Qinba Mountain area. The sharp greenness growth areas of Yanan and Yulin are account for 55.46% and 34.34%, respectively, while those in southern Shaanxi are 41.03%, indicating that the southern Shaanxi area with humid climate also had a significant greening trend.