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• This study distinguished the contribution ratios of climate change and human activities on NDVI variation. • The NDVI, predicted NDVI, and residual NDVI significantly increased in Southwest China. • The combined effect of climate change and human activities dominated 83.22% of the NDVI variation. • The ecologically sensitive zones were distributed in the Tibetan Plateau and Sichuan Basin. • Except for the Tibetan Plateau, the vegetation greening in other landform units was dominated by the combination effect. Revealing the driving mechanism of climatic change and anthropogenic activities on vegetation variation and identifying the ecologically sensitive zones in Southwest China are critical for formulating regional ecological restoration strategies. Herein, a NDVI-based spatial–temporal model in Southwest China from 2000 to 2021 under the influences of climatic change and anthropogenic activities alone and in combination was determined based on MODIS NDVI and in situ meteorological data using Theil-Sen median analysis, the Mann–Kendall significance test, residual analysis, and relative analysis. The results showed that on the annual scale, the NDVI, predicted NDVI, and residual NDVI significantly increased at rates of 0.0016 yr−1, 0.0008 yr−1, and 0.0008 yr−1 in Southwest China from 2000 to 2021, respectively. Moreover, the NDVI, predicted NDVI, and residual NDVI significantly (P < 0.05) increased in the Guangxi Hills (GXH), Hengduan Mountains (HDM), Sichuan Basin (SCB), Yunnan-Guizhou Plateau (YGP), Zoige Plateau (ZP) and Tibetan Plateau (TP). The areas with an increase in the NDVI, predicted NDVI, and residual NDVI accounted for 81.45 %, 79.73 %, and 71.20 % of Southwest China, respectively. The NDVI variation in Southwest China was dominated by the combined effects of climatic change and anthropogenic activities, accounting for 83.22 % of the total study area. In addition, 62.76 % of the study area exhibited a greening trend. The contributions of climatic change were greater than those of anthropogenic activities for greening areas, and the opposite is true for browning areas. Innovatively, ecologically sensitive zones were identified through the Theil-Sen median analysis and Mann–Kendall significance test and accounted for 16.78 % of the total study area. Overall, this study proposed a NDVI-based spatial–temporal mode to investigate the driving mechanism of driving forces on NDVI variation, identify ecologically sensitive zones and suggest a management framework in Southwest China. [ABSTRACT FROM AUTHOR]