Grassland NDVI in Ngari Prefecture, Tibet Autonomous Region Remains Dominantly Increasing After Filtering Out Climatic Effects (2000–2024)

Numerous studies indicate that the Tibet Autonomous Region’s grasslands have experienced widespread greening since remote sensing data became available. While climate warming and moistening can drive this trend, there is growing interest in quantifying the effect of non-climatic factors, including human activities. A widely used method estimates these effects by comparing potential and actual vegetation productivity. This study focuses on Ngari, a region constrained by both temperature and moisture. We constructed a multiple regression model using climate variables to predict NDVI and to achieve a good fit for as many pixels as possible. Residual trends, analyzed via the Kendall Tau method, reflect vegetation dynamics after removing climatic effects—a form of statistical control. Results show that grassland NDVI in Ngari increased overall (2000–2024), with 73% of pixels showing a positive Kendall Tau (among them 34% were significant at p < 0.05). The best-performing model used July–August SPEI, April–July precipitation, and mean temperature. After removing climate effects, pixels with a positive Kendall Tau rose to 74.1% (among them 21% were significant at p < 0.05), indicating that non-climatic factors exerted a net positive influence on Ngari’s grassland trends from 2000 to 2024.