Monitoring Long-Term Vegetation Dynamics in the Hulun Lake Basin of Northeastern China Through Greening and Browning Speeds from 1982 to 2015

Vegetation dynamics in the Hulun Lake Basin (HLB), a vulnerable grassland-wetland-forest transition zone in Northeastern Inner Mongolia, North China, are sensitive to climate change, but traditional greenness metrics like the normalized difference vegetation index (NDVI) lack process-level insights. Using the GIMMS NDVI3g dataset (1982-2015) and meteorological data, this study analyzed the spatiotemporal dynamics of the NDVI and vegetation NDVI change rate (VNDVI)-a metric quantifying greening and browning speeds via NDVI temporal variation-employing linear regression and partial correlation analyses. The NDVI exhibited an overall significant upward trend of +0.0028 yr^-1 (<i>p</i> < 0.05) across more than 70% of the basin, indicating a persistent greening tendency. The VNDVI revealed an accelerated spring greening rate of +0.8% yr^-1 (<i>p</i> < 0.05) and a slowed autumn browning rate of -0.6% yr^-1 (<i>p</i> < 0.05), reflecting an extended growing season. Spatial correlation analysis showed that the temperature dominated spring greening (r = 0.52), precipitation governed summer growth (r = 0.64), and solar radiation modulated autumn senescence (r = 0.38). Compared with the NDVI, the VNDVI was more sensitive to both climatic fluctuations and anthropogenic disturbances, highlighting its utility in capturing process-level vegetation dynamics. These findings provide quantitative insights into the mechanisms of vegetation change in the HLB and offer scientific support for ecological conservation in North China's grassland-forest ecotone.