Spatiotemporal Changes in Vegetation Cover and Their Driving Mechanisms in Lüliang City from 2000 to 2023 Based on MODIS NDVI and Google Earth Engine

Vegetation is a key indicator of changes in global ecosystems. Monitoring its dynamics is important for regional environmental management and ecological assessment. This study examined Lüliang City, Shanxi Province, using the cloud-computing capabilities of Google Earth Engine (GEE) to process 24 years (2000–2023) of MODIS MOD13Q1 NDVI data. Pixel-wise linear regression, the Mann–Kendall trend test, coefficient-of-variation analysis, and geospatial overlay analysis were used to characterize spatiotemporal changes in vegetation cover, its stability, and potential drivers. The results show that: (1) the annual mean NDVI increased significantly despite interannual fluctuations (slope = 0.0047 yr−1, p < 0.01), with a reported increase of 42.9%; the coefficient of variation (CV = 0.15) indicates that the ecosystem remains subject to notable variability; (2) vegetation change displayed marked spatial heterogeneity, with significant improvement in the southeast and localized degradation in the northwest and developed areas. Significantly improved areas accounted for 66.7% of the study area, while significantly degraded areas accounted for 4.5%; and (3) national ecological programs, including the Grain for Green Program and the Three-North Shelterbelt Program, were identified as the leading human drivers of overall improvement. Mining, urban expansion, and transport infrastructure were associated with localized degradation, while interannual precipitation variability modulated vegetation stability. The findings quantify vegetation change over the study period and provide evidence to support the identification of priority conservation areas and differentiated ecological management in the Yellow River Basin.