Abstract: Hydropower is a crucial source of clean energy, yet the long construction period and broad impact range of hydropower stations result in significant uncertainties regarding their effects on surrounding vegetation. Based on MODIS Normalized Difference Vegetation Index (NDVI) and the utilization of the Google Earth Engine (GEE) as a computational platform, this study employed the LandTrendr algorithm to analyze the timing and magnitude of vegetation disturbance. Additionally, the Theil-Sen Median and Hurst index were combined to investigate the dynamic impacts of hydropower stations with different regulation modes on regional vegetation from 2000 to 2022 in the middle Jinsha River. The results revealed that: (1) The major change points in NDVI aligned with the respective dam's impoundment years (Guanyinyan: 2015; Rudila: 2013; Dragon's Mouth: 2013; Ah Hai: 2013). The influence range of weekly-regulated hydropower stations (0~13 km) was wider than that of daily-regulated stations (0~9 km), with a larger positive change area (37.21~54.53%) compared to daily-regulated stations (22.35~38.07%), which gradually diminished in intensity away from the riverbank; (2) From 2000 to 2022, NDVI of the four major hydropower stations generally exhibited an upward trend (0.001~0.004 per year), showing a cycle of "rise - fall - rise" before, during, and after the construction. The operation of hydropower stations facilitated the restoration of surrounding vegetation. The weekly-regulated stations demonstrated a greater positive impact on vegetation (NDVI increase rate of 0.007~0.008 per year) compared to the daily-regulated stations (NDVI increase rate of 0.005~0.007 per year); (3) Changes in vegetation around hydropower stations were influenced by both climate and station operation, and the latter having a more significant impact on vegetation than the former; (4) The impact of hydropower stations on surrounding vegetation displayed a spillover effect, indicating outward diffusion of negative impacts of spreading in the future, albeit with a delayed effect. This study provided a reliable scientific foundation and theoretical support for the sustainability of regional vegetation and the sustainable operation of hydropower stations.