Abstract: To investigate the long-term variation patterns and driving factors of vegetation vitality in Changting County within the context of soil erosion control in the red soil region of southern China, a long-term vegetation vitality dataset was constructed using Landsat imagery from 2000 to 2020. The Integrated Topographic Correction (ITC) model was applied to mitigate the impact of complex mountainous terrain, thereby enhancing the spectral consistency and classification accuracy of the imagery. High-precision identification of major vegetation types was achieved by integrating the Random Forest classification method. Furthermore, Theil-Sen trend analysis and the Mann-Kendall significance test were employed to reveal the spatiotemporal evolution characteristics of vegetation vitality in Changting County from 2000 to 2020. The Geodetector was utilized to analyze the dominant driving forces and interaction mechanisms underlying its spatial heterogeneity. The results indicate that among the four vegetation types, broad-leaved forests exhibited the highest vitality, followed by coniferous forests and bamboo forests with similar values, while shrub-grass communities showed the lowest vitality. All vegetation types demonstrated a fluctuating upward trend. The trends in key treatment areas and non-key treatment areas aligned with the overall county pattern. However, the vitality advantage of broad-leaved forests was more pronounced in key treatment areas, and regional differences in vegetation vitality were observed. Vegetation vitality across the county improved significantly, with areas showing a highly significant increase accounting for 52.17%. The recovery rate in key treatment areas exceeded that in non-key treatment areas. Topographic factors and vegetation type were the primary drivers of vegetation vitality change, while the influence of human activity factors has gradually increased, reflecting the dynamic interplay between ecological governance and socio-economic development.