Vegetation recovery assessment in green legacy initiative sites of Gubalafto district, Ethiopia, using Sentinel-2 and Google Earth Engine

Land and vegetation degradation remain persistent environmental challenges in Ethiopia. To address these impacts, the Ethiopian government has promoted large‑scale tree planting through the Green Legacy Initiative (GLI) since 2019. Given this national intervention, local-level quantitative evidence on ecological effectiveness remains lacking. Therefore, this study evaluated vegetation recovery at GLI sites in the Gubalafto District. The high-resolution Sentinel-2 imagery and conflict data (from 2016 to 2024) were processed in the Google Earth Engine (GEE) environment. Moreover, vegetation greening (NDVI) and moisture content (NDMI) were examined using Welch’s t-test and Pearson correlation across the 2024 GLI sites (n = 37 polygons). Results show that vegetation greenness increased significantly from 2016 to 2019 (+ 0.26, p < 0.001), followed by a decline in 2021 (-0.068) and 2024 (-0.187). These declines coincided with persistent moisture stress and escalating local conflict. The NDVI and NDMI were strongly correlated (r = 0.666–0.780, p < 0.001), confirming humidity availability as a key driver of restoration success. The moisture stress and conflict or disruption affect the socio-economic and ecological impact of the green legacy initiatives. For the successful restoration, the policymakers and practitioners should integrate the moisture-sensitive planning and conflict resolution mechanisms with GLI initiatives.