Reforestation can help combat land degradation and mitigate climate change, particularly in semi-arid regions, but its success is difficult to assess because field data are limited, vegetation patterns are highly variable, and large-scale monitoring is costly. This project develops AI-based approaches to derive indicators such as tree density, biomass, and biodiversity from high-resolution drone and satellite imagery. By combining Earth observation, machine learning, and field data, the project aims to create scalable and transferable models for spatially explicit assessment of reforestation outcomes.