A large proportion of trees and shrubs are located outside of forests in peri-urban and rural dryland areas, playing a crucial role for the stability of the ecosystems, biodiversity, and providing food resources and shelter for humans and animals. However, no large scale assessment on individual trees and their density outside of forests exists. Here, this project applies deep learning on sub-meter resolution satellite imagery at continental scale, to map each woody plant and its characteristics (e.g. density, crown size) in hyper-arid, arid and semi-arid Africa, with a specific focus on the Sahara and Sahel. Furthermore, the environmental and social factors that determine the distribution, characteristics and functions of each tree and shrub are analyzed. Results will be stored in a publicly available spatial data-base including each woody plant outside forests in Africa, which is pivotal to understand their role in ecology, as carbon stocks, agroforestry, and in people’s livelihoods.