Abstract
Counting every tree because every tree counts This project aims towards a wall-to-wall identification of trees in global drylands and a study of their ecological services and socio-environmental determinants. The project will apply a new generation of satellite imagery at sub-metre resolution and extensive field data in conjunction with fully convolutional neural networks, a deep learning technique being able to identify objects within imagery at unprecedented accuracy. In doing so, we will lay the groundwork for new insights into the contribution of human agency and climate change to the distribution of dryland trees and their role in mitigating degradation, climate change and poverty.
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