We combine Machine Learning, Remote Sensing and Geography to discover unprecedented knowledge at the level of individual trees.​
We use PlanetScope, Sentinel-2, Landsat, Skysat, Maxar and Gaofen satellite images to produce detailed maps on tree locations, cover, biomass, and canopy height, from local to continental scale.​
View our maps!​​
Our work has been published in Nature, Nature Climate Change, Nature Sustainability, PNAS Nexus, Science Advances, Nature Plants, Nature Food, Nature Geoscience, Nature Ecology, Nature Communications, etc.​​​
Latest
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New study in Nature Cities studying urban trees with RapidEye and PlanetScope
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Nature Reviews: High-resolution sensors and deep learning models for tree resource monitoring.
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The Tree Explorer is regularly updated (all still experimental).
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We mapped about 3 million baobabs all over the Sahel, published in Nature Ecology.
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New paper at ECCV 2024 including codes and dataset
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New paper in Nature Sustainability also covered in "The Hindu".
Highly detailed
Homogeneous
Large Scale