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Trees outside forests

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Publications

We are very active in publishing our work. Here a selection, see Google Scholar for all studies.

High-resolution sensors and deep learning models for tree resource monitoring

Nature Reviews Electrical Engineering, 2025

We summarized our experiences gained over the past years.

A strong but uneven increase in urban tree cover in China over the recent decade

Nature Cities, 2025

We used RapidEye and PlanetScope to study tree cover changes over hundreds of cities in China over 2010-2019.

Severe decline in large farmland trees in India over recent decade

Nature Sustainability, 2024

We tracked 0.6 billion large trees from 2010 to 2022 and found that many disappeared.

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Forest classification

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Tree detection confidence is classified into contiguous forests, trees outside forests, and forest gaps. Can also be used as binary tree/no-tree mask.

Screenshot from 2026-03-10 09-01-53.png

Forest classification

________________________________

Tree detection confidence is classified into contiguous forests, trees outside forests, and forest gaps. Can also be used as binary tree/no-tree mask.

Screenshot from 2026-03-10 09-01-53.png

Forest classification

________________________________

Tree detection confidence is classified into contiguous forests, trees outside forests, and forest gaps. Can also be used as binary tree/no-tree mask.

Screenshot from 2026-03-10 09-01-53.png

Forest classification

________________________________

Tree detection confidence is classified into contiguous forests, trees outside forests, and forest gaps. Can also be used as binary tree/no-tree mask.

Screenshot from 2026-03-10 09-01-53.png

Forest classification

________________________________

Tree detection confidence is classified into contiguous forests, trees outside forests, and forest gaps. Can also be used as binary tree/no-tree mask.

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