Open-Canopy: Towards Very High Resolution Forest Monitoring
Abstract
Estimating canopy height and its changes at meter resolution from satellite imagery is a significant challenge in computer vision with critical environmental applications. However, the lack of open-access datasets at this resolution hinders the reproducibility and evaluation of models. We introduce Open-Canopy, the first open-access, country-scale benchmark for very high-resolution (1.5 m) canopy height estimation, covering over 87,000 km2 across France with 1.5 m resolution satellite imagery and aerial LiDAR data. Additionally, we present Open-Canopy-, a benchmark for canopy height change detection between images from different years at tree level--a challenging task for current computer vision models. We evaluate state-of-the-art architectures on these benchmarks, highlighting significant challenges and opportunities for improvement. Our datasets and code are publicly available at https://github.com/fajwel/Open-Canopy.
Cite
Text
Fogel et al. "Open-Canopy: Towards Very High Resolution Forest Monitoring." Conference on Computer Vision and Pattern Recognition, 2025. doi:10.1109/CVPR52734.2025.00138Markdown
[Fogel et al. "Open-Canopy: Towards Very High Resolution Forest Monitoring." Conference on Computer Vision and Pattern Recognition, 2025.](https://mlanthology.org/cvpr/2025/fogel2025cvpr-opencanopy/) doi:10.1109/CVPR52734.2025.00138BibTeX
@inproceedings{fogel2025cvpr-opencanopy,
title = {{Open-Canopy: Towards Very High Resolution Forest Monitoring}},
author = {Fogel, Fajwel and Perron, Yohann and Besic, Nikola and Saint-André, Laurent and Pellissier-Tanon, Agnès and Schwartz, Martin and Boudras, Thomas and Fayad, Ibrahim and d'Aspremont, Alexandre and Landrieu, Loic and Ciais, Philippe},
booktitle = {Conference on Computer Vision and Pattern Recognition},
year = {2025},
pages = {1395-1406},
doi = {10.1109/CVPR52734.2025.00138},
url = {https://mlanthology.org/cvpr/2025/fogel2025cvpr-opencanopy/}
}