CVPR 2025highlight0 citations

Open-Canopy: Towards Very High Resolution Forest Monitoring

Fajwel Fogel, Yohann Perron, Nikola Besic, Laurent Saint-André, Agnès Pellissier-Tanon, Martin Schwartz, Thomas Boudras, Ibrahim Fayad

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.

BibTeX
@InProceedings{Fogel_2025_CVPR,
    author    = {Fogel, Fajwel and Perron, Yohann and Besic, Nikola and Saint-Andr\'e, Laurent and Pellissier-Tanon, Agn\`es and Schwartz, Martin and Boudras, Thomas and Fayad, Ibrahim and d'Aspremont, Alexandre and Landrieu, Loic and Ciais, Philippe},
    title     = {Open-Canopy: Towards Very High Resolution Forest Monitoring},
    booktitle = {Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR)},
    month     = {June},
    year      = {2025},
    pages     = {1395-1406}
}