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 km$^2$ across France with 1.5 m resolution satellite imagery and aerial LiDAR data. Additionally, we present Open-Canopy-$\Delta$, 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.
Open-Canopy: Towards Very High Resolution Forest Monitoring
Open-Canopy provides open-access canopy height and change detection benchmarks using satellite and LiDAR data, enabling evaluations of state-of-the-art computer vision models.
- Year
- 2024
- Venue
- CVPR 2025 1
- Authors
- 11
- Hosting
- Abstract onlyARXIV-DEFAULT
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- arxiv.org/abs/2407.09392v4ARXIV-DEFAULT
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