Open-Canopy: Towards Very High Resolution Forest Monitoring

Estimating canopy height and its changes at meter resolution from satellite imagery remains a challenging computer vision task 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, countryscale benchmark for very high-resolution (1.5 m) canopy height estimation, covering over 87,000 km² across France with 1.5 m panchromatic resolution satellite imagery and aerial LiDAR data. Additionally, we present Open-Canopy-∆, a benchmark for canopy height reduction detection between images from different years at tree level-a difficult 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 . N N 50m 50m (a) VHR images, 1.5m (b) ALS height map, 1.5m (c) Ours, 1.5m MAE: 3.3m (d) Tolan † [67], 1.2m MAE: 4.3m (e) Schwartz † [61], 10m MAE: 6.4m (f) Liu † [37], 3m MAE: 6.9m (g) Potapov † [50], 30m MAE: 8.8m (h) Pauls † [47], 10m MAE: 9.0m (i) Lang [35], 10m MAE: 15.9m