Open-Canopy: Towards Very High Resolution Forest Monitoring

TL;DR

This paper introduces Open-Canopy, the first open-access high-resolution satellite dataset for forest canopy height estimation and change detection, enabling reproducible research and benchmarking in environmental monitoring.

Contribution

It provides the first large-scale, open-access dataset for very high-resolution forest canopy height and change detection, facilitating advancements in remote sensing and computer vision.

Findings

State-of-the-art models face significant challenges on the benchmarks.

Open-Canopy enables reproducible research in forest monitoring.

The dataset covers over 87,000 km² across France.

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 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.