  Estimating canopy height and canopy height change at meter resolution from
satellite imagery has numerous applications, such as monitoring forest health,
logging activities, wood resources, and carbon stocks. However, many existing
forest datasets are based on commercial or closed data sources, restricting the
reproducibility and evaluation of new approaches. To address this gap, we
introduce Open-Canopy, the first open-access and country-scale benchmark for
very high resolution (1.5 m) canopy height estimation. Covering more than
87,000 km$^2$ across France, Open-Canopy combines SPOT satellite imagery with
high resolution aerial LiDAR data. We also propose Open-Canopy-$\Delta$, the
first benchmark for canopy height change detection between two images taken at
different years, a particularly challenging task even for recent models. To
establish a robust foundation for these benchmarks, we evaluate a comprehensive
list of state-of-the-art computer vision models for canopy height estimation.
The dataset and associated codes can be accessed at
https://github.com/fajwel/Open-Canopy.
