Estimating Canopy Height at Scale

We propose a framework for global-scale canopy height estimation based on satellite data. Our model leverages advanced data preprocessing techniques, resorts to a novel loss function designed to counter geolocation inaccuracies inherent in the ground-truth height measurements, and employs data from the Shuttle Radar Topography Mission to effectively filter out erroneous labels in mountainous regions, enhancing the reliability of our predictions in those areas. A comparison between predictions and ground-truth labels yields an MAE/RMSE of 2. 43 / 4. 73 (meters) overall and 4. 45 / 6. 72 (meters) for trees taller than five meters, which depicts a substantial improvement compared to existing global-scale products. The resulting height map as well as the underlying framework will facilitate and enhance ecological analyses at a global scale, including, but not limited to, large-scale forest and biomass monitoring.

Authors

• Jan Pauls
• Max Zimmer
• Una M. Kelly
• Martin Schwartz
• Sassan Saatchi
• Philippe Ciais
• Sebastian Pokutta
• Martin Brandt
• Fabian Gieseke

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