Estimating Canopy Height at Scale
<|reference_start|>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 maps. 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.<|reference_end|>
@article{pauls2024estimating,
    title={Estimating Canopy Height at Scale},
    author={Jan Pauls, Max Zimmer, Una M. Kelly, Martin Schwartz, Sassan Saatchi,
  Philippe Ciais, Sebastian Pokutta, Martin Brandt, Fabian Gieseke},
    journal={arXiv preprint arXiv:2406.01076},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.01076},
    primaryClass={cs.CV cs.AI cs.LG}
}