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Poster

Estimating Canopy Height at Scale

Jan Pauls · Max Zimmer · Una Kelly · Martin Schwartz · Sassan Saatchi · Philippe CIAIS · Sebastian Pokutta · Martin Brandt · Fabian Gieseke

Hall C 4-9 #412
[ ] [ Project Page ] [ Paper PDF ]
[ Poster
Tue 23 Jul 2:30 a.m. PDT — 4 a.m. PDT

Abstract:

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.

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