EGU24-20213, updated on 11 Mar 2024
https://doi.org/10.5194/egusphere-egu24-20213
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

High-resolution mapping of tree mortality in European forests

Yan Cheng1, Stefan Oehmcke1, Clemens Mosig2, Beloiu Mirela3, Teja Kattenborn4, Christin Abel1, Dimitri Gominski1, Thomas Nord-Larsen1, Rasmus Fensholt1, and Stephanie Horion1
Yan Cheng et al.
  • 1University of Copenhagen, Copenhagen, Denmark (yach@ign.ku.dk)
  • 2Remote Sensing Centre for Earth System Research (RSC4Earth), Leipzig University, Leipzig, Germany
  • 3Institute of Terrestrial Ecosystems, ETH Zurich, Zurich, Switzerland
  • 4University of Freiburg, Freiburg, Germany

Tree mortality has escalated worldwide in recent years due to climate warming and unprecedented drought events. However, mapping tree mortality across forest ecosystems has not yet been achieved. Aerial photos provide opportunities to reveal the spatial and spectral characteristics of canopy death at local to landscape scales. In this work, we present a deep learning model for mapping tree mortality from aerial photos in various forested ecosystems across Europe. This model builds on a baseline model trained with data on dead tree canopies from California using sub-meter resolution aerial photos and allows the use of various spatial resolutions of the input images (ranging from 10 to 60 cm). By comparing our results to ground observations and/or state-of-the-art forest disturbance and loss products, we will discuss the advantages and limitations of aerial photo-based tree mortality mapping. The proposed framework can be used for large-scale mapping of tree mortality from multi-year aerial photos. The tree mortality maps provide detailed information that can help understand the mechanisms of tree mortality under climate change. Furthermore, aerial photo-based maps can serve as training labels for mapping pixel-level deadwood fractions from satellite images, which enables seamless spatial coverage and could be an essential step towards a global map of tree mortality. 

How to cite: Cheng, Y., Oehmcke, S., Mosig, C., Mirela, B., Kattenborn, T., Abel, C., Gominski, D., Nord-Larsen, T., Fensholt, R., and Horion, S.: High-resolution mapping of tree mortality in European forests, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20213, https://doi.org/10.5194/egusphere-egu24-20213, 2024.