EGU24-5792, updated on 08 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Improving forest disturbance labels through Sentinel-1 change detection validation

Franziska Müller1, Laura Eifler1, Felix Cremer1, Vitus Benson1, Gustau Camps-Valls2, and Ana Bastos1
Franziska Müller et al.
  • 1Max-Planck-Institute of Biogeochemistry, Dept. Biogeochemical Integration, Jena, Germany
  • 2University of Valencia, Valencia, Spain

Global forest ecosystems face unprecedented challenges, such as fire, wind, drought, and insect outbreaks, resulting in rapid forest decline. Analyzing these disturbances on a large scale requires the use of remote sensing techniques, but the spatial and temporal uncertainty in forest disturbance reference data poses a significant obstacle.

In this study, we validate and refine existing disturbance labels of the U.S. Forest Service Forest Health Protection [1] Dataset USDA by using a change detection algorithm [2] based on radar data from Sentinel-1. To this end, we analyze the spatio-temporal overlap of disturbed areas from Sentinel-1 with the USDA labels and further explore spatio-temporal fingerprints of remote sensing indices commonly used for disturbance detection. As the analysis of the remote sensing indices shows, this refinement of the accuracy of disturbance labels provides a more reliable basis for ecological research and land management practice.



[1] Coleman, T. W., Graves, A. D., Heath, Z., Flowers, R. W., Hanavan, R. P., Cluck, D. R., & Ryerson, D. (2018). Accuracy of aerial detection surveys for mapping insect and disease disturbances in the United States. Forest Ecology and Management, 430, 321–336.

[2] Cremer, F., Gans, F., Cortes, J. & Thiel, C. (2023). Mapping Forest Loss in Europe with Sentinel-1. In European Commission, Joint Research Centre, Soille, P., Lumnitz, S., Albani, S., Proceedings of the 2023 conference on Big Data from Space (BiDS’23) – From foresight to impact – 6-9 November 2023, Austrian Center, Vienna, Soille, P.(editor), Lumnitz, S.(editor), Albani, S.(editor), (pp. 361 - 364) Publications Office of the European Union, 2023,


How to cite: Müller, F., Eifler, L., Cremer, F., Benson, V., Camps-Valls, G., and Bastos, A.: Improving forest disturbance labels through Sentinel-1 change detection validation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5792,, 2024.