Automatic Quantification of Instream Large Wood Storage Combining Machine Learning and High-Resolution Aerial Imagery

Janbert Aarnink; Gabriele Consoli; Bryce Finch; Marc O'Callaghan; Ivan Pascal; Samuel Wiesmann; Virginia Ruiz-Villanueva

doi:https://doi.org/10.5194/egusphere-egu25-10295

[Back] [Session GM10.3]

EGU25-10295, updated on 15 Mar 2025

https://doi.org/10.5194/egusphere-egu25-10295

EGU General Assembly 2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Automatic Quantification of Instream Large Wood Storage Combining Machine Learning and High-Resolution Aerial Imagery

Janbert Aarnink

¹, Gabriele Consoli

¹, Bryce Finch¹, Marc O'Callaghan¹, Ivan Pascal¹, Samuel Wiesmann

³, and Virginia Ruiz-Villanueva²

Janbert Aarnink et al.

¹University of Lausanne, IDYST, RivES, Switzerland (janbert.aarnink@unil.ch)
²Institute of Geography, University of Bern, Switzerland
³Swiss National Park, Zernez, Switzerland

How to cite: Aarnink, J., Consoli, G., Finch, B., O'Callaghan, M., Pascal, I., Wiesmann, S., and Ruiz-Villanueva, V.: Automatic Quantification of Instream Large Wood Storage Combining Machine Learning and High-Resolution Aerial Imagery, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10295, https://doi.org/10.5194/egusphere-egu25-10295, 2025.

This abstract has been withdrawn on 25 Jul 2025.