Articles | Volume 18, issue 22
https://doi.org/10.5194/gmd-18-8751-2025
https://doi.org/10.5194/gmd-18-8751-2025
Development and technical paper
 | 
20 Nov 2025
Development and technical paper |  | 20 Nov 2025

Autoencoder-based feature extraction for the automatic detection of snow avalanches in seismic data

Andri Simeon, Cristina Pérez-Guillén, Michele Volpi, Christine Seupel, and Alec van Herwijnen

Viewed

Total article views: 1,506 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
996 357 153 1,506 61 96
  • HTML: 996
  • PDF: 357
  • XML: 153
  • Total: 1,506
  • BibTeX: 61
  • EndNote: 96
Views and downloads (calculated since 27 May 2024)
Cumulative views and downloads (calculated since 27 May 2024)

Viewed (geographical distribution)

Total article views: 1,506 (including HTML, PDF, and XML) Thereof 1,497 with geography defined and 9 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 20 Nov 2025
Download
Short summary
Avalanche detection systems are crucial for forecasting, but distinguishing avalanches from other seismic sources remains a challenge. We propose novel autoencoder models to automatically extract features and compare them with engineered seismic features. These features are then used to classify avalanches and noise events. The autoencoder feature classifiers exhibit the highest sensitivity in detecting avalanches, while the engineered seismic classifier performs better overall.
Share