Articles | Volume 26, issue 6
https://doi.org/10.5194/nhess-26-2921-2026
https://doi.org/10.5194/nhess-26-2921-2026
Research article
 | 
25 Jun 2026
Research article |  | 25 Jun 2026

Exploring seismic mass-movement data with anomaly detection and dynamic time warping

Francois Kamper, Fabian Walter, Patrick Paitz, Matthias Meyer, Michele Volpi, and Mathieu Salzmann

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Latest update: 25 Jun 2026
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Short summary
We use anomaly detection to automatically find patterns in seismic data that may signal dangerous mass-movement events such as landslides, glacier collapses, or debris flows. Because such movements are rare, our approach reduces the amount of data that must be analyzed to find them, whether by experts, semi-supervised methods or clustering procedures. We demonstrate the usefulness of our approach by mining for mass movements in Switzerland and Greenland.
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