Articles | Volume 12, issue 3
https://doi.org/10.5194/esurf-12-641-2024
https://doi.org/10.5194/esurf-12-641-2024
Research article
 | 
03 May 2024
Research article |  | 03 May 2024

Machine learning prediction of the mass and the velocity of controlled single-block rockfalls from the seismic waves they generate

Clément Hibert, François Noël, David Toe, Miloud Talib, Mathilde Desrues, Emmanuel Wyser, Ombeline Brenguier, Franck Bourrier, Renaud Toussaint, Jean-Philippe Malet, and Michel Jaboyedoff

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Latest update: 17 Jun 2024
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Short summary
Natural disasters such as landslides and rockfalls are mostly difficult to study because of the impossibility of making in situ measurements due to their destructive nature and spontaneous occurrence. Seismology is able to record the occurrence of such events from a distance and in real time. In this study, we show that, by using a machine learning approach, the mass and velocity of rockfalls can be estimated from the seismic signal they generate.