Articles | Volume 7, issue 2
https://doi.org/10.5194/esurf-7-491-2019
https://doi.org/10.5194/esurf-7-491-2019
Research article
 | 
03 Jun 2019
Research article |  | 03 Jun 2019

Automatic detection of avalanches combining array classification and localization

Matthias Heck, Alec van Herwijnen, Conny Hammer, Manuel Hobiger, Jürg Schweizer, and Donat Fäh

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Cited articles

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Esposito, A. M., Giudicepietro, F., Scarpetta, S., D’Auria, L., Marinaro, M., and Martini, M.: Automatic discrimination among landslide, explosion-quake and microtremor seismic signals at Stromboli Volcano using neural networks, B. Seismol. Soc. Am., 96, 1230, https://doi.org/10.1785/0120050097, 2006. a
Hammer, C., Beyreuther, M., and Ohrnberger, M.: A seismic-event spotting system for Volcano fast-response systems, B. Seismol. Soc. Am., 102, 948–960, https://doi.org/10.1785/0120110167, 2012. a, b
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Short summary
We used continuous seismic data from two small aperture geophone arrays deployed in the region above Davos in the eastern Swiss Alps to develop a machine learning workflow to automatically identify signals generated by snow avalanches. Our results suggest that the method presented could be used to identify major avalanche periods and highlight the importance of array processing techniques for the automatic classification of avalanches in seismic data.