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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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Matthias Heck on behalf of the Authors (31 Oct 2018)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (14 Nov 2018) by Michael Dietze
RR by Florian Fuchs (11 Dec 2018)
RR by Anonymous Referee #4 (12 Dec 2018)
ED: Reconsider after major revisions (28 Dec 2018) by Michael Dietze
AR by Alec van Herwijnen on behalf of the Authors (22 Mar 2019)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (28 Mar 2019) by Michael Dietze
RR by Florian Fuchs (28 Mar 2019)
ED: Publish subject to technical corrections (01 Apr 2019) by Michael Dietze
ED: Publish subject to technical corrections (01 Apr 2019) by Niels Hovius (Editor)
AR by Alec van Herwijnen on behalf of the Authors (18 Apr 2019)  Manuscript 
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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.