Journal cover Journal topic
Earth Surface Dynamics An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 3.765 IF 3.765
  • IF 5-year value: 3.719 IF 5-year
    3.719
  • CiteScore value: 3.83 CiteScore
    3.83
  • SNIP value: 1.281 SNIP 1.281
  • IPP value: 3.61 IPP 3.61
  • SJR value: 1.527 SJR 1.527
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 17 Scimago H
    index 17
  • h5-index value: 18 h5-index 18
ESurf | Articles | Volume 7, issue 2
Earth Surf. Dynam., 7, 491–503, 2019
https://doi.org/10.5194/esurf-7-491-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue: From process to signal – advancing environmental...

Earth Surf. Dynam., 7, 491–503, 2019
https://doi.org/10.5194/esurf-7-491-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 03 Jun 2019

Research article | 03 Jun 2019

Automatic detection of avalanches combining array classification and localization

Matthias Heck et al.
Viewed  
Total article views: 1,134 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
879 236 19 1,134 14 16
  • HTML: 879
  • PDF: 236
  • XML: 19
  • Total: 1,134
  • BibTeX: 14
  • EndNote: 16
Views and downloads (calculated since 03 May 2018)
Cumulative views and downloads (calculated since 03 May 2018)
Viewed (geographical distribution)  
Total article views: 1,077 (including HTML, PDF, and XML) Thereof 1,073 with geography defined and 4 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited  
Saved (final revised paper)  
No saved metrics found.
Saved (discussion paper)  
No saved metrics found.
Discussed (final revised paper)  
No discussed metrics found.
Discussed (discussion paper)  
No discussed metrics found.
Latest update: 05 Dec 2019
Publications Copernicus
Download
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.
We used continuous seismic data from two small aperture geophone arrays deployed in the region...
Citation