Item: Automatically Finding Avalanches in Geophone Data: A Pattern Recognition Workflow
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Title: Automatically Finding Avalanches in Geophone Data: A Pattern Recognition Workflow
Proceedings: Proceedings, 2012 International Snow Science Workshop, Anchorage, Alaska
Authors:
- Marc J. Rubin [ Dept. of Electrical Engineering and Computer Science, Colorado School of Mines, Golden, CO, USA ]
- Tracy Camp [ Dept. of Electrical Engineering and Computer Science, Colorado School of Mines, Golden, CO, USA ]
- Alec van Herwijnen [ WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland ]
Date: 2012
Abstract: In this article we summarize a pattern recognition workflow to automatically detect avalanche events from passive seismic data collected from geophones near Davos, Switzerland during the 2010-2011 snow season. Our workflow consists of three steps: 1) spectral flux based event selection, 2) feature extraction, and 3) classification. The results are quite promising: our workflow achieves 93% overall classification accuracy with 13% precision for detecting avalanches for the entire season.
Object ID: issw-2012-989-992.pdf
Language of Article: English
Presenter(s): unknown
Keywords: avalanche detection, danger level, avalanche forecasting
Page Number(s): 989-992
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