Automatic identification of alpine mass movements by a combination of seismic and infrasound sensors

Open access
Date
2018-05Type
- Journal Article
Citations
Cited 17 times in
Web of Science
Cited 19 times in
Scopus
ETH Bibliography
yes
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Abstract
The automatic detection and identification of alpine mass movements such as debris flows, debris floods, or landslides have been of increasing importance for devising mitigation measures in densely populated and intensively used alpine regions. Since these mass movements emit characteristic seismic and acoustic waves in the low-frequency range (<30 Hz), several approaches have already been developed for detection and warning systems based on these signals. However, a combination of the two methods, for improving detection probability and reducing false alarms, is still applied rarely. This paper presents an update and extension of a previously published approach for a detection and identification system based on a combination of seismic and infrasound sensors. Furthermore, this work evaluates the possible early warning times at several test sites and aims to analyze the seismic and infrasound spectral signature produced by different sediment-related mass movements to identify the process type and estimate the magnitude of the event. Thus, this study presents an initial method for estimating the peak discharge and total volume of debris flows based on infrasound data. Tests on several catchments show that this system can detect and identify mass movements in real time directly at the sensor site with high accuracy and a low false alarm ratio. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000268450Publication status
publishedExternal links
Journal / series
SensorsVolume
Pages / Article No.
Publisher
MDPISubject
infrasound sensors; seismic sensors; debris flow; detection system; identification systemOrganisational unit
09558 - Walter, Fabian (ehemalig) / Walter, F. ((former))
Funding
157551 - Glacial Hazard Monitoring with Seismology (GlaHMSeis) (SNF)
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Show all metadata
Citations
Cited 17 times in
Web of Science
Cited 19 times in
Scopus
ETH Bibliography
yes
Altmetrics