Towards the automatic detection of seismic and infrasound signals generated by snow avalanches
Typ
Examensarbete för masterexamen
Program
Publicerad
2019
Författare
Hebbe, Alexander
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
Avalanches are the cause of many fatal accidents every winter in the European Alps.
Established procedures to forecast the regional avalanche danger level use data on the
weather, the snow cover and recent avalanche activity. Avalanche activity data is today
obtained by visual observations. As avalanches generally occur during snowstorms
when visibility is poor, these data are often incomplete in space and time. To solve this
issue, arrays of infrasound or seismic sensors can be deployed to monitor avalanches at
distances up to 4 kilometers, independent of visibility or time of day. Today, only infrasound
systems are used operationally to automatically localize and detect avalanches.
The main limitation of these systems is that only larger dry-snow avalanches can be detected,
as it is generally assumed that wet-snow or smaller avalanches do not generate
enough energetic infrasound signals. Since seismic signals are generated by a different
process than infrasound signals, seismic systems can be used to detect both dry- and
wet-snow avalanches. However, methods to automatically detect avalanches in near
real-time have not been established yet.
In this project, seismic and infrasound signals generated by avalanches from two
winter seasons were investigated at a field site above Davos, Switzerland. With an array
processing method, specifically a sliding window three dimensional beamforming
algorithm, it was possible to localize the source of avalanches and track changes over
time. The method worked for localizing avalanches from both infrasound and seismic
data. It was found that avalanches generate seismic activity for a longer duration and
that seismic sensors also record infrasound. Using a frequency-wavenumber-analysis
to apply a velocity filter to separate seismic and infrasound wave fields did not further
improve the accuracy of the localization method. To automatically detect avalanches,
18 parameters were derived based on the beamforming method and pattern recognition
procedures. For the testing season (2016-2017), 55% of all visually confirmed
avalanches were detected from the seismic data. The learning season (2017-2018) detected
100% of all visually confirmed avalanches from both seismic and infrasound data
with a low ratio of detected unassigned events. These results clearly suggest that automatic
detection of avalanches can also reliably be used on seismic data. Since the
processing method is computationally efficient, it could be implemented for near realtime
avalanche detection using seismic monitoring systems.
Beskrivning
Ämne/nyckelord
Infrasound; Seismic; signal processing; pattern recognition; automatic avalanche event detection; event localization; FK filter