Publication Date:
2013-04-18
Description:
Twenty-five lava fountains occurred on Mt. Etna from January 2011 to April 2012. In summer 2012
volcanic activity resumed in a milder form within the Bocca Nuova crater, before it came to an essential halt
in August 2012. All these unrests offer rich material for testing automatic procedures of data processing and
alert systems, running 24/7, in the context of volcano surveillance. We focus on the seismic background
radiation – volcanic tremor – which plays a key role in the monitoring of Mt. Etna. Since 2006 a multistation
alert system has been established in the INGV operative centre of Catania exploiting STA/LTA
ratios. Besides, also the spectral characteristics of the signal, which change correspondingly to the type of
volcanic activity, can be exploited for warning purposes. Here we apply Self Organizing Maps and Fuzzy
Clustering which offer an efficient way to visualize signal characteristics and its development with time. All
these techniques allow to identify early stages of eruptive events, and automatically flag a critical status
before this becomes evident in conventional monitoring techniques.
Changes of tremor characteristics are related to the position of the source of the signal. The location of
the sources exploits the distribution of the amplitudes across the seismic network. The locations were
extremely useful for warning, throughout both the flank eruption in 2008 as well as the 2011 lava fountains,
during which a clear migration of tremor sources towards the eruptive centres could be noticed in advance.
The location of the sources completes the picture of an imminent volcanic unrest, and corroborates early
warnings flagged by the changes of signal characteristics.
Real time data processing requires computational efficiency, robustness of the methods and stability of
data acquisition. The amplitude based multi-station approach is not sensitive to the failure of single stations
and therefore offers a good stability. The single station approach, exploiting unsupervised classification
techniques, limits logistic efforts, as only one or few key stations are necessary. Both strategies have proven
to be insensitive to disturbances (undesired transients like earthquakes, noise, short gaps in the continuous
data flow). False alarms were not encountered so far.
Stable data acquisition and processing come with a properly designed data storage solution. The
reliability of data storage and its access is a critical issue. A cluster architecture has been realized for failover
protection, including a Storage Area Network system, which allow easy data access following predefined
user policies. We present concepts of the software architectures deployed at INGV Osservatorio Etneo in
order to implement this tremor-based multi approach system. We envisage the integration of seismic data
and those originating from other scientific fields (e. g., volcano imagery, geochemistry, deformation, gravity,
magneto-telluric). This will facilitate cross-checking of evidences encountered from the single data streams,
in particular allow their immediate verification with respect to ground truth.
Description:
Published
Description:
Nicolosi (Catania, Italy)
Description:
1.4. TTC - Sorveglianza sismologica delle aree vulcaniche attive
Description:
5.6. TTC - Attività di Sala Operativa
Description:
open
Keywords:
Etna, Volcanic tremor
;
Volcano monitoring, Pattern recognition
;
Self Organizing Map, Fuzzy clustering
;
Data acquisition
;
04. Solid Earth::04.06. Seismology::04.06.06. Surveys, measurements, and monitoring
;
04. Solid Earth::04.06. Seismology::04.06.08. Volcano seismology
;
04. Solid Earth::04.08. Volcanology::04.08.06. Volcano monitoring
;
05. General::05.01. Computational geophysics::05.01.01. Data processing
;
05. General::05.01. Computational geophysics::05.01.04. Statistical analysis
Repository Name:
Istituto Nazionale di Geofisica e Vulcanologia (INGV)
Type:
Oral presentation
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