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Monitoring Seismo-volcanic and Infrasonic Signals at Volcanoes: Mt. Etna Case Study

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TLDR
In this article, the authors describe analysis methods used to detect and locate seismo-volcanic and infrasonic signals at Mt. Etna using a method based on spatial seismic amplitude distribution, assuming propagation in a homogeneous medium.
Abstract
Volcanoes generate a broad range of seismo-volcanic and infrasonic signals, whose features and variations are often closely related to volcanic activity. The study of these signals is hence very useful in the monitoring and investigation of volcano dynamics. The analysis of seismo-volcanic and infrasonic signals requires specifically developed techniques due to their unique characteristics, which are generally quite distinct compared with tectonic and volcano-tectonic earthquakes. In this work, we describe analysis methods used to detect and locate seismo-volcanic and infrasonic signals at Mt. Etna. Volcanic tremor sources are located using a method based on spatial seismic amplitude distribution, assuming propagation in a homogeneous medium. The tremor source is found by calculating the goodness of the linear regression fit (R 2) of the log-linearized equation of the seismic amplitude decay with distance. The location method for long-period events is based on the joint computation of semblance and R 2 values, and the location method of very long-period events is based on the application of radial semblance. Infrasonic events and tremor are located by semblance–brightness- and semblance-based methods, respectively. The techniques described here can also be applied to other volcanoes and do not require particular network geometries (such as arrays) but rather simple sparse networks. Using the source locations of all the considered signals, we were able to reconstruct the shallow plumbing system (above sea level) during 2011.

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Citations
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Journal ArticleDOI

A comprehensive interpretative model of slow slip events on Mt. Etna's eastern flank

TL;DR: In this paper, the authors investigated the origin of the recently observed slow-slip events on the eastern flank of Mt. Etna and proposed a general kinematic model for the instability of this area of the volcano.
Journal ArticleDOI

Multiparametric study of the February-April 2013 paroxysmal phase of Mt. Etna New South-East crater

TL;DR: European FP7 MED-SUV (MEditerranean SUpersite Volcanoes) and SIGMA (Sistema Integrato di sensori in ambiente cloud per la Gestione Multirischio Avanzata)
Journal ArticleDOI

Pressurization and depressurization phases inside the plumbing system of Mount Etna volcano: Evidence from a multiparametric approach

TL;DR: In this paper, the authors mainly focus on the period between these cycles, applying a multiparametric approach, and they mainly interpret the variations as due to a gradual pressurization of the plumbing system, from the shallowest part, where LP and volcanic tremor are located, down to about 3-9 km below sea level, pressure source depths obtained by both geodetic and CO2 data.
Journal ArticleDOI

Space-Time Evolution of Magma Storage and Transfer at Mt. Etna Volcano (Italy): The 2015-2016 Reawakening of Voragine Crater

TL;DR: In this paper, the authors presented a grant for the University of Catania (Catania, Italy) with a grant number of 2F119B and grant number: PNRA14_00011, PRA 2016-18, 22722132120
References
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Book

The jackknife, the bootstrap, and other resampling plans

Bradley Efron
TL;DR: The Delta Method and the Influence Function Cross-Validation, Jackknife and Bootstrap Balanced Repeated Replication (half-sampling) Random Subsampling Nonparametric Confidence Intervals as mentioned in this paper.
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Long-period volcano seismicity: its source and use in eruption forecasting

TL;DR: At an active volcano, long-period seismicity reflects pressure fluctuations resulting from unsteady mass transport in the sub-surface plumbing system, and hence provides a glimpse of the internal dynamics of the volcanic edifice as mentioned in this paper.
Journal ArticleDOI

Semblance and other coherency measures for multichannel data

Norman S. Neidell, +1 more
- 01 Jun 1971 - 
TL;DR: In this article, the concept of semblance is introduced, along with a descriptive review of several of the more common likeness or coherence measures, including cross-correlation, which is related to an energy-normalized crosscorrelation and share certain features of the summation method or stack which has been used recently as a coherence measure.
Journal ArticleDOI

A comparison of select trigger algorithms for automated global seismic phase and event detection

TL;DR: While no algorithm was clearly optimal under all source, receiver, path, and noise conditions tested, an STA/LTA algorithm incorporating adaptive window lengths controlled by nonstationary seismogram spectral characteristics was found to provide an output that best met the requirements of a global correlated event-detection and location system.
Journal ArticleDOI

The Source‐Scanning Algorithm: mapping the distribution of seismic sources in time and space

TL;DR: The Source Scanning Algorithm (SSA) as discussed by the authors is a method for imaging the distribution of seismic sources in both time and space, using trial locations and origin times, the method calculates the "brightness" function by summing the absolute amplitudes observed at all stations at their respective predicted arrival times.
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