NDLI: Probabilistic Reasoning Over Seismic Time Series: Volcano Monitoring by Hidden Markov Models at Mt. Etna

Content Provider	Springer Nature Link
Author	Cassisi, Carmelo Prestifilippo, Michele Cannata, Andrea Montalto, Placido Patanè, Domenico Privitera, Eugenio
Copyright Year	2016
Abstract	From January 2011 to December 2015, Mt. Etna was mainly characterized by a cyclic eruptive behavior with more than 40 lava fountains from New South-East Crater. Using the RMS (Root Mean Square) of the seismic signal recorded by stations close to the summit area, an automatic recognition of the different states of volcanic activity (QUIET, PRE-FOUNTAIN, FOUNTAIN, POST-FOUNTAIN) has been applied for monitoring purposes. Since values of the RMS time series calculated on the seismic signal are generated from a stochastic process, we can try to model the system generating its sampled values, assumed to be a Markov process, using Hidden Markov Models (HMMs). HMMs analysis seeks to recover the sequence of hidden states from the observations. In our framework, observations are characters generated by the Symbolic Aggregate approXimation (SAX) technique, which maps RMS time series values with symbols of a pre-defined alphabet. The main advantages of the proposed framework, based on HMMs and SAX, with respect to other automatic systems applied on seismic signals at Mt. Etna, are the use of multiple stations and static thresholds to well characterize the volcano states. Its application on a wide seismic dataset of Etna volcano shows the possibility to guess the volcano states. The experimental results show that, in most of the cases, we detected lava fountains in advance.
Starting Page	2365
Ending Page	2386
Page Count	22
File Format	PDF
ISSN	00334553
Journal	Pure and applied geophysics
Volume Number	173
Issue Number	7
e-ISSN	14209136
Language	English
Publisher	Springer International Publishing
Publisher Date	2016-04-13
Publisher Place	Cham
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Volcano monitoring Explosive volcanism Time-series analysis Volcano seismology Probability distributions Geophysics/Geodesy
Content Type	Text
Resource Type	Article
Subject	Geochemistry and Petrology Geophysics

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