Automatic detection of long-period events at Campi Flegrei Caldera (Italy)

Details Automatic detection of long-period events at Campi Flegrei Caldera (Italy) Automatic detection of long-period events at Campi Flegrei Caldera (Italy)

Sep 2011

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011georl..3818302c&link_type=abstract

Geophysical Research Letters, Volume 38, Issue 18, CiteID L18302

Statistics

Computation

Computational Geophysics: Data Analysis: Algorithms And Implementation, Computational Geophysics: Neural Networks, Fuzzy Logic, Machine Learning (1942), Informatics: Software Tools And Services, Seismology: Volcano Seismology (4302, 8419), Volcanology: Calderas

Scientific paper

We propose a novel approach to analyze continuous seismic signal and separate the sources from background noise. A specific application to the seismicity recorded at Campi Flegrei Caldera during the 2006 ground uplift is presented. The fundamental objective is to improve the standard procedures of picking the emergent onset arrivals of the seismic signals, often buried in the high-level ambient noise, in order to obtain an appropriate catalogue for monitoring the activity of this densely populated volcanic area. This is particularly useful in order to estimate the release of the seismic energy and to put constraints on the source dynamics. An Independent Component Analysis based approach for the Blind Source Separation of convolutive mixtures is adopted to obtain a clear separation of Long Period events from the ambient noise. The approach presents good performance and it is suitable for real time implementation in seismic monitoring. Its application to the continuous seismic signal recorded at Campi Flegrei has allowed the extraction of high-quality waveforms, considerably improving the detection of low-energy events.

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