Hypocenter and focal mechanism of an earthquake can be determined by the analysis of signals, named waveforms, related to the wave field produced and recorded by a seismic network. Assuming that waveform similarity implies the similarity of focal parameters, the analysis of those signals characterized by very similar shapes can be used to give important details about the physical phenomena which have generated an earthquake. Recent works have shown the effectiveness of cross-correlation and/or cross-spectral dissimilarities to identify clusters of seismic events. In this work we propose a new dissimilarity measure between seismic signals whose reliability has been tested on real seismic data by computing external and internal validation indices on the obtained clustering. Results show its superior quality in terms of cluster homogeneity and computational time with respect to the largely adopted cross correlation dissimilarity

Benvegna, F., D'Alessandro, A., LO BOSCO, G., Luzio, D., Pinello, L., & Tegolo, D. (2011). A New Dissimilarity Measure for Clustering Seismic Signals. In G. Maino, & G.L. Foresti (a cura di), Image Analysis and Processing – ICIAP 2011 (pp. 434-443). Heidelberg : Springer Verlag [10.1007/978-3-642-24088-1_45].

A New Dissimilarity Measure for Clustering Seismic Signals

BENVEGNA, Francesco;D'ALESSANDRO, Antonino;LO BOSCO, Giosue';LUZIO, Dario;PINELLO, Luca;TEGOLO, Domenico
2011

Abstract

Hypocenter and focal mechanism of an earthquake can be determined by the analysis of signals, named waveforms, related to the wave field produced and recorded by a seismic network. Assuming that waveform similarity implies the similarity of focal parameters, the analysis of those signals characterized by very similar shapes can be used to give important details about the physical phenomena which have generated an earthquake. Recent works have shown the effectiveness of cross-correlation and/or cross-spectral dissimilarities to identify clusters of seismic events. In this work we propose a new dissimilarity measure between seismic signals whose reliability has been tested on real seismic data by computing external and internal validation indices on the obtained clustering. Results show its superior quality in terms of cluster homogeneity and computational time with respect to the largely adopted cross correlation dissimilarity
Settore INF/01 - Informatica
Settore GEO/11 - Geofisica Applicata
978-3-642-24087-4
Benvegna, F., D'Alessandro, A., LO BOSCO, G., Luzio, D., Pinello, L., & Tegolo, D. (2011). A New Dissimilarity Measure for Clustering Seismic Signals. In G. Maino, & G.L. Foresti (a cura di), Image Analysis and Processing – ICIAP 2011 (pp. 434-443). Heidelberg : Springer Verlag [10.1007/978-3-642-24088-1_45].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10447/60524
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