This work presents a study about dissimilarity measures for seismic signals, and their relation to clustering in the particular problem of the identification of earthquake focal mechanisms, i.e. the physical phenomena which have generated an earthquake. Starting from the assumption that waveform similarity implies similarity in the focal parameters, important details about them can be determined by studying waveforms related to the wave field produced by earthquakes and recorded by a seismic network. Focal mechanisms identification is currently investigated by clustering of seismic events, using mainly cross-correlation dissimilarity in conjunction with hierarchical clustering algorithm. By the way, it results that such adoptions have not been sufficiently validated. To shed light on this we have studied the cross correlation dissimilarity on simulated seismic signals in conjunction with hierarchical and partitional clustering algorithms, and compared its performance with a newly one recently introduced for the purpose called cumulative shape. In particular, we have properly created synthetic waveforms related to two types of focal mechanisms, showing that the cumulative shape perform better than cross-correlation in the identification of the expected clustering solution

Benvegna, F., Lo Bosco, G., Tegolo, D. (2013). Dissimilarity Measures for the Identification of Earthquake Focal Mechanisms. In A. Petrosino (a cura di), Image Analysis and Processing – ICIAP 2013 (pp. 500-509). Berlin : Springer [10.1007/978-3-642-41184-7_51].

Dissimilarity Measures for the Identification of Earthquake Focal Mechanisms

LO BOSCO, Giosue';TEGOLO, Domenico
2013-01-01

Abstract

This work presents a study about dissimilarity measures for seismic signals, and their relation to clustering in the particular problem of the identification of earthquake focal mechanisms, i.e. the physical phenomena which have generated an earthquake. Starting from the assumption that waveform similarity implies similarity in the focal parameters, important details about them can be determined by studying waveforms related to the wave field produced by earthquakes and recorded by a seismic network. Focal mechanisms identification is currently investigated by clustering of seismic events, using mainly cross-correlation dissimilarity in conjunction with hierarchical clustering algorithm. By the way, it results that such adoptions have not been sufficiently validated. To shed light on this we have studied the cross correlation dissimilarity on simulated seismic signals in conjunction with hierarchical and partitional clustering algorithms, and compared its performance with a newly one recently introduced for the purpose called cumulative shape. In particular, we have properly created synthetic waveforms related to two types of focal mechanisms, showing that the cumulative shape perform better than cross-correlation in the identification of the expected clustering solution
2013
978-3-642-41183-0
Benvegna, F., Lo Bosco, G., Tegolo, D. (2013). Dissimilarity Measures for the Identification of Earthquake Focal Mechanisms. In A. Petrosino (a cura di), Image Analysis and Processing – ICIAP 2013 (pp. 500-509). Berlin : Springer [10.1007/978-3-642-41184-7_51].
File in questo prodotto:
File Dimensione Formato  
81570500.pdf

accesso aperto

Tipologia: Versione Editoriale
Dimensione 306.08 kB
Formato Adobe PDF
306.08 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/83705
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
social impact