Dissimilarity Measures for the Identification of Earthquake Focal Mechanisms

Domenico Tegolo, Giosue' Lo Bosco, Francesco Benvegna, Domenico Tegolo, Giosué Lo Bosco

Risultato della ricerca: Conference contribution

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 byclustering 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
Lingua originaleEnglish
Titolo della pubblicazione ospiteImage Analysis and Processing – ICIAP 2013
Pagine500-509
Numero di pagine10
Stato di pubblicazionePublished - 2013

Serie di pubblicazioni

NomeLECTURE NOTES IN COMPUTER SCIENCE

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cita questo

    Tegolo, D., Lo Bosco, G., Benvegna, F., Tegolo, D., & Lo Bosco, G. (2013). Dissimilarity Measures for the Identification of Earthquake Focal Mechanisms. In Image Analysis and Processing – ICIAP 2013 (pagg. 500-509). (LECTURE NOTES IN COMPUTER SCIENCE).