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Clustering of Hybrid Events at Stromboli Volcano (Italy)
Type
Conference paper
Language
English
Obiettivo Specifico
1.4. TTC - Sorveglianza sismologica delle aree vulcaniche attive
Status
Published
Conference Name
Issued date
June 3, 2011
Conference Location
Vietri sul Mare, Salerno
Keywords
Abstract
The last effusive eruption on February 27, 2007 at Stromboli volcano
was characterized by the occurrence of a particular typology of seismic events
named “hybrids”. During March about 4000 of these signals were recorded, and
three main swarms happened: the first one on days 6-8, with more than 1200
events; the second one on day 20, with more than 400 events; and the third one on
day 22, with about 600 events. The study of these events and specifically their
location is the main purpose of this work because it not only characterizes a
particular aspect of the 2007 effusive eruption but at the same time can improve
the understanding of the eruptive processes of the volcano. Thus, in order to locate
them it was first necessary to group the signals according to their waveform
similarity and then apply relative location techniques on individual families. To
perform the clustering an unsupervised SOM neural network was used. This
technique is capable of working without any “a-priori” information about data
distribution and structure. Its results have revealed differences in the families of
events recorded during and between the swarms, underlying from a volcanological
point different locations or source mechanisms of the involved structures.
Moreover, they have shown to be consistent compared to those obtained by
applying the Hierarchical Clustering technique. However, in contrast to the latter,
the SOM clustering does not critically depend on its parameters and allows for an
easier result visualization and interpretation.
was characterized by the occurrence of a particular typology of seismic events
named “hybrids”. During March about 4000 of these signals were recorded, and
three main swarms happened: the first one on days 6-8, with more than 1200
events; the second one on day 20, with more than 400 events; and the third one on
day 22, with about 600 events. The study of these events and specifically their
location is the main purpose of this work because it not only characterizes a
particular aspect of the 2007 effusive eruption but at the same time can improve
the understanding of the eruptive processes of the volcano. Thus, in order to locate
them it was first necessary to group the signals according to their waveform
similarity and then apply relative location techniques on individual families. To
perform the clustering an unsupervised SOM neural network was used. This
technique is capable of working without any “a-priori” information about data
distribution and structure. Its results have revealed differences in the families of
events recorded during and between the swarms, underlying from a volcanological
point different locations or source mechanisms of the involved structures.
Moreover, they have shown to be consistent compared to those obtained by
applying the Hierarchical Clustering technique. However, in contrast to the latter,
the SOM clustering does not critically depend on its parameters and allows for an
easier result visualization and interpretation.
References
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Stromboli volcano (Italy) reconstructed from direct observations and surveys with a handheld thermal
camera, J. Geoph. Res. 110, B02201, (2005) DOI:10.1029/2004JB003129.
[2] W. De Cesare, M. Orazi, R. Peluso, G. Scarpato, A. Caputo, L. D’Auria, F. Giudicepietro, M. Martini, C.
Buonocunto, M. Capello, A. M. Esposito, The broadband seismic network of Stromboli volcano, Italy,
Seismol. Res. Lett. 80 (2009) 435-439; doi: 10.1785/gssrl.80.3.435.
[3] A. M. Esposito, S. Scarpetta, Giudicepietro F., S. Masiello, L. Pugliese, A. Esposito, Nonlinear
Exploratory Data Analysis Applied to Seismic Signals, B. Apolloni et al. (Eds.): WIRN/NAIS 2005,
LNCS 3931, Springer-Verlag Berlin Heidelberg 2006, 70-77.
[4] A. M. Esposito, F. Giudicepietro, S. Scarpetta, L. D’Auria, M. Marinaro, M. Martini, Automatic
discrimination among landslide, explosion-quake and microtremor seismic signals at Stromboli volcano
using Neural Networks, Bull Seismol. Soc. Am. (BSSA), 96, N. 4° (2006) 1230-1240, doi:
10.1785/0120050097.
[5] B. Everitt, S. Landau, M. Leese, Cluster Analysis, Oxford University Press, New York (2001).
[6] F. Giudicepietro, D. Lo Bascio, T. Caputo, L. D’Auria, Drum_Pkev: un programma per la costituzione di
cataloghi supervisionati di eventi sismici ad elevata frequenza di accadimento, Rapporti Tecnici NGV,
Numero 124 (2010).
[7] E. I. Gordeev, S.L. Senyukov, Seismic activity at Koryakski Volcano in 1994: hybrid seismic events and
their implications for forecasting volcanic activity, J. Volcanol. Geotherm. Res. 128 (1-3) (2003) 225-
232.
10
[8] R. M. Harrington and E. E. Brodsky, Volcanic hybrid earthquakes that are brittle-failure events, Geoph.
Res. Lett. 34, L06308, doi:10.1029/2006GL028714 (2007).
[9] S. C. Johnson, Hierarchical Clustering Schemes, Psychometrika, 2:241-254 (1967).
[10] T. Kohonen, Self Organizing Maps, Springer-Verlag, 1995.
[11] T. Kohonen, J. Hynninen, J. Kangas, J. Laaksonen, SOM_PAK: The self-organizing map program
package, Report A31, Helsinki University of Technology, Laboratory of Computer and Information
Science, Espoo, Finland (1996) (http://www.cis.hut.fi/research/som_lvq_pak.shtml).
[12] T. Kohonen, Self-Organizing Maps, Series in Information Sciences 30. Springer, Heidelberg. Second
ed. (1997).
[13] M. Martini, F. Giudicepietro, L. D’Auria, A.M. Esposito, T. Caputo, R. Curciotti, W. De Cesare, M.
Orazi, G. Scarpato, A. Caputo, R. Peluso, P. Ricciolino, A. Linde, S. Sacks, Seismological monitoring
of the Feb. 2007 effusive eruption of the Stromboli volcano, Ann. Geophys. 50 (2007) 775-788.
[14] M. Mattia, M. Aloisi, G. Di Grazia, S. Gambino, M. Palano, V. Bruno, Geophysical investigations of
the plumbing system of Stromboli volcano (Aeolian Islands, Italy), J. Volcanol. Geotherm. Res. 176
(2008) 529-540.
[15] S. A. Mingoti, J. O. Lima, Comparing SOM neural network with Fuzzy c-means, K-means and
traditional hierarchical clustering algorithms, In European Journal of Operational Research 174, 1742-
1750, Elsevier, Amsterdam (2006).
[16] E. V. Samsonova, T. Back, J. N. Kok, A. P. IJzerman, Reliable Hierarchical Clustering with the Self-
Organizing Map, In Proceeding of the 6th International Conference on Intelligent Data Analysis, 385-
396, Madrid, Spain (2005).
[17] F. Waldhauser and W. L. Ellsworth, A Double-Difference Earthquake Location Algorithm: Method and
Application to the Northern Hayward Fault, California, Bull. Seismol. Soc. Am. (BSSA), 90, 6 (2000)
1353-1368.
[18] J. Wassermann, Volcano Seismology, CHAPTER 13 in New Manual of Seismological Observatory
Practice (2002), revised version, Library Wissenschaftspark Albert Einstein, electronically published
2009.
Stromboli volcano (Italy) reconstructed from direct observations and surveys with a handheld thermal
camera, J. Geoph. Res. 110, B02201, (2005) DOI:10.1029/2004JB003129.
[2] W. De Cesare, M. Orazi, R. Peluso, G. Scarpato, A. Caputo, L. D’Auria, F. Giudicepietro, M. Martini, C.
Buonocunto, M. Capello, A. M. Esposito, The broadband seismic network of Stromboli volcano, Italy,
Seismol. Res. Lett. 80 (2009) 435-439; doi: 10.1785/gssrl.80.3.435.
[3] A. M. Esposito, S. Scarpetta, Giudicepietro F., S. Masiello, L. Pugliese, A. Esposito, Nonlinear
Exploratory Data Analysis Applied to Seismic Signals, B. Apolloni et al. (Eds.): WIRN/NAIS 2005,
LNCS 3931, Springer-Verlag Berlin Heidelberg 2006, 70-77.
[4] A. M. Esposito, F. Giudicepietro, S. Scarpetta, L. D’Auria, M. Marinaro, M. Martini, Automatic
discrimination among landslide, explosion-quake and microtremor seismic signals at Stromboli volcano
using Neural Networks, Bull Seismol. Soc. Am. (BSSA), 96, N. 4° (2006) 1230-1240, doi:
10.1785/0120050097.
[5] B. Everitt, S. Landau, M. Leese, Cluster Analysis, Oxford University Press, New York (2001).
[6] F. Giudicepietro, D. Lo Bascio, T. Caputo, L. D’Auria, Drum_Pkev: un programma per la costituzione di
cataloghi supervisionati di eventi sismici ad elevata frequenza di accadimento, Rapporti Tecnici NGV,
Numero 124 (2010).
[7] E. I. Gordeev, S.L. Senyukov, Seismic activity at Koryakski Volcano in 1994: hybrid seismic events and
their implications for forecasting volcanic activity, J. Volcanol. Geotherm. Res. 128 (1-3) (2003) 225-
232.
10
[8] R. M. Harrington and E. E. Brodsky, Volcanic hybrid earthquakes that are brittle-failure events, Geoph.
Res. Lett. 34, L06308, doi:10.1029/2006GL028714 (2007).
[9] S. C. Johnson, Hierarchical Clustering Schemes, Psychometrika, 2:241-254 (1967).
[10] T. Kohonen, Self Organizing Maps, Springer-Verlag, 1995.
[11] T. Kohonen, J. Hynninen, J. Kangas, J. Laaksonen, SOM_PAK: The self-organizing map program
package, Report A31, Helsinki University of Technology, Laboratory of Computer and Information
Science, Espoo, Finland (1996) (http://www.cis.hut.fi/research/som_lvq_pak.shtml).
[12] T. Kohonen, Self-Organizing Maps, Series in Information Sciences 30. Springer, Heidelberg. Second
ed. (1997).
[13] M. Martini, F. Giudicepietro, L. D’Auria, A.M. Esposito, T. Caputo, R. Curciotti, W. De Cesare, M.
Orazi, G. Scarpato, A. Caputo, R. Peluso, P. Ricciolino, A. Linde, S. Sacks, Seismological monitoring
of the Feb. 2007 effusive eruption of the Stromboli volcano, Ann. Geophys. 50 (2007) 775-788.
[14] M. Mattia, M. Aloisi, G. Di Grazia, S. Gambino, M. Palano, V. Bruno, Geophysical investigations of
the plumbing system of Stromboli volcano (Aeolian Islands, Italy), J. Volcanol. Geotherm. Res. 176
(2008) 529-540.
[15] S. A. Mingoti, J. O. Lima, Comparing SOM neural network with Fuzzy c-means, K-means and
traditional hierarchical clustering algorithms, In European Journal of Operational Research 174, 1742-
1750, Elsevier, Amsterdam (2006).
[16] E. V. Samsonova, T. Back, J. N. Kok, A. P. IJzerman, Reliable Hierarchical Clustering with the Self-
Organizing Map, In Proceeding of the 6th International Conference on Intelligent Data Analysis, 385-
396, Madrid, Spain (2005).
[17] F. Waldhauser and W. L. Ellsworth, A Double-Difference Earthquake Location Algorithm: Method and
Application to the Northern Hayward Fault, California, Bull. Seismol. Soc. Am. (BSSA), 90, 6 (2000)
1353-1368.
[18] J. Wassermann, Volcano Seismology, CHAPTER 13 in New Manual of Seismological Observatory
Practice (2002), revised version, Library Wissenschaftspark Albert Einstein, electronically published
2009.
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