Unsupervised Neural Analysis of Very-Long-Period Events at Stromboli Volcano Using the Self-Organizing Maps
Author(s)
Language
English
Obiettivo Specifico
1.4. TTC - Sorveglianza sismologica delle aree vulcaniche attive
Status
Published
JCR Journal
JCR Journal
Peer review journal
No
Issue/vol(year)
5/98(2008)
Publisher
Seismological Society of America
Pages (printed)
2449–2459
Date Issued
2008
Abstract
We have implemented a method based on an unsupervised neural network
to cluster the waveforms of very-long-period (VLP) events associated with
explosive activity at the Stromboli volcano (southern Italy). Stromboli has several
active vents in the summit area producing together more than 200 explosions=day.
We applied this method to investigate the relationship between each vent and its associated
VLP explosive waveform.
We selected 147 VLP events recorded between November and December 2005,
when digital infrared camera recordings were available. From a visual inspection of
the infrared camera images, we classified the VLPs on the basis of which vent produced
each explosion. We then applied the self-organizing map (SOM), an unsupervised
neural technique widely applied in data exploratory analysis, to cluster the VLPs
on the basis of their waveform similarity.
Our analysis demonstrates that the most recurrent VLP waveforms are usually
generated by the same vent. Some exceptions occurred, however, in which different
waveforms are associated with the same vent, as well as different vents generating
similar waveforms. This suggests that the geometry of the upper conduit-vent system
plays a role in shaping the recurring VLP events, whereas occasional modest changes
in the source process dynamics produce the observed exceptions.
to cluster the waveforms of very-long-period (VLP) events associated with
explosive activity at the Stromboli volcano (southern Italy). Stromboli has several
active vents in the summit area producing together more than 200 explosions=day.
We applied this method to investigate the relationship between each vent and its associated
VLP explosive waveform.
We selected 147 VLP events recorded between November and December 2005,
when digital infrared camera recordings were available. From a visual inspection of
the infrared camera images, we classified the VLPs on the basis of which vent produced
each explosion. We then applied the self-organizing map (SOM), an unsupervised
neural technique widely applied in data exploratory analysis, to cluster the VLPs
on the basis of their waveform similarity.
Our analysis demonstrates that the most recurrent VLP waveforms are usually
generated by the same vent. Some exceptions occurred, however, in which different
waveforms are associated with the same vent, as well as different vents generating
similar waveforms. This suggests that the geometry of the upper conduit-vent system
plays a role in shaping the recurring VLP events, whereas occasional modest changes
in the source process dynamics produce the observed exceptions.
References
Auger, E., L. D’Auria, M. Martini, B. Chouet, and P. Dawson (2006). Realtime
monitoring and massive inversion of source parameters of very
long period seismic signals: an application to Stromboli volcano, Italy,
Geophys. Res. Lett. 33, L04301, doi 10.1029/2005GL024703.
Bertagnini, A., M. Coltelli, P. Landi, M. Pompilio, and M. Rosi (1999). Violent
explosions yield new insights into dynamics of Stromboli volcano,
Eos Trans. AGU 80 no. 52, 633–636, doi 10.1029/99EO00415.
Calvari, S., L. Spampinato, L. Lodato, A. J. L. Harris, M. R. Patrick, J. Dehn,
M. R. Burton, and D. Andronico (2005). Chronology and complex
volcanic processes during the 2002–2003 flank eruption at Stromboli
volcano (Italy) reconstructed from direct observations and surveys with a handheld thermal camera, J. Geophys. Res. 110, B02201,
doi 10.1029/2004JB003129.
Cercone, J. M., and J. R. Martin (1994). An application of neural networks to
seismic signal discrimination, Phillips Laboratory Report No. 3,
PL-TR-94-2178, Hanscon Air Force Base, Massachusetts.
Chouet, B., G. De Luca, G. Milana, P. Dawson, M. Martini, and R. Scarpa
(1998). Shallow velocity structure of Stromboli volcano, Italy, derived
from small-aperture array measurements of Strombolian tremor, Bull.
Seismol. Soc. Am. 88, no. 3, 653–666.
Chouet, B., G. Saccorotti, P. Dawson, M. Martini, R. Scarpa, G. De Luca, G.
Milana, and M. Cattaneo (1999). Broadband measurements of the
sources of explosions at Stromboli volcano, Italy, Geophys. Res. Lett.
26, no. 13, 1937.
Chouet, B., P. Dawson, T. Ohminato, M. Martini, G. Saccorotti, F. Giudicepietro,
G. De Luca, G. Milana, and R. Scarpa (2003). Source
mechanisms of explosions at Stromboli volcano, Italy, determined
from moment-tensor inversions of very-long-period data, J. Geophys.
Res. 108 no. B1, 2019, doi 10.1029/2002JB001919.
D’Auria, L., F. Giudicepietro, M. Martini, and R. Peluso (2006). Seismological
insight into the kinematics of the 5 April 2003 vulcanian explosion
at Stromboli volcano (southern Italy), Geophys. Res. Lett. 33,
L08308, doi 10.1029/2006GL026018.
Del Pezzo, E., A. Esposito, F. Giudicepietro, M. Marinaro, M. Martini, and
S. Scarpetta (2003). Discrimination of earthquakes and underwater
explosions using neural networks, Bull. Seismol. Soc. Amer. 93,
no. 1, 215–223.
Dowla, F. U. (1995). Neural networks in seismic discrimination, in Monitoring
a Comprehensive Test Ban Treaty, in NATO ASI, Series E E. S.Husebye and A. M. Dainty (Editors), Vol. 303, Kluwer, Dordrecht,
777–789.
Dowla, F. U., S. R. Taylor, and R. W. Anderson (1990). Seismic discrimination
with artificial neural networks: preliminary results with regional
spectral data, Bull. Seismol. Soc. Am. 80, 1346–1373.
Esposito, A. M., F. Giudicepietro, S. Scarpetta, L. D’Auria, M. Marinaro,
and M. Martini (2006). Automatic discrimination among landslide,
explosion-quake and microtremor seismic signals at Stromboli volcano
using neural networks, Bull. Seismol. Soc. Am. 96, no. 4A, 1230–1240,
doi 10.1785/0120050097.
Esposito, A. M., S. Scarpetta, F. Giudicepietro, S. Masiello, L. Pugliese, and
A. Esposito (2006). Nonlinear exploratory data analysis applied to
seismic signals, in Proceedings of the 16th Italian Workshop on
Neural Nets, WIRN 2005, and International Workshop on Natural
and Artificial Immune Systems, Vietri sul Mare, Italy, 8–11 June 2005,
B. Apolloni (Editor), Lecture Notes in Computer Science 3931,
Springer-Verlag, Berlin, 70–77.
Floreano, D., and C. Matiussi (1995). Manuale sulle Reti Neurali, Edizione
Mulino, Bologna.
Kohonen, T. (1989). Self-Organization and Associative Memory, Springer-
Verlag, Berlin.
Kohonen, T. (1995). Self-Organizing Maps, Springer-Verlag, Berlin.
Kohonen, T. (1997). Self-Organizing Maps, Second Ed., Series in Information
Sciences, Vol. 30, Springer, New York.
Kohonen, T., J. Hynninen, J. Kangas, and J. Laaksonen (1996). SOM_PAK:
the self-organizing map program package, Helsinki University of
Technology Report A31, Laboratory of Computer and Information
Science, Espoo, Finland (also available at http://www.cis.hut.fi/
research/som_lvq_pak.shtml, last accessed September 2008).
Kohonen, T., E. Oja, O. Simula, A. Visa, and J. Kangas (1996). Engineering
applications of self-organizing map, Proc. IEEE 84, no. 10,
1358–1384.
Martini, M. (2004). Very long period seismic activity at Stromboli volcano
(Italy) in 2003–2004, in IAVCEI General Assembly Abstracts, Pucon,
Chile, 14–19 November 2004.
Martini, M., B. Chouet, L. D’Auria, F. Giudicepietro, and P. Dawson (2004).
The seismic source stability of the very long period signals of the
Stromboli volcano, in EGU General Assembly Abstracts, Nice, France,
25–30 April 2004.
Masiello, S., A. M. Esposito, S. Scarpetta, F. Giudicepietro, A. Esposito, and
M. Marinaro (2005). Application of self organized maps and curvilinear
component analysis to the discrimination of the Vesuvius
seismic signals, Proceedings of the International Workshop on Self
Organizing Maps (WSOM2005), Paris, France, 5–8 September
2005, 387–396.
Maurer, W. J., F. U. Dowla, and S. P. Jarpe (1992). Seismic event interpretation
using self organizing neural networks, Proc. SPIE 1709, 950–958. McGreger, A. D., and J. M. Lees (2004). Vent discrimination at Stromboli
volcano, Italy, J. Volcanol. Geotherm. Res. 137, 169–185.
Neuberg, J., R. Luckett, M. Ripepe, and T. Braun (1994). Highlights from a
seismic broadband array on Stromboli volcano, Geophys. Res. Lett. 21,
no. 9, 749–752.
Rosi, M., A. Bertagnini, and P. Landi (2000). Onset of the persistent activity
at Stromboli volcano (Italy), Bull. Volcanol. 62, no. 4–5, 294–300.
Scarpetta, S., F. Giudicepietro, E. C. Ezin, S. Petrosino, E. Del Pezzo,
M. Martini, and M. Marinaro (2005). Automatic classification of
seismic signals at Mt. Vesuvius volcano, Italy using neural networks,
Bull. Seismol. Soc. Am. 95, 185–196.
Tiira, T. (1999). Detecting teleseismic events using artificial neural
networks, Comput. Geosci. 25, 929–939.
Wang, J., and T. Teng (1995). Artificial neural network based seismic
detector, Bull. Seismol. Soc. Am. 85, 308–319.
Wielandt, E., and T. Forbriger (1999). Near-field seismic displacement and
tilt associated with the explosive activity of Stromboli, Ann. Geofis. 42,
no. 3, 407–416.
monitoring and massive inversion of source parameters of very
long period seismic signals: an application to Stromboli volcano, Italy,
Geophys. Res. Lett. 33, L04301, doi 10.1029/2005GL024703.
Bertagnini, A., M. Coltelli, P. Landi, M. Pompilio, and M. Rosi (1999). Violent
explosions yield new insights into dynamics of Stromboli volcano,
Eos Trans. AGU 80 no. 52, 633–636, doi 10.1029/99EO00415.
Calvari, S., L. Spampinato, L. Lodato, A. J. L. Harris, M. R. Patrick, J. Dehn,
M. R. Burton, and D. Andronico (2005). Chronology and complex
volcanic processes during the 2002–2003 flank eruption at Stromboli
volcano (Italy) reconstructed from direct observations and surveys with a handheld thermal camera, J. Geophys. Res. 110, B02201,
doi 10.1029/2004JB003129.
Cercone, J. M., and J. R. Martin (1994). An application of neural networks to
seismic signal discrimination, Phillips Laboratory Report No. 3,
PL-TR-94-2178, Hanscon Air Force Base, Massachusetts.
Chouet, B., G. De Luca, G. Milana, P. Dawson, M. Martini, and R. Scarpa
(1998). Shallow velocity structure of Stromboli volcano, Italy, derived
from small-aperture array measurements of Strombolian tremor, Bull.
Seismol. Soc. Am. 88, no. 3, 653–666.
Chouet, B., G. Saccorotti, P. Dawson, M. Martini, R. Scarpa, G. De Luca, G.
Milana, and M. Cattaneo (1999). Broadband measurements of the
sources of explosions at Stromboli volcano, Italy, Geophys. Res. Lett.
26, no. 13, 1937.
Chouet, B., P. Dawson, T. Ohminato, M. Martini, G. Saccorotti, F. Giudicepietro,
G. De Luca, G. Milana, and R. Scarpa (2003). Source
mechanisms of explosions at Stromboli volcano, Italy, determined
from moment-tensor inversions of very-long-period data, J. Geophys.
Res. 108 no. B1, 2019, doi 10.1029/2002JB001919.
D’Auria, L., F. Giudicepietro, M. Martini, and R. Peluso (2006). Seismological
insight into the kinematics of the 5 April 2003 vulcanian explosion
at Stromboli volcano (southern Italy), Geophys. Res. Lett. 33,
L08308, doi 10.1029/2006GL026018.
Del Pezzo, E., A. Esposito, F. Giudicepietro, M. Marinaro, M. Martini, and
S. Scarpetta (2003). Discrimination of earthquakes and underwater
explosions using neural networks, Bull. Seismol. Soc. Amer. 93,
no. 1, 215–223.
Dowla, F. U. (1995). Neural networks in seismic discrimination, in Monitoring
a Comprehensive Test Ban Treaty, in NATO ASI, Series E E. S.Husebye and A. M. Dainty (Editors), Vol. 303, Kluwer, Dordrecht,
777–789.
Dowla, F. U., S. R. Taylor, and R. W. Anderson (1990). Seismic discrimination
with artificial neural networks: preliminary results with regional
spectral data, Bull. Seismol. Soc. Am. 80, 1346–1373.
Esposito, A. M., F. Giudicepietro, S. Scarpetta, L. D’Auria, M. Marinaro,
and M. Martini (2006). Automatic discrimination among landslide,
explosion-quake and microtremor seismic signals at Stromboli volcano
using neural networks, Bull. Seismol. Soc. Am. 96, no. 4A, 1230–1240,
doi 10.1785/0120050097.
Esposito, A. M., S. Scarpetta, F. Giudicepietro, S. Masiello, L. Pugliese, and
A. Esposito (2006). Nonlinear exploratory data analysis applied to
seismic signals, in Proceedings of the 16th Italian Workshop on
Neural Nets, WIRN 2005, and International Workshop on Natural
and Artificial Immune Systems, Vietri sul Mare, Italy, 8–11 June 2005,
B. Apolloni (Editor), Lecture Notes in Computer Science 3931,
Springer-Verlag, Berlin, 70–77.
Floreano, D., and C. Matiussi (1995). Manuale sulle Reti Neurali, Edizione
Mulino, Bologna.
Kohonen, T. (1989). Self-Organization and Associative Memory, Springer-
Verlag, Berlin.
Kohonen, T. (1995). Self-Organizing Maps, Springer-Verlag, Berlin.
Kohonen, T. (1997). Self-Organizing Maps, Second Ed., Series in Information
Sciences, Vol. 30, Springer, New York.
Kohonen, T., J. Hynninen, J. Kangas, and J. Laaksonen (1996). SOM_PAK:
the self-organizing map program package, Helsinki University of
Technology Report A31, Laboratory of Computer and Information
Science, Espoo, Finland (also available at http://www.cis.hut.fi/
research/som_lvq_pak.shtml, last accessed September 2008).
Kohonen, T., E. Oja, O. Simula, A. Visa, and J. Kangas (1996). Engineering
applications of self-organizing map, Proc. IEEE 84, no. 10,
1358–1384.
Martini, M. (2004). Very long period seismic activity at Stromboli volcano
(Italy) in 2003–2004, in IAVCEI General Assembly Abstracts, Pucon,
Chile, 14–19 November 2004.
Martini, M., B. Chouet, L. D’Auria, F. Giudicepietro, and P. Dawson (2004).
The seismic source stability of the very long period signals of the
Stromboli volcano, in EGU General Assembly Abstracts, Nice, France,
25–30 April 2004.
Masiello, S., A. M. Esposito, S. Scarpetta, F. Giudicepietro, A. Esposito, and
M. Marinaro (2005). Application of self organized maps and curvilinear
component analysis to the discrimination of the Vesuvius
seismic signals, Proceedings of the International Workshop on Self
Organizing Maps (WSOM2005), Paris, France, 5–8 September
2005, 387–396.
Maurer, W. J., F. U. Dowla, and S. P. Jarpe (1992). Seismic event interpretation
using self organizing neural networks, Proc. SPIE 1709, 950–958. McGreger, A. D., and J. M. Lees (2004). Vent discrimination at Stromboli
volcano, Italy, J. Volcanol. Geotherm. Res. 137, 169–185.
Neuberg, J., R. Luckett, M. Ripepe, and T. Braun (1994). Highlights from a
seismic broadband array on Stromboli volcano, Geophys. Res. Lett. 21,
no. 9, 749–752.
Rosi, M., A. Bertagnini, and P. Landi (2000). Onset of the persistent activity
at Stromboli volcano (Italy), Bull. Volcanol. 62, no. 4–5, 294–300.
Scarpetta, S., F. Giudicepietro, E. C. Ezin, S. Petrosino, E. Del Pezzo,
M. Martini, and M. Marinaro (2005). Automatic classification of
seismic signals at Mt. Vesuvius volcano, Italy using neural networks,
Bull. Seismol. Soc. Am. 95, 185–196.
Tiira, T. (1999). Detecting teleseismic events using artificial neural
networks, Comput. Geosci. 25, 929–939.
Wang, J., and T. Teng (1995). Artificial neural network based seismic
detector, Bull. Seismol. Soc. Am. 85, 308–319.
Wielandt, E., and T. Forbriger (1999). Near-field seismic displacement and
tilt associated with the explosive activity of Stromboli, Ann. Geofis. 42,
no. 3, 407–416.
Type
article