Improving the Classification of Volcanic Seismic Events Extracting New Seismic and Speech Features

  • Millaray Curilem
  • Camilo Soto
  • Fernando Huenupan
  • Cesar San Martin
  • Gustavo Fuentealba
  • Carlos Cardona
  • Luis Franco
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10657)


This paper presents a study on features extracted from the seismic and speech domains that were used to classify four groups of seismic events of the Llaima volcano, located in the Araucanía Region of Chile. 63 features were extracted from 769 events that were labeled and segmented by experts. A feature selection process based on a genetic algorithm was implemented to select the best descriptors for the classifying structure formed by one SVM for each class. The process identified a few features for each class, and a performance that overcame the results of previous similar works, reaching over that 95% of exactitude and showing the importance of the feature selection process to improve classification. These are the newest results obtained from a technology transfer project in which advanced signal processing tools are being applied, in collaboration with the Southern Andes Volcano Observatory (OVDAS), to develop a support system for the monitoring of the Llaima volcano.


Volcanic seismicity Pattern recognition SVM Feature selection 



We would like to thank FONDEF as this study is being supported by the project FONDEF IDeA IT15I10027.


  1. 1.
    Chouet, B.: A seismic model for the source of long-period events and harmonic tremor. In: Gasparini, P., Scarpa, R., Aki, K. (eds.) Volcanic Seismology, pp. 133–156. Springer, Heidelberg/New York (1992). CrossRefGoogle Scholar
  2. 2.
    Lahr, J.C., Chouet, B.A., Stephens, C.D., Power, J.A., Page, R.A.: Earthquake classification, location and error analysis in a volcanic environment: implications for the magmatic system of the 1989–1990 eruptions at Redoubt Volcano, Alaska. J. Volcanol. Geoth. Res. 62(1–4), 137–151 (1994)CrossRefGoogle Scholar
  3. 3.
    Curilem, M., Vergara, J., San Martin, C., Fuentealba, G., Cardona, C., Huenupan, F., Chacón, M., Khan, S., Hussein, W., Becerra, N.: Pattern recognition applied to seismic signals of the Llaima volcano (Chile): an analysis of the events’ features. J. Volcanol. Geoth. Res. 282, 134–177 (2014)CrossRefGoogle Scholar
  4. 4.
    Langer, H., Falsaperla, S., Messina, A., Spampinato, S., Behncke, B.: Detecting imminent eruptive activity at Mt Etna, Italy, in 2007–2008 through pattern classification of volcanic tremor data. J. Volcanol. Geoth. Res. 200(1–2), 1–17 (2011)CrossRefGoogle Scholar
  5. 5.
    Bhatti, S.M., Khan, M.S., Wuth, J., Huenupan, F., Curilem, M., Franco, L., Becerra-Yoma, N.: Automatic detection of volcano-seismic events by modeling state and event duration in hidden Markov models. J. Volcanol. Geoth. Res. 324, 134–143 (2016)CrossRefGoogle Scholar
  6. 6.
    Curilem, G., Vergara, J., Fuentealba, G., Acuña, G., Chacón, M.: Classification of seismic signals at Villarrica volcano (Chile) using neural networks and genetic algorithms. J. Volcanol. Geoth. Res. 180, 1–8 (2009)CrossRefGoogle Scholar
  7. 7.
    Cortés, G., García, L., Álvarez, I., Benítez, C., de la Torre, T., Ibáñez, J.: Parallel System Architecture (PSA): an efficient approach for automatic recognition of volcano-seismic events. J. Volcanol. Geoth. Res. 271, 1–10 (2014)CrossRefGoogle Scholar
  8. 8.
    Scarpetta, S., Giudicepietro, F., Ezin, E.C., Petrosino, S., Del Pezzo, E., Martíni, M., Marinaro, M.: Automatic classification of seismic signals at Mt Vesuvius Volcano, Italy, using neural networks. Bull. Seismol. Soc. Am. 95(1), 185–196 (2005)CrossRefGoogle Scholar
  9. 9.
    Langer, H., Falsaperla, S., Powell, T., Thompson, G.: Automatic classification and a-posteriori analysis of seismic event identification at Soufriere Hills volcano, Montserrat. J. Volcanol. Geoth. Res. 153, 1–10 (2006)CrossRefGoogle Scholar
  10. 10.
    Erlebacher, G., Yuen, D.A.: A wavelet toolkit for visualization and analysis of large data sets in earthquake research. Pure. Appl. Geophys. 161, 2215–2229 (2004)CrossRefGoogle Scholar
  11. 11.
    Ibáñez, J., Benítez, C., Gutiérrez, L., Cortés, G., García-Yeguas, A., Alguacil, G.: The classification of seismo-volcanic signals using Hidden Markov Models as applied to the Stromboli and Etna volcanoes. J. Volcanol. Geoth. Res. 187, 218–226 (2009)CrossRefGoogle Scholar
  12. 12.
    San-Martin, C., Melgarejo, C., Gallegos, C., Soto, G., Curilem, M., Fuentealba, G.: Feature extraction using circular statistics applied to volcano monitoring. In: Bloch, I., Cesar, Roberto M. (eds.) CIARP 2010. LNCS, vol. 6419, pp. 458–466. Springer, Heidelberg (2010). CrossRefGoogle Scholar
  13. 13.
    Joevivek, V., Chandrasekar, N., Srinivas, Y.: Improving seismic monitoring system for small to intermediate earthquake detection. Int. J. Comput. Sci. Secur. 4(3), 308–315 (2010)Google Scholar
  14. 14.
    Álvarez, I., García, L., Cortés, G., Benítez, C., de La Torre, A.: Discriminative feature selection for automatic classification of volcano-seismic signals. IEEE Geosci. Remote Sens. Lett. 9(2), 151–155 (2012)CrossRefGoogle Scholar
  15. 15.
    Unglert, K., Radić, V., Jellinek, A.M.: Principal component analysis vs. self-organizing maps combined with hierarchical clustering for pattern recognition in volcano seismic spectra. J. Volcanol. Geoth. Res. 320, 58–74 (2016)CrossRefGoogle Scholar
  16. 16.
    Vapnik, V.: The Nature of Statistical Learning Theory. Springer, New York (1995). CrossRefMATHGoogle Scholar
  17. 17.
    Holland, J.H.: Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. The MIT Press, Cambridge (1992). 228 p.Google Scholar
  18. 18.
    Kuri-Morales, A.: Pattern recognition via Vasconcelos’ Genetic Algorithm. In: Sanfeliu, A., Martínez Trinidad, J.F., Carrasco Ochoa, J.A. (eds.) CIARP 2004. LNCS, vol. 3287, pp. 328–335. Springer, Heidelberg (2004). CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Millaray Curilem
    • 1
  • Camilo Soto
    • 1
  • Fernando Huenupan
    • 1
  • Cesar San Martin
    • 1
  • Gustavo Fuentealba
    • 1
  • Carlos Cardona
    • 2
  • Luis Franco
    • 2
  1. 1.Facultad de Ingeniería y CienciasUniversidad de La FronteraTemucoChile
  2. 2.Observatorio Vulcanológico de los Andes SurTemucoChile

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