Please use this identifier to cite or link to this item:
http://hdl.handle.net/2122/7645
DC Field | Value | Language |
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dc.contributor.authorall | Messina, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma2, Roma, Italia | en |
dc.contributor.authorall | Langer, H.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia | en |
dc.date.accessioned | 2012-01-27T14:16:51Z | en |
dc.date.available | 2012-01-27T14:16:51Z | en |
dc.date.issued | 2011-03-27 | en |
dc.identifier.uri | http://hdl.handle.net/2122/7645 | en |
dc.description.abstract | Continuous seismic monitoring plays a key role in the surveillance of the Mt. Etna volcano. Besides earthquakes, which often herald eruptive episodes, the persistent background signal, known as volcanic tremor, provides important information on the volcano status. Changes in the regimes of activity are usually concurrent with variations in tremor characteristics. As continuous recording leads rapidly to the accumulation of large amounts of data, parameter extraction and automated processing become crucial. We propose techniques of unsupervised classification and present a software, named KKAnalysis, developed for this purpose. Essentials of KKAnalysis are demonstrated on tremor data recorded on Mt. Etna during various states of volcanic activity encountered in 2007 and 2008. KKAnalysis is based on MATLAB and combines various unsupervised pattern recognition techniques, in particular self-organizing maps (SOM) and cluster analysis. An early software version was successfully applied to seismic signals recorded on Mt. Etna during the eruption in 2001. Since each situation may require different configurations, we designed KKAnalysis with a specific GUI allowing users to easily modify parameters. All results are given graphically, in screen plots and metafiles (MATLAB and TIF format), as well as in alphanumeric form. The synoptic visualization of results from SOM and cluster analysis facilitates an immediate inspection. The potential of this representation is demonstrated by focusing on data recorded during a flank eruption on May 13, 2008. Changes of tremor characteristics can be clearly identified at a very early stage, well before enhanced volcanic activity becomes visible in the time series. At the same time, data reduction to less than 1% of the original amount is achieved, which facilitates interpretation and storage of the essential information. Running the program in a typical configuration requires computing time less than 1 min, allowing an on-line application for early warning purposes at INGV–Sezione di Catania | en |
dc.language.iso | English | en |
dc.publisher.name | Elsevier | en |
dc.relation.ispartof | Computers & Geosciences | en |
dc.relation.ispartofseries | 7/37(2011) | en |
dc.subject | Self-Organizing Map | en |
dc.subject | Cluster Analysis | en |
dc.subject | K-means | en |
dc.subject | Fuzzy C-means | en |
dc.subject | Volcano Seismology | en |
dc.subject | Volcano Monitoring | en |
dc.title | Pattern recognition of volcanic tremor data on Mt. Etna (Italy) with KKAnalysis — A software program for unsupervised classification | en |
dc.type | article | en |
dc.description.status | Published | en |
dc.type.QualityControl | Peer-reviewed | en |
dc.description.pagenumber | 953-961 | en |
dc.subject.INGV | 04. Solid Earth::04.06. Seismology::04.06.08. Volcano seismology | en |
dc.subject.INGV | 04. Solid Earth::04.08. Volcanology::04.08.06. Volcano monitoring | en |
dc.subject.INGV | 05. General::05.01. Computational geophysics::05.01.01. Data processing | en |
dc.subject.INGV | 05. General::05.01. Computational geophysics::05.01.02. Cellular automata, fuzzy logic, genetic alghoritms, neural networks | en |
dc.subject.INGV | 05. General::05.02. Data dissemination::05.02.03. Volcanic eruptions | en |
dc.identifier.doi | 10.1016/j.cageo.2011.03.015 | en |
dc.relation.references | Behncke, B., 2009. Personal communication. Brouwer, R.K., 2009. A method of relational fuzzy clustering based on producing feature vectors using FastMap. Information Sciences 179 (20), 3561–3582. Cannata, A., Catania, A., Alparone, S., 2008. Volcanic tremor at Mt. Etna: inferences on magma dynamics during effusive and explosive activity. Journal of Volcanology and Geothermal Research 178, 19–31. doi:10.1016/j.jvolgeores. 2007.11.027. Corsaro, R.A., Falsaperla, S., Langer, H., 2010. Geochemical patterns classification of recent Mt. Etna volcanic products based on a synopsis of Kohonen maps and fuzzy clustering. Geophysical Research Abstracts 12 EGU2010-10416-1. Davies, D.L., Bouldin, D.W., 1979. A cluster separation measure. IEEE Transactions on Pattern Analysis and Machine Learning 1 (2), 224–227. Di Grazia, G., Falsaperla, S., Langer, H., 2006. Volcanic tremor location during the 2004 Mt. Etna lava effusion. Geophysical Research Letters 33, L04304. doi:10.1029/2005GL025177. D’Urso, P., Maharaj, E.A., 2009. Autocorrelation-based fuzzy clustering of time series. Fuzzy Sets and Systems 160 (24), 3565–3589. Er, M.J., Parthasarathi, R., 2005. A novel self-organizing neural fuzzy network for automatic generation of fuzzy inference systems, Advances in Neural Net- works. Springer, Berlin 434–439. Esposito, A.M., Giudicepietro, F., D’Auria, L., Scarpetta, S., Martini, M., Coltelli, M., Marinaro, M., 2008. Unsupervised neural analysis of very long period events at Stromboli volcano using the self-organizing maps. Bulletin of the Seismologi- cal Society of America 98, 2449–2459. doi:10.1785/0120070110. Falsaperla, S., Alparone, S., D’Amico, S., Di Grazia, G., Ferrari, F., Langer, H., Sgroi, T., Spampinato, S., 2005. Volcanic tremor at Mt. Etna, Italy, preceding and accompanying the eruption of July–August, 2001. Pure and Applied Geophy- sics 162, 2111–2132. doi:10.1007/s00024-005-2710-y. Falsaperla, S., Graziani, S., Nunnari, G., Spampinato, S., 1996. Automatic classifica- tion of volcanic earthquakes by using multi-layered neural networks. Natural Hazards 13, 205–228. Kohonen, T., 2001. Self Organizing Maps, 3rd ed. Springer, Berlin, Germany, 501 pp. Langer, H., Falsaperla, S., 1996. Long-term observation of volcanic tremor on Stromboli volcano (Italy): a synopsis. Pure and Applied Geophysics 147, 57–82. Langer, H., Falsaperla, S., 2003. Seismic monitoring at Stromboli volcano (Italy): a case study for data reduction and parameter extraction. Journal of Volcanology and Geothermal Research 128, 233–245. Langer, H., Falsaperla, S., Masotti, M., Campanini, R., Spampinato, S., Messina, A., 2009. Synopsis of supervised and unsupervised pattern classification techni- ques applied to volcanic tremor data at Mt. Etna, Italy. Geophysical Journal International 178, 1132–1144. doi:10.1111/j.1365-246X.2009.04179.x. Langer, H., Falsaperla, S., Powell, T., Thompson, G., 2006. Automatic classification and a-posteriori analysis of seismic event identification at Soufriere Hills volcano, Montserrat. Journal of Volcanology and Geothermal Research 153 (1–2), 357–369. Scarpetta, S., Giudicepietro, F., Ezin, E.C., Petrosino, S., Del Pezzo, E., Martini, M., Marinaro, M., 2005. Automatic classification of seismic signals at Mt. Vesuvius volcano, Italy, using neural networks. Bulletin of the Seismological Society of America 95, 185–196. doi:10.1785/0120030075. Spath, H., 1985. Cluster Dissection and Analysis. Horwood, Chichester, 226 pp. Tokushige, S., Yadohisa, H., Inada, K., 2007. Crisp and fuzzy k-means clustering algorithms for multivariate functional data. Computational Statistics 22 (1), 1–16. Vesanto, J., Himberg, J., Alhoniemi, E., Parhankangas, J., 2000. SOM Toolbox for Matlab 5. Report A57, Helsinki University of Technology, Helsinki, Finland. | en |
dc.description.obiettivoSpecifico | 1.5. TTC - Sorveglianza dell'attività eruttiva dei vulcani | en |
dc.description.obiettivoSpecifico | 5.6. TTC - Attività di Sala Operativa | en |
dc.description.journalType | JCR Journal | en |
dc.description.fulltext | reserved | en |
dc.contributor.author | Messina, A. | en |
dc.contributor.author | Langer, H. | en |
dc.contributor.department | Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma2, Roma, Italia | en |
dc.contributor.department | Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione OE, Catania, Italia | en |
item.openairetype | article | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en | - |
item.grantfulltext | restricted | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.fulltext | With Fulltext | - |
crisitem.author.dept | Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione OE, Catania, Italia | - |
crisitem.author.dept | Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione OE, Catania, Italia | - |
crisitem.author.orcid | 0000-0002-3358-7210 | - |
crisitem.author.orcid | 0000-0002-2508-8067 | - |
crisitem.author.parentorg | Istituto Nazionale di Geofisica e Vulcanologia | - |
crisitem.author.parentorg | Istituto Nazionale di Geofisica e Vulcanologia | - |
crisitem.classification.parent | 04. Solid Earth | - |
crisitem.classification.parent | 04. Solid Earth | - |
crisitem.classification.parent | 05. General | - |
crisitem.classification.parent | 05. General | - |
crisitem.classification.parent | 05. General | - |
crisitem.department.parentorg | Istituto Nazionale di Geofisica e Vulcanologia | - |
crisitem.department.parentorg | Istituto Nazionale di Geofisica e Vulcanologia | - |
Appears in Collections: | Article published / in press |
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2011 - CAGEO - Messina and Langer_earthpr.pdf | Main article | 1.76 MB | Adobe PDF |
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