"Seismic-mass" density-based algorithm for spatio-temporal clustering

In this research work a new hybrid approach to spatio-temporal seismic clustering is proposed. The method builds upon a novel density based clustering scheme that explicitly takes into account earthquake's magnitude during the density estimation. The new density based clustering algorithm considers both time and spatial information during cluster formation. Therefore clusters lie in a spatio-temporal space. A hierarchical agglomerative clustering algorithm acts upon the identified clusters after dropping the time information in order to come up only with the spatial description of seismic events. The approach is demonstrated using data from the vicinity of the Hellenic seismic arc in order to enable its comparison with some of the state-of-the-art distinct seismic region identification methodologies. The presented results indicate that the combination of the two clustering stages could be potentially used for an automatic definition of major seismic sources.

[1]  V. Zobin Earthquake clustering in shallow subduction zones: Kamchatka and Mexico , 1996 .

[2]  B. Ripley,et al.  Pattern Recognition , 1968, Nature.

[3]  Hans-Peter Kriegel,et al.  A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.

[4]  S. Hernández,et al.  Modelling seismic activity using a Bayesian non-parametric method , 2011 .

[5]  Anil K. Jain Data clustering: 50 years beyond K-means , 2008, Pattern Recognit. Lett..

[6]  Richard M. Allen,et al.  The deterministic nature of earthquake rupture , 2005, Nature.

[7]  Ahmad Zamani,et al.  Computer-based self-organized tectonic zoning: a tentative pattern recognition for Iran , 2004, Comput. Geosci..

[8]  B. Papazachos,et al.  Time-Independent and Time-Dependent Seismic Hazard in Greece Based on Seismogenic Sources , 2000 .

[9]  G. Drakatos,et al.  A catalog of aftershock sequences in Greece (1971–1997): Their spatial and temporal characteristics , 2001 .

[10]  K. Kayabol A Latent Variable Bayesian Approach to Spatial Clustering with Background Noise , 2011 .

[11]  Rodolfo Console,et al.  Physical and stochastic models of earthquake clustering , 2006 .

[12]  B. Mukhopadhyay,et al.  Seismic cluster analysis for the Burmese–Andaman and West Sunda Arc: insight into subduction kinematics and seismic potentiality , 2010 .

[13]  D. Sornette,et al.  Renormalization group theory of earthquakes , 1996 .

[14]  Reza Boostani,et al.  Tectonic Zoning of Iran Based on Self-Organizing Map , 2009 .

[15]  G. Weatherill,et al.  Delineation of shallow seismic source zones using K-means cluster analysis, with application to the Aegean region , 2009 .

[16]  Assadollah Noorzad,et al.  Clustering analysis of the seismic catalog of Iran , 2009, Comput. Geosci..

[17]  G. Weatherill,et al.  An alternative approach to probabilistic seismic hazard analysis in the Aegean region using Monte Carlo simulation , 2010 .

[18]  Martin R. Varley,et al.  Detection of Weak Seismo-Electric Signals Upon the Recordings of the Electrotelluric Field by Means of Neuro-Fuzzy Technology , 2007, IEEE Geoscience and Remote Sensing Letters.

[19]  P. Reasenberg Second‐order moment of central California seismicity, 1969–1982 , 1985 .

[20]  Bertrand Meyer,et al.  Fault interactions in the Sea of Marmara pull-apart (North Anatolian Fault): earthquake clustering and propagating earthquake sequences , 2007 .

[22]  Martin R. Varley,et al.  Soft-Computing Modelling of Seismicity in the Southern Hellenic Arc , 2008, IEEE Geoscience and Remote Sensing Letters.

[23]  Anthony J. Konstantaras,et al.  Classification of Distinct Seismic Regions and Regional Temporal Modelling of Seismicity in the Vicinity of the Hellenic Seismic Arc , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[24]  R. Bürgmann Earthquakes: Imperfect dominoes , 2009 .

[25]  Isabelle Guyon,et al.  Clustering: Science or Art? , 2009, ICML Unsupervised and Transfer Learning.

[26]  B. Mukhopadhyay,et al.  Seismic clusters and their characteristics at the Arabian Sea Triple Junction: Supportive evidences for plate margin deformations , 2011 .

[27]  A. Zamani,et al.  Computer-based self-organized tectonic zoning revisited: Scientific criterion for determining the optimum number of zones , 2011 .

[28]  F. Vallianatos,et al.  Electric current generation associated with the deformation rate of a solid: Preseismic and coseismic signals , 1998 .

[29]  Ch. Papaioannou,et al.  A deterministic seismic hazard analysis for shallow earthquakes in Greece , 2007 .

[30]  G. Weatherill,et al.  SEISMIC HAZARD ASSESSMENT AND ZONING IN JAVA: NEW AND ALTERNATIVE PROBABILISTIC ASSESSMENT MODELS , 2008 .