A Novel Method for Seismogenic Zoning Based on Triclustering: Application to the Iberian Peninsula

Entropy

Francisco Martínez-Álvarez¹  David Gutiérrez-Avilés³  Antonio Morales-Esteban⁵  Jorge Reyes²  José L. Amaro-Mellado⁴  Cristina Rubio-Escudero³ 

[1]TGT-NT2 Labs, Santiago de Chile, 7820090, Chile

[2] E-Mail:

[3]Department of Computer Science, University of Seville, Seville, 41012, Spain

[4] E-Mails:

[5]Department of Graphics Engineering, University of Seville, Seville, 41012, Spain

[6] E-Mail:

[7]Department of Building Structures and Geotechnical Engineering, University of Seville, Seville 41012, Spain

[8] E-Mail:

关键词: triclustering;    seismic zoning;    self-organizing maps;    Iberian Peninsula;   

DOI  :  10.3390/e17075000

来源: mdpi

【 摘 要 】

A previous definition of seismogenic zones is required to do a probabilistic seismic hazard analysis for areas of spread and low seismic activity. Traditional zoning methods are based on the available seismic catalog and the geological structures. It is admitted that thermal and resistant parameters of the crust provide better criteria for zoning. Nonetheless, the working out of the rheological profiles causes a great uncertainty. This has generated inconsistencies, as different zones have been proposed for the same area. A new method for seismogenic zoning by means of triclustering is proposed in this research. The main advantage is that it is solely based on seismic data. Almost no human decision is made, and therefore, the method is nearly non-biased. To assess its performance, the method has been applied to the Iberian Peninsula, which is characterized by the occurrence of small to moderate magnitude earthquakes. The catalog of the National Geographic Institute of Spain has been used. The output map is checked for validity with the geology. Moreover, a geographic information system has been used for two purposes. First, the obtained zones have been depicted within it. Second, the data have been used to calculate the seismic parameters (b-value, annual rate). Finally, the results have been compared to Kohonen’s self-organizing maps.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland