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Automatic methods for generating seismic intensity maps

Part of: Geophysics Inference from stochastic processes Geophysics (general)

Published online by Cambridge University Press:  14 July 2016

David R. Brillinger ,
Chang Chiann ,
Rafael A. Irizarry  and
Pedro A. Morettin
David R. Brillinger*
Affiliation:
University of California, Berkeley
Chang Chiann*
Affiliation:
University of Sao Paulo
Rafael A. Irizarry*
Affiliation:
Johns Hopkins University
Pedro A. Morettin*
Affiliation:
University of Sao Paulo
*
1Postal address: Department of Statistics, University of California, Berkeley, CA 94720, USA. Email: [email protected]
2Postal address: Department of Statistics, University of São Paulo, SP 05315–970, Brazil.
3Postal address: Department of Biostatistics, Johns Hopkins University, Baltimore, MD 21205, USA.
2Postal address: Department of Statistics, University of São Paulo, SP 05315–970, Brazil.
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Abstract

For many years the modified Mercalli (MM) scale has been used to describe earthquake damage and effects observed at scattered locations. In the next stage of an analysis involving MM data, isoseismal lines based on the observations have been added to maps by hand, i.e. subjectively. However a few objective methods have been proposed (by e.g. De Rubeis et al., Brillinger, Wald et al. and Pettenati et al.). The work presented here develops objective methods further. In particular the ordinal character of the MM scale is specifically taken into account. Numerical smoothing is basic to the approach and methods involving splines, local polynomial regression and wavelets are illustrated. The approach also allows the inclusion of explanatory variables, for example site effects. The procedure is implemented for data from the 17 October 1989 Loma Prieta earthquake.

Keywords

Isoseismalslocal polynomialsMercalli scaleordinal datasmoothingsplineswavelets

MSC classification

Primary: 62M30: Spatial processes
Secondary: 86A15: Seismology
Type
Models and statistics in seismology
Information
Journal of Applied Probability , Volume 38 , Issue A: Probability, Statistics and Seismology , 2001 , pp. 188 - 201
Copyright
Copyright © Applied Probability Trust 2001 

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