Abstract
For a quick and stable estimation of earthquake damaged buildings worldwide, using Phased Array type L-band Synthetic Aperture Radar (PALSAR) loaded on the Advanced Land Observing Satellite (ALOS) satellite, a model combining the usage of satellite synthetic aperture radar (SAR) imagery and Japan Meteorological Agency (JMA)-scale seismic intensity is proposed. In order to expand the existing C-band SAR based damage estimation model into L-band SAR, this paper rebuilds a likelihood function for severe damage ratio, on the basis of dataset from Japanese Earth Resource Satellite-1 (JERS-1)/SAR (L-band SAR) images observed during the 1995 Kobe earthquake and its detailed ground truth data. The model which integrates the fragility functions of building damage in terms of seismic intensity and the proposed likelihood function is then applied to PALSAR images taken over the areas affected by the 2007 earthquake in Pisco, Peru. The accuracy of the proposed damage estimation model is examined by comparing the results of the analyses with field investigations and/or interpretation of high-resolution satellite images.
Highlights
Worldwide remote monitoring from space of natural disasters, such as earthquakes, tsunamis, and floods, is becoming more common in recent years with the launch of the “International Charter Space and Major Disaster” system
In order to evaluate the building damage ratio from synthetic aperture radar (SAR) images, and to allow an integrated analysis with other types of information such as seismic intensity information, Nojima et al derived a regression discriminant function that relates to the building damage ratio from the correlation and difference in backscattering coefficient, and created a model for quantitatively estimating the severe building damage ratio from a modeled likelihood function based on the regression discriminant function [12]
The severe building damage ratio estimation model for L-band SAR image proposed above is applied to Advanced Land Observing Satellite (ALOS)/Phased Array type L-band Synthetic Aperture Radar (PALSAR) images for the 2007 Peru earthquake, and the accuracy of the model is examined through comparisons between the results of integration with seismic intensity information and the actual damage situation
Summary
Worldwide remote monitoring from space of natural disasters, such as earthquakes, tsunamis, and floods, is becoming more common in recent years with the launch of the “International Charter Space and Major Disaster” system. In order to evaluate the building damage ratio from SAR images, and to allow an integrated analysis with other types of information such as seismic intensity information, Nojima et al derived a regression discriminant function that relates to the building damage ratio from the correlation and difference in backscattering coefficient, and created a model for quantitatively estimating the severe building damage ratio from a modeled likelihood function based on the regression discriminant function [12] The versatility of this model has been qualitatively demonstrated, as it is not very susceptible to the effects of satellite observation conditions and regional characteristics, because it uses intensity information in the form of backscattering coefficient in order to extract areas of damage [13]. Assess our model performance by comparisons with field investigations
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