Detection of Earthquake-Induced Building Damages Using Polarimetric SAR Data

Sang-Eun Park,Yoon Taek Jung

doi:10.3390/rs12010137

Abstract

Remote sensing, particularly using synthetic aperture radar (SAR) systems, can be an effective tool in detecting and assessing the area and amount of building damages caused by earthquake or tsunami. Several studies have provided experimental evidence for the importance of polarimetric SAR observations in building damage detection and assessment, particularly caused by a tsunami. This study aims to evaluate the practical applicability of the polarimetric SAR observations to building damage caused by the direct ground-shaking of an earthquake. The urban areas heavily damaged by the 2016 Kumamoto earthquake in Japan have been investigated by using the polarimetric PALSAR-2 data acquired in pre- and post-earthquake conditions. Several polarimetric change detection approaches, such as the changes of polarimetric scattering powers, the matrix dissimilarity measures, and changes of the radar scattering mechanisms, were examined. Optimal damage indicators in the presence of significant natural changes, and a novel change detection method by the fuzzy-based fusion of polarimetric damage indicators are proposed. The accuracy analysis results show that the proposed automatic classification method can successfully detect the selected damaged areas with a detection rate of 90.9% and false-alarm rate of 1.3%.

Highlights

Earthquakes are one of the major natural disasters
The synthetic aperture radar (SAR)-based detection of building damages caused by earthquake and tsunami has been studied mainly by the change detection method using single-polarization multitemporal SAR images acquired at pre- and post-disaster conditions
The repetitive observation of the earth’s surface with space-borne SAR remote sensing has shown great potential to detect a large damaged area caused by various natural disasters

Summary

Introduction

Earthquakes are one of the major natural disasters. The direct ground-shaking and secondary effects, e.g., tsunami, can cause numerous structural failures in urban areas, resulting in human fatalities. After earthquake or tsunami disasters, it is important to quickly ascertain the area and amount of building damage. The SAR-based detection of building damages caused by earthquake and tsunami has been studied mainly by the change detection method using single-polarization multitemporal SAR images acquired at pre- and post-disaster conditions. Matsuoka and Yamazaki [1] analyzed changes in the backscattering coefficients and intensity correlation using ERS SAR data for detecting building damages caused by the 1995 Kobe earthquake. In [6], the sensitivities of the normalized intensity difference and the intensity correlation to damage grades were evaluated using the high-resolution TerraSAR-X and Cosmo-SkyMed data. The experiments for the 2010 Haiti earthquake showed that the normalized intensity difference provided better correlation with damage grades. It was pointed out that the sensitivity of SAR parameters to damage grades can be significantly affected by the temporal baseline between the pre-and post-earthquake acquisitions

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