Earthquake

Synthetic aperture radar (SAR) is remarkable for its capability to record the backscattering coefficient, the physical value of the earth’s surface, regardless of weather condition or sun illumination. Therefore, SAR is a powerfultool that can be utilized to develop a universal method to comprehend damaged areas in disasters such as earthquakes, forest fires, and floods. We performed a feasibility study on backscattering characteristics of damaged areas in the 1995 Hyogoken-Nanbu (Kobe), Japan, earthquake using the preandpost-event ERS images, revealing that the backscattering coefficient and intensity correlation between the two attained values were significantly lowered in hard-hit areas. The evaluation, however, was performed without speckle noise reduction. We also investigated the effects of speckle noise reduction and pixel-window size in evaluating building damage using the difference in the backscattering coefficient and correlation coefficient of the pre…

A strong earthquake occurred beneath the city of Bam, Iran, on 26 December 2003. High-resolution optical satellite images, such as Ikonos and QuickBird, obtained after the earthquake indicate that severely damaged areas were widely distributed in the city. A European radar satellite, Envisat, also captured the hard-hit areas on 07 January 2004. This paper introduces an automated damage detection technique that was developed based on the dataset of the 1995 Kobe, Japan, earthquake and applied to Envisat/ASAR imagesof Bam. A detailed investigation of the characteristics of the areas damaged due to the Bam earthquake in terms of the differences in the backscattering coefficient and the correlation coefficient of the pre- and post-event Envisat/ASAR images was conducted in order to raise the precision of damage detection. Finally, the damage-mapping scheme was revised to present the distribution of damaged areas in Bam.

Remote sensing technology is playing an increasingly important role in post-disaster decision support. Organizations including the Earthquake Engineering Research Institute (EERI) and Multidisciplinary Center for Earthquake Engineering Research (MCEER) recognize that following major earthquakes, satellite imagery can bring significant benefits to response and recovery efforts, through urban damage assessment. Following an introductory review of prior research undertaken in the field, this paper presents methodological techniques for determining the location and severity of post-earthquake building damage. The damage detection algorithms are based on the comparative analysis of a multitemporal sequence of optical or SAR images, acquired before and after the event. Following initial pre-processing to geo-reference and co-register the imagery, damage is detected in terms of spectral changes between the scenes. Depending on its spatial resolution, image processing…

Remote sensing technology is increasingly recognized as a valuablepost-earthquake damage assessment tool. Recent studies performed by research teams in the U.S., Japan and Europe have demonstrated that building damage sustained in urban environments can be readily identified through the analysis of optical (Matsuoka and Yamazaki, 1998; Chiroiu et al., 2002; Huyck et al., 2002; Mitomi et al., 2002; Yusuf et al., 2002; Shinozukaet al., 2000; Saito and Spence, 2004) and synthetic aperature radar (SAR) (Aoki et al., 1998, Huyck et al., 2002; Yusuf et al., 2002) imagery. Under the broad aim of identifying ways in which post-earthquake response and recovery activities can be improved through the integration of remote sensing technologies, a Multidisciplinary Center for Earthquake Engineering Research (MCEER) team has been investigating their use for urban damage detection and emergency response (Eguchi et al., 1999; Eguchi et al., 2000a, 2000b; Eguchi et al., 2003; Huyck and…

Lack of reliable, up to date, available and qualified geospatial data is one of the problems we are faced to have a proper response to natural disasters. On the other hand, complexity of earthquake phenomena from time, position and intensity, makes it a very uncertain phenomenon to assess. Furthermore, there is no comprehensive spatial analysis tool to support decision making under such disasters. Therefore, development of spatial decision support system (SDSS) to support processing and analyzing geo-spatial data for disaster management and damage estimation is of extreme importance. Previous research shows that about 70 % of Iranian urban areas are suspect to earthquake, therefore, Iran is located in an extremely earthquake risk prone areas in the world.This paper outlines a methodology to assess damage estimation due to an earthquake using SDSS. The methodology is based on quantifying number of buildings destroyed due to an earthquake using high resolution remotely…

A strong earthquake struck the city of Bam in southeast Iran on 26 December 2003. The earthquake brought massive destruction to the city and its surrounding rural areas. QuickBird, a high-resolution satellite, captured a clear image of Bam on 03 January 2004, eight days after the event. The city was also observed by QuickBird on 30 September 2003, about three months before theevent. In this paper, using the pre-event image, the location of individual buildings was registered on GIS and the city blocks surrounded by major roadswere assigned. Then, the visual damage interpretation based on the European Macroseismic Scale (EMS-98) was carried out building by building, comparing the pre-event and post-event images. The result of the damage inspection was compared with field survey data, and the accuracy and usefulness of the high-resolution satellite images in damage detection was demonstrated.

Various studies were carried out in the last years with the purpose of assessingnatural hazard damages using remote sensing and photo interpretation techniques. Most of them analyze the case of floods or landslides, where damages could be estimated. For the seismic events, the first studies were carried out basically after the Kocaeli Earthquake of 1999, were spatial images from various satellites could be exploited. The recent progresses of remote sensing in terms of spatial resolution and data processing open new possibilities concerning the natural hazard assessment. Using a high resolution optical imagery available today, a damage detection could be performed inclusively in urban areas.

A multidisciplinary approach based on high resolution satellite data and earthquake engineering was applied in order to estimate the damage after the Bhuj, (India), Earthquake of January 26th, 2001. The study provide a fast loss estimation, in terms of physical damage and…

A large-scale earthquake with a magnitude of 7.6 occurred on October 8, 2005 in the northern part of Pakistan. The Geographical Survey Institute (GSI) carried out various analyses to clarify in detail with the data from satellites the crustal deformation accompanying the earthquake.

GSI mapped the crustal deformation spatially with Synthetic Aperture Radar data from the European Space Agency’s ENVISAT, and found that the newly deformed area occupies a 90-kilometer-long northwest-southeast trending strip. The heavily damaged area north of Muzaffarabad has the maximum deformation up to 6-meter uplift as observed by the satellite.

There are known active faults stretching to the northwest and southeast near the epicenter, which reveal some uplift (on the northeastern side) and dextral (right-lateral) strike-slip activity. The detected crustal deformation was along these active faults and all observations were consistent with previously known directions of…

The focus of this study was to thoroughly exploit the capability of very high-resolution (VHR) satellite imagery such as Ikonos and QuickBird for disaster mitigation. An efficient automated methodology that detects damage was implemented to derive the rich information available from VHR satellite imagery. Consequently, the detected results and the VHR satellite imagery are attractively presented through a fly-over animation and visualization. The aim is to assist the field-based damage estimation and to strengthen public awareness. The available Ikonos and QuickBird data captured after the Bam, Iran, earthquake in December 2003 was employed to demonstrate the competence of the automated detection algorithm and fly-over animation/visualization. These results are consistent with the field-based damage results.

This paper introduces the Recovery Project,which aims to identify indicators of post-disaster recoveryusing satellite imagery, internet-based statistics andadvanced field survey techniques. This paper reviews therecovery literature as a means of introducing the recoveryprocess and the considerations that must be made whenevaluating recovery. This is followed by an introduction tothe Recovery project and its two case study sites: 1. BanNam Khem, Thailand and 2. Muzaffarabad, Pakistan. Areview of the recovery process at Ban Nam Khem ispresented along with a diagram of potential indicatorsobtained from the literature research. The paperconcludes with a short discussion on how remote sensingmay be used to monitor some of these indicators.