In order to develop an automatic damage detection technique, the characteristics of texture in high-resolution satellite images observed before and after the 2010 Haiti earthquake are examined. From the texture analysis based on gray-level co-occurrence matrix, the dissimilarity of the images is identified as better classifier than other texture indices in detecting collapsed buildings. By using the dissimilarity calculated from the pre- and post-event images, damage detection is performed to identify the distribution of the collapsed buildings and the accuracy of the detection is assessed by the ROC analysis. The result shows that about 70% of the collapsed buildings are correctly detected by the proposed method.

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Two sets of high-resolution SAR imageries from TerraSAR-X were used to calculate radar characteristics like correlation coefficient and backscatter difference for building damage detection after the 2010 Haiti earthquake in the city center of Port-au-Prince. The Normalized Difference Vegetation Index from a Quickbird image was used to delineate non-vegetated areas. The threshold values for correlation coefficient and backscatter differences were determined to find the change. By our threshold values, we could achieve reasonable detection accuracy in low- and moderate-density areas.

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For quick estimation of damage building ratio due to earthquakes occurred in Peru using L-band Synthetic Aperture Radar (SAR) imagery, a regression discriminant function that uses differences and correlations of the backscattering coefficient as explanatory variables and a likelihood function for severe damage ratio were developed based on the dataset of ALOS/PALSAR images observed the 2007 Peru earthquake and the detailed field survey data of Pisco city. We also investigated the effects of pixel-window size for calculating two variables in evaluating building damage. From the analysis, an optimum window size for the damage evaluation was obtained. Finally, the model which integrates the fragility functions of building damage in terms of seismic intensity and proposed likelihood function from ALOS images was introduced.

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The authors propose a research framework in developing a method to search and detect the impact of catastrophic tsunami disaster by integrating remote sensing and GIS technologies, which consist of four damage mapping efforts, 1) Inundation mapping by satellite remote sensing, 2) Structural damage mapping by aerial photo interpretation, 3) Estimation of structural damage, 4) Mapping tsunami debris by post-event image analysis as an indicator of impact. The method is implemented to the 2011 Tohoku earthquake tsunami disaster to identify the regional impact of this event.

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Heavy casualties and severe property losses occurred by the tsunami in the Off-Pacific-Coast of Tohoku, Japan Earthquake on March 11, 2011. Satellite visible images are easy to grasp damages caused by disasters, but they cannot be obtained at nighttime. Hence a blank time of information may occur if a disaster happens at nighttime. On the other hand, satellite thermal infrared images can be taken at nighttime although it has an inferior spatial resolution. Thermal infrared images are also expected to grasp flooded areas by tsunami using the temperature distribution. This study extracted the flooded areas from ASTER thermal infrared images by calculating the difference in temperature before and after the earthquake. The examples of the extraction method were demonstrated for Soma and Ishinomaki cities, where significant tsunami damages were observed. The results were compared with ASTER false-color composite images and the inundated area map created by Geospatial Information Authority of Japan (GSI) to evaluate the accuracy of the proposed method. These comparisons show reasonable agreement of flooded areas with the daytime optical images and the GIS map. The extraction results were also compared with the distribution of the normalized difference vegetation index (NDVI) and high correlation between them was observed.

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The Tohoku earthquake on March 11, 2011, which occurred off the Pacific coast of the northeastern (Tohoku) Japan, caused gigantic tsunamis and brought vast devastation and a huge number of human casualties. Various high-resolution satellites quickly captured the details of affected areas, and were used for emergency response. In this study, the extraction of tsunami inundation areas and damaged buildings were carried out using high resolution pre- and post-event synthetic aperture radar (SAR) images. Since the water surface generally shows very low backscattering intensity, the inundation areas could be extracted by the difference of SAR backscattered intensity between the pre- and post-event images obtained by TerraSAR-X. Then, the changed buildings were detected by calculating the difference and correlation coefficient in the shape of a building. When a changed building was enclosed by the inundation areas, this building was labeled as a damaged building by tsunami. Finally, the results were compared with visual interoperation results to examine the accuracy of the proposed method.

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The 2011 off the Pacific coast of Tohoku earthquake caused extremely large tsunami. The authors conducted the field survey in Asahi, Chiba Prefecture after the occurrence of the earthquake. To reveal the extent of tsunami-inundated areas in Asahi, satellite images captured after the event were employed. Then, the polygons to show the tsunami-inundated areas were developed in the geographic information system (GIS). The authors compared the affected areas with the existing tsunami hazard map in Asahi. The relationship between the topographical characteristics and the inundated areas was also considered using the digital elevation model. In addition, the results of the numerical simulation of tsunami propagation were compared with the inundated areas interpreted using satellite images.

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We assess tsunami damage on bridge structures due to the 2011 off the Pacific Coast of Tohoku earthquake tsunami by analyzing satellite images offered by Google Earth. We obtain the inundation heights at damaged bridges due to the tsunamis by carrying out tsunami flow simulations based on shallow water theory, which are discretized by using the finite difference method with a staggered leap-flog scheme. The dependence of distances of wash-away decks and wash-away areas of abutments upon tsunami inundation heights are revealed.

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In order to make useful suggestions to future tsunami urban recovery policies, the authors examined the transition of housing location in the damaged areas due to the 2011 Great East Japan Earthquake and Tsunami in Miyagi and Iwate Prefecture, Japan. This paper analyzes the relationship between the situation of resettlement in higher land after the 1896 Tsunami and the building damage due to the 1933 Tsunami in those areas. Then, comparing the sequential aero photos between the 2011 Tsunami and the 1933 Tsunami, it presents that the damage ratio of housing had decreased in coastal areas in the objective 22 districts but the damage number of housing had increased in the objective 29 districts.

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Visual interpretation of optical satellite images is widely used to detect building damages after recent earthquakes in the world. However, since optical satellites images are acquired from the vertical direction, they can observe only roofs of buildings. Building damages such as mid-story collapse are often overlooked because the upper surfaces of buildings do not change so much. This paper proposes the method to detect this kind of building collapses from the change in building heights, estimated from the shadow lengths in optical images measured before and after an earthquake. Boumerdes city, Algeria, is selected as a case study site where many buildings were collapsed in the 2003 Boumerdes Earthquake. Two QuickBird images, taken before and two days after the earthquake, were employed. Based on the measurement of shadow lengths, some mid-story collapses were successfully detected. The measurement of building heights was also carried out using layover effects in SAR intensity images. The tests for TerraSAR-X images in Tokyo Metropolitan area showed good level of accuracy in building height measurement. These methods may provide useful information in detecting building damages, as well as from texture information.

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