Disaster Risk Evaluation and Damage Detection Using Remote Sensing Data for Global Rescue Operations

In this study, for supporting global rescue operations, we will propose a new earthquake damage detection method, based on a combination of earthquake damage estimation using earthquake information (magnitude, location of source, detailed ground condition, and attenuation equation for distance) and change detection by means of remote sensing data. First, to find collapsed buildings and houses on the earth’s surface, we adopt a coherence or difference image calculated from multi-temporal SAR images observed before and after the earthquake. Next, to estimate seismic intensity and probability of destruction caused by the earthquake, we applied an earthquake engineering model. Finally, damaged area is calculated from a logical AND of the coherence or difference image and destruction probability. As a result of our simulation, we were able to obtain a damage detection map that corresponds with the actual damage of houses. The detection map has less noise than the coherence or difference image, which indicates that the proposed method has better detection ability than that of using only the change observed by SAR.