Damage estimation caused by an earthquake is a major task in the post-disaster mitigation process. To enhance the relief and rescue operation in the affected area, it is required to receive rapid and accurate knowledge about the conditions of damaged area. Remote sensing techniques were proved to be useful in the last decades in detecting, identifying and monitoring the impact and effect of natural disasters. Recently emerging LiDAR data provide the height of the ground objects, which can be used to extract the collapsed building in a complex urban environment. Using the aerophotographs and the normalized digital surface model (nDSM) extracted from LiDAR data, the authors developed a method based on OBIA and SVM for extracting the earthquake-caused collapsed building. The test study in Port-au-Prince, Haiti’s capital, after January 12,2010 earthquake shows that the method can extract collapsed buildings with high accuracy of 86.1%.
于海洋, 程钢, 张育民, 卢小平. 基于LiDAR和航空影像的地震灾害倒塌建筑物信息提取[J]. 国土资源遥感, 2011, 23(3): 77-81.
YU Hai-yang, CHENG Gang, ZHANG Yu-min, LU Xiao-ping. The Detection of Earthquake-caused Collapsed Building Information from LiDAR Data and Aerophotograph. REMOTE SENSING FOR LAND & RESOURCES, 2011, 23(3): 77-81.
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2011, Vol. 23 
