基于LiDAR和航空影像的地震灾害倒塌建筑物信息提取

The Detection of Earthquake-caused Collapsed Building Information from LiDAR Data and Aerophotograph

地震灾害损失评估是震后展开救灾工作的重要环节。快速、准确地获取震后损毁建筑物信息能够为灾区减灾、救灾工作提供有效的支持。高分辨率航空遥感是灾害监测的重要技术手段,但其信息自动提取的精度受到一定的限制。近年来新出现的LiDAR技术能够提供地面目标的高程信息,可应用于复杂环境下倒塌建筑物信息的提取。研究中采用航空遥感数据和LiDAR数据,基于面向对象的图像分析(Object-Based Image Analysis,OBIA)与SVM技术相结合的方法对2010年1月12日海地地震中倒塌建筑物信息进行了提取,提取总体精度达到86.1%。

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%.