Extraction of earthquake damage buildings from multi-source remote sensing data based on correlation change detection and object-oriented classification techniques

Object-oriented classification technology of remote sensing images, as a spatial information extraction method, plays a key role in earthquake damage information extraction. However, it has limitations in extracting buildings from optical remote sensing images due to the characteristic vulnerable to weather and other reasons. To solve this problem, this paper proposes a method for detecting building damage by optical image in combiniation with SAR correlation changes and object-oriented classification, which extracts buildings from fusion data including optical image and SAR correlation image. Not only the spatial and spectral features, but also the correlation of buildings is considered during the extraction. The M_S8.0 Wenchuan earthquake caused a wide range of building’s collapse and casualties. Taking Dujiangyan area near the source as an example, the method above is tested. The results show that the accuracy of building extraction is improved by using the proposed method compared with the method only from optical image.