Multi-level detection of damaged buildings from high-resolution optical satellite images

This paper presents a newly developed multi-level detection methodology using high-resolution optical satellite images. It aims to balance the quick response requirement and the details of detected results and hence, to satisfy various user demands. Damage extent is firstly detected from only post-disaster image on the first level, texture-based processing. This level quickly maps the damage extent and damage distribution but not in details. In some focused areas, the second level with object-based processing will derive further details of the damage using both pre- and post-data. The methodology is demonstrated on QuickBird images acquired over the damage areas of Barn, Iran, which was extensively devastated by the December 2003 earthquake. The detected results show a good agreement with the ones by visual detection and field survey.