Building damage detection from post-earthquake aerial imagery using building grey-value and gradient orientation analyses

The collapsed buildings due to 1999 Kocaeli earthquake were detected from post-event panchromatic aerial imagery based on grey-value and the gradient orientation of the buildings. The building boundaries were available and stored in a GIS as vector polygons. The building polygons were utilized to perform the assessments in a building specific manner. The approach was implemented in a selected area of Golcuk, which is one of the urban areas most strongly hit by the earthquake. First, the buildings were selected one-by-one from the integrated vector (building boundaries) and raster (aerial photo) data set. The building damage detection process was then divided into two branches. In the first branch, the detection was performed using the building grey-value information. To do that, a greyvalue threshold (T1) was determined for discriminating the collapsed buildings from the un-collapsed ones. In the second branch, a group of operations including the gradient calculation and the determination of gradient orientation were performed. By utilizing the orientation information, an optimum threshold level (T2) was determined for the standard deviation of the angle distribution of the building pixels. When assessing the condition of a building, the results of the two branches were combined and a final decision was made in an integrated manner. Of the 284 buildings analyzed, 254 were labeled correctly as collapsed or un-collapsed providing an overall accuracy of 89.44%. The results reveal that the collapsed buildings due to the earthquake can be successfully detected from post-event aerial images.