Remote Sensing for Resilient Multi-Hazard Disaster Response, Volume III: Multi-Sensor Image Fusion Techniques for Robust Neighborhood-Scale Urban Damage Assessment

Keywords: Remote sensing. Multi-hazard disaster response. Disaster resiliency. Damage assessments. Multi-sensor image fusion techniques. Bam, Iran earthquake, December 26, 2003. Satellite imagery. Quickbird. IKONOS. Damage detection.

Abstract: This report investigates multi-sensor pixel-based image fusion methodologies, combing ‘before’ and ‘after’ images from two different high-resolution optical satellites (Quickbird and IKONOS), to assess neighborhood damage extent and severity. The 2003 earthquake that struck Bam, Iran is used as a case study. Three different pixel-based methodological approaches were used to investigate damage-related changes: spectral comparison, textural comparison and edge-based comparison. The results showed that all three damage detection methods successfully identified building collapse within neighborhoods of Bam. This is Volume III of a five part series of reports that investigate the use of remote sensing techniques for resilient multi-hazard disaster response.