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

摘要

This report investigates multi-sensor pixel-based image fusion methodologies, combining 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.