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Remote Sensing for Resilient Multi-Hazard Disaster Response. Volume III: Multi-Sensor Image Fusion Techniques for Robust Neighborhood-Scale Urban Damage Assessment.
Adams, B. J.; McMillan, A.
Multidisciplinary Center for Earthquake Engineering Research, Buffalo, NY.; Federal Highway Administration, Washington, DC.; National Science Foundation, Arlington, VA. Earthquake Engineering Research Centers Program., November 17, 2008, 166 p.
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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.
Remote sensing imagery; Debris mapping; Case studies; Resilient multi-hazard disaster response; Iran; Edge detection; Aerial photographs; Image fusion; Damage assessments; 2003 Bam earthquake; Urban damage assessments; Multi-sensor pixel-based image fusion; Spctral comparison; Texture-based comparison; Optical satellites; Quickbird; IKONOS