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MCEER Earthquake Reconnaissance Investigation

Within residential districts of Bam (Figure 7), entire blocks of family homes have been destroyed. Their distinct footprint and white roof in the before image, is replaced by chaotic piles of brown rubble (see also Figure 2c through Figure 2e). With buildings constructed from local materials, the sand-colored debris is difficult to distinguish from the sandy ground surface.


Image shows clear buildings and roads
Image shows  blurry roads and dots of rubble
(a) before (b) after
Image shows clear buidlings and roads
Image shows  blurry roads and dots of rubble
(c) before (d) after
Image shows clear buildings and roads
mage shows  blurry roads and dots of rubble
(e) before (f) after

Click here for larger version

Figure 7 Building damage within eastern residential districts of Bam, visualized by comparing the ‘before’ and ‘after’ QuickBird satellite imagery. Imagery courtesy of DigitalGlobe,

Future Research

This research program will continue working towards an end goal of robust damage detection algorithms that can be rapidly deployed in future earthquakes to aid response and recovery efforts. From a methodological perspective, findings from the 1999 Turkey, and 2003 Algerian and Iranian events, will be consolidated, and existing optical damage detection algorithms refined and augmented with new capabilities. In particular, the integration of SAR satellite imagery would enable 24/7, all weather damage assessment. While damage detection algorithms presently map the general occurrence of building collapse, future research will explore a refined scaling that expresses damage severity and extent. In terms of research implementation, VIEWS technology will be extended to include these refinements, and on the basis of feedback from field reconnaissance teams, enhanced to optimize performance during future deployments. In achieving these objectives, collaboration will continue with U.S. and International research partners.


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