Object‐Oriented Image Understanding and Post‐Earthquake Damage Assessment for the 2003 Bam, Iran, Earthquake

Abstract

This paper presents a methodology for quantifying the number of buildings that collapsed following the Bam earthquake. The approach is object rather than pixel‐oriented, commencing with the inventory of buildings as objects in high‐resolution QuickBird satellite imagery captured before the event. The number of collapsed structures is computed based on the unique statistical characteristics of these objects/buildings within the “after” scene. A total of 18,872 structures were identified within Bam, of which the results suggest that 34% collapsed—a total of 6,473. Preliminary assessments indicate an overall accuracy for the damage classification of 70.5%.