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%.

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

GUSELLA, LUCA;BITELLI, GABRIELE;MOGNOL, ALESSANDRO
2005

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%.
2005
Gusella L.; Adams B.J.; Bitelli G.; Huyck C.K.; Mognol A.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/26364
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