Detection of collapsed buildings caused by the 1999 Izmit, Turkey earthquake through digital analysis of post-event aerial photographs


Turker M. , SAN B. T.

INTERNATIONAL JOURNAL OF REMOTE SENSING, cilt.25, ss.4701-4714, 2004 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 25 Konu: 21
  • Basım Tarihi: 2004
  • Doi Numarası: 10.1080/01431160410001709976
  • Dergi Adı: INTERNATIONAL JOURNAL OF REMOTE SENSING
  • Sayfa Sayıları: ss.4701-4714

Özet

In this study, the post-earthquake aerial photographs were digitally processed and analysed to detect collapsed buildings caused by the Izmit, Turkey earthquake of 17 August 1999. The selected area of study encloses part of the city of Golcuk, which is one of the urban areas most strongly hit by the earthquake. The analysis relies on the idea that if a building is collapsed, then it will not have corresponding shadows. The boundaries of the buildings were available and stored in a Geographical Information System (GIS) as vector polygons. The vector building polygons were used to match the shadow casting edges of the buildings with their corresponding shadows and to perform analyses in a building-specific manner. The shadow edges of the buildings were detected through a Prewitt edge detection algorithm. For each building, the agreement was then measured between the shadow producing edges of the building polygons and the thresholded edge image based on the percentage of shadow edge pixels. If the computed percentage value was below a preset threshold then the building being assessed was declared as collapsed. Of the 80 collapsed buildings, 74 were detected correctly, providing 92.50% producer's accuracy. The overall accuracy was computed as 96.15%. The results show that the detection of the collapsed buildings through digital analysis of post-earthquake aerial photographs based on shadow information is quite encouraging. It is also demonstrated that determining the optimum threshold value for separating the collapsed from uncollapsed buildings is important.