Displaying earthquake damage in an urban area using a vegetation – impervious – soil model and remotely sensed data


Kaya, S., Llewellyn, G. and Curran, P.J. (2004) Displaying earthquake damage in an urban area using a vegetation – impervious – soil model and remotely sensed data. In, Proceedings of the International Society for Photogrammetry and Remote Sensing Conference. International Society for Photogrammetry and Remote Sensing Conference Istanbul, Turkey, International Society for Photogrammetry and Remote Sensing, 634-638.

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Description/Abstract

The aim of this study was to use remotely sensed data to record earthquake-induced land cover change. On 17 August 1999, an earthquake struck northwestern Turkey, at 3:01:17 a.m. local time and lasted about 40 seconds. The most heavily damaged area was around the Gulf of Izmit and the city of Adapazari. The towns of Golcuk and Yalova, along the southern shore of the Gulf, the harbour city of Izmit at the eastern end of the Gulf, the town of Sapanca about 40 km east of Izmit and the city of Adapazari 50 km east of Izmit were sites of massive structural damage and extensive ground failure. The pre-earthquake and post-earthquake SPOT HRV images of the city of Adapazari were geometrically corrected and classified and revealed that 7.1 % of the post-earthquake area comprised collapsed buildings. The trend and relative magnitude of earthquake-induced land cover change were displayed using the Vegetation, Impervious, Soil (V-I-S) model.

Item Type: Book Section
Related URLs:
Keywords: spot hrv data, earthquake, land cover, vegetation-impervious-soil model, adapazari, classification
Subjects: G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography
G Geography. Anthropology. Recreation > GE Environmental Sciences
Divisions: University Structure - Pre August 2011 > School of Geography > Remote Sensing and Spatial Analysis
ePrint ID: 15576
Date Deposited: 06 May 2005
Last Modified: 27 Mar 2014 18:06
Publisher: International Society for Photogrammetry and Remote Sensing
URI: http://eprints.soton.ac.uk/id/eprint/15576

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