Earthquake-induced built-up damage identification using IRS-P6 data: a comparative study using fuzzy-based classifiers |
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| Authors: | Sandeep Singh Sengar Anil Kumar Sanjay Kumar Ghosh Hans Raj Wason |
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| Institution: | 1. Earthquake Engineering Department , Indian Institute of Technology Roorkee , Roorkee , 247667 , India talktosengar@yahoo.co.in;3. Indian Institute of Remote Sensing, Indian Space Research Organization , Dehradun , 248001 , India;4. Department of Civil Engineering , Indian Institute of Technology Roorkee , Roorkee , 247667 , India;5. Earthquake Engineering Department , Indian Institute of Technology Roorkee , Roorkee , 247667 , India |
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| Abstract: | The 8 October 2005 earthquake caused widespread destruction in both the state of Jammu and Kashmir of India and Northern Pakistan. Due to poor accessibility in the hazardous and difficult mountainous terrain, a proper and comprehensive ground-based survey was not possible. However, with the help of remote sensing data and its analysis techniques, it is feasible to undertake both earthquake-related damage identification and assessment. This study attempts to document and identify built-up damaged (BD) areas using spectral indices taking temporal multispectral images from IRS-P6 LISS-IV. Five spectral indices have been used to identify BD areas using supervised possibilistic c-means (PCM) and noise cluster (NC) classifiers, to analyse the satellite data. The result indicates that Class Based Sensor Independent (CBSI) based Transformed Normalized Difference Vegetation Index (TNDVI) temporal indices provide the best results for identifying BD areas, while Simple Ratio (SR) index gives the best results for built-up undamaged area identification. Further, it observed that PCM classifier performed better in comparison to NC classifier. |
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| Keywords: | temporal indices entropy noise cluster (NC) possibilistic c-means (PCM) Kashmir earthquake built-up damage (BD) |
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