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Evaluating the severity of building fires with the analytical hierarchy process, big data analysis, and remote sensing

Authors :
Yuan-Shang Lin
Yu-Chi Sung
Ching-An Lee
Gary Li-Kai Hsiao
Source :
Natural Hazards. 103:1843-1856
Publication Year :
2020
Publisher :
Springer Science and Business Media LLC, 2020.

Abstract

This study assessed the severity of building fires in 17 villages that comprise Taishan District, New Taipei City, Taiwan. A literature review was performed to discuss the impact of fire severity assessment criteria in order to develop items and factors for the analytic hierarchy process (AHP). We identified six items for the building fire severity assessment: rescue response time, narrow road density, water-sacristy area density, building risk, hazardous materials’ place density, and fire safety inspection-regulated premises density. Big data analysis and remote sensing were employed to facilitate devising the AHP structure with items and factors. We also compared the annual average burned area from 2005 to 2015 through the building fire severity assessment to validate assessment accuracy. The actual yearly average burned area in each village of Taishan District was used to verify the building fire severity assessment, and the compliance rate of the rating (i.e., high, moderate, and low) was, respectively, 60%, 67%, and 67%. The proposed assessment is evidently feasible and can act as a reference for quantitative analyses for assessments of building fire severity.

Details

ISSN :
15730840 and 0921030X
Volume :
103
Database :
OpenAIRE
Journal :
Natural Hazards
Accession number :
edsair.doi...........22b593db6028be956c761333da474922