Urban vulnerability under various blast loading scenarios: Analysis using GIS-based multi-criteria decision analysis techniques. (February 2018)

• Record Type: Journal Article
• Authors: Ebrahimian Ghajari, Yasser; Alesheikh, Ali Asghar; Modiri, Mahdi; Hosnavi, Reza; Abbasi, Morteza; Sharifi, Ayyoob
• Is Part Of: Cities. Volume 72(2018)Part A
• Page Start: 102
• Page End: 114
• Publication Date: 2018-02
• Subjects: Physical vulnerability -- Multi-criteria evaluation -- Geospatial Information Systems -- Blast loading -- Ordered Weighted Averaging; City planning -- Periodicals; Urban policy -- Periodicals; 711.4
• DOI: 10.1016/j.cities.2017.08.006
• Languages: English
• ISSNs: 0264-2751

Abstract

Abstract: This paper examines physical vulnerability of District No. 6 of Tehran to blast damages and blast loads. The main objectives are to enhance planners and decision makers' awareness of the extent of vulnerability of buildings in the study area (under different risk scenarios) and to provide guidance on how to enhance preparedness against potential risks. Physical vulnerability of District No. 6 of Tehran was evaluated under three different blast loading scenarios. An expert survey, involving specialists with expertise in urban development, passive defense, construction, and architecture was carried out to extract fourteen vulnerability criteria. Fuzzy criteria maps corresponding to each of these criteria were produced in Geospatial Information Systems (GIS) environment. Fuzzy analytic hierarchy processing was used to weigh the criteria. Criterion maps were combined using the fuzzy weighted linear combination operator. Finally, Ordered Weighted Averaging (OWA) operator was applied to generate final vulnerability maps. Results show that, for all scenarios, almost 70% of the buildings in the district are of high vulnerability. Sensitivity analysis confirms the reliability of the model. Highlights: Vulnerability of buildings in District No.6 of Tehran is examined. Three different scenarios are developed for vulnerability analysis. GIS and Multi Criteria Decision Making (MCDM) techniques are utilized for generating vulnerability maps. Results show that about 70% of the buildings are of high vulnerability. Density, age, height, and lot coverage ratio are the main factors that contribute to vulnerability.