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A GIS-Based Fuzzy Decision Making Model for Seismic Vulnerability Assessment in Areas with Incomplete Data

Sadrykia, Mansoureh, Delavar, Mahmoud Reza, Zare, Mehdi
ISPRS international journal of geo-information 2017 v.6 no.4
decision making, disasters, earthquakes, geographic information systems, geophysics, models, risk assessment, uncertainty
Earthquakes are one of the natural disasters that threaten many lives every year. It is important to estimate seismic damages in advance to be able to reduce future losses. However, seismic vulnerability assessment is a complicated problem, especially in areas with incomplete data, due to incorporated uncertainties. Therefore, it is important to use adequate methods that take into account and handle the associated uncertainties. Although different seismic vulnerability assessment methods at the urban scale have been proposed, the purpose of this research is to introduce a new Geospatial Information System GIS-based model using a modified integration of Analytical Hierarchy Process (AHP), fuzzy sets theory, and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) in a vector-based environment. The proposed method emphasizes handling one of the important uncertainties in areas with incomplete data, namely the ‘vagueness’ of the existing knowledge about influences of the criteria on seismic vulnerability, which is handled using fuzzy sets theory in this research. The applicability of the proposed method is tested in a municipality district of Tabriz, which is in a near vicinity to the fault system. It can be concluded that the proposed method contributes to a pragmatic and efficient assessment of physical seismic vulnerability under uncertainty, which provides useful information for assisting planners in mitigation and preparation stages in less-studied areas.