An Assessment of Social Resilience against Natural Hazards through Multi-Criteria Decision Making in Geographical Setting: A Case Study of Sarpol-e Zahab, Iran

Davoud Shahpari Sani, Mohammad Taghi Heidari, Hossein Tahmasebi Mogaddam, Saman Nadizadeh Shorabeh, Saman Yousefvand, Anahita Karmpour and Jamal Jokar Arsanjani
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Davoud Shahpari Sani: Department of Demography, Faculty of Social Sciences, University of Tehran, Tehran 1417935840, Iran
Mohammad Taghi Heidari: Department of Geography, Faculty of Humanities, University of Zanjan, Zanjan 3879145371, Iran
Hossein Tahmasebi Mogaddam: Department of Geography, Faculty of Humanities, University of Zanjan, Zanjan 3879145371, Iran
Saman Nadizadeh Shorabeh: Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran 1417935840, Iran
Saman Yousefvand: Department of Sociology, Faculty of Social Sciences, University of Tehran, Tehran 1417935840, Iran
Anahita Karmpour: Department of Political & Social Science, Institute of Sociology, Freie Universität Berlin, 14195 Berlin, Germany
Jamal Jokar Arsanjani: Geoinformatics Research Group, Department of Planning and Development, Aalborg University Copenhagen, A.C. Meyers Vænge 15, DK-2450 Copenhagen, Denmark

Sustainability, 2022, vol. 14, issue 14, 1-22

Abstract: The aim of this study was to propose an approach for assessing the social resilience of citizens, using a locative multi-criteria decision-making (MCDM) model for an exemplary case study of Sarpol-e Zahab city, Iran. To do so, a set of 10 variables and 28 criteria affecting social resilience were used and their weights were measured using the Analytical Hierarchy Process, which was then inserted into the Weighted Linear Combination (WLC) model for mapping social resilience across our case study. Finally, the accuracy of the generated social resilience map, the correlation coefficient between the results of the WLC model and the accuracy level of the social resilience map were assessed, based on in-situ data collection after conducting a survey. The outcomes revealed that more than 60% of the study area falls into the low social resilience category, categorized as the most vulnerable areas. The correlation coefficient between the WLC model and the social resilience level was 79%, which proves the acceptability of our approach for mapping social resilience of citizens across cities vulnerable to diverse risks. The proposed methodological approach, which focuses on chosen data and presented discussions, borne from this study can be beneficial to a wide range of stakeholders and decision makers in prioritizing resources and efforts to benefit more vulnerable areas and inhabitants.

Keywords: social resilience; natural hazards; locative multi-criteria decision-making (MCDM) model; Sarpol-e Zahab (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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