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Sustainability 2017, 9(12), 2222; doi:10.3390/su9122222 (registering DOI)

A Spatial Disaster Assessment Model of Social Resilience Based on Geographically Weighted Regression

1
Graduate Student, Department of Civil and Environmental Engineering, Seoul National University, 1 Gwanak-Ro, Gwanak-Ku, Seoul 08826, Korea
2
Associate Professor, Dept. of Civil and Environment Engineering, Seoul National University, 1 Gwanak-Ro, Gwanak-Ku, Seoul 08826, Korea; Adjunct Professor, the Institute of Construction and Environmental Engineering (ICEE), 1 Gwanak-Ro, Gwanak-Ku, Seoul 08826, Korea
3
Associate Professor, Department of Building, National University of Singapore, Architecture Drive 4, Singapore
*
Author to whom correspondence should be addressed.
Received: 6 October 2017 / Revised: 27 November 2017 / Accepted: 28 November 2017 / Published: 4 December 2017
(This article belongs to the Special Issue Management Strategies and Innovations for Sustainable Construction)
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Abstract

Since avoiding the occurrence of natural disasters is difficult, building ‘resilient cities’ is gaining more attention as a common objective within urban communities. By enhancing community resilience, it is possible to minimize the direct and indirect losses from disasters. However, current studies have focused more on physical aspects, despite the fact that social aspects may have a closer relation to the inhabitants. The objective of this paper is to develop an assessment model for social resilience by measuring the heterogeneity of local indicators that are related to disaster risk. Firstly, variables were selected by investigating previous assessment models with statistical verification. Secondly, spatial heterogeneity was analyzed using the Geographically Weighted Regression (GWR) method. A case study was then undertaken on a flood-prone area in the metropolitan city, Seoul, South Korea. Based on the findings, the paper proposes a new spatial disaster assessment model that can be used for disaster management at the local levels. View Full-Text
Keywords: disaster assessment; social resilience; Geographically Weighted Regression (GWR) disaster assessment; social resilience; Geographically Weighted Regression (GWR)
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Chun, H.; Chi, S.; Hwang, B.G. A Spatial Disaster Assessment Model of Social Resilience Based on Geographically Weighted Regression. Sustainability 2017, 9, 2222.

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