A spatial disaster assessment model of social resilience based on geographically weighted regression

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. © 2017 by the authors.