Multiscale GIS based-model to assess urban social vulnerability and associated risk: Evidence from 146 urban centers of Eastern India

Abstract

Social vulnerability in this study is expressed by highlighting the different forms of social deprivation experienced by the urban inhabitants. This article proposes a fundamental approach to quantify social vulnerability and associated risk in urban areas. Here, urban social vulnerability (USoV) consists of three interconnected dimensions, i.e. exposure, sensitivity, and adaptive capacity. Based on these three dimensions’ the urban social vulnerability index (USoVI) was computed using 15 indicators. Therefore, using the GIS environment, a composite measure is applied to identify and map the spatial heterogeneity of USoV for the 146 urban centres in Eastern India. The results highlight that most urban locations experience moderate to high exposure, sensitivity and low adaptive capacity corresponding to high USoV. Moran's I result indicates that the adaptive capacity shows the largest spatial association, while sensitivity indicates the lowest Moran value with the least association. Also, the spatial distribution pattern of USoVI across the urban centres is assessed by using the Univariate LISA techniques. The multiscale geographically weighted regression (MGWR) model estimates 67.4% variance of the constructed model. The study findings assist policymakers and urban stakeholders in devising an effective, participatory, and geographically targeted plan for coping with potential bottlenecks experienced by urban residents.