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Measuring Community Disaster Resilience in the Conterminous Coastal United States.

Authors :
Rifat, Shaikh Abdullah Al
Liu, Weibo
Source :
ISPRS International Journal of Geo-Information. Aug2020, Vol. 9 Issue 8, p469. 1p.
Publication Year :
2020

Abstract

In recent years, building resilient communities to disasters has become one of the core objectives in the field of disaster management globally. Despite being frequently targeted and severely impacted by disasters, the geographical extent in studying disaster resilience of the coastal communities of the United States (US) has been limited. In this study, we developed a composite community disaster resilience index (CCDRI) for the coastal communities of the conterminous US that considers different dimensions of disaster resilience. The resilience variables used to construct the CCDRI were justified by examining their influence on disaster losses using ordinary least squares (OLS) and geographically weighted regression (GWR) models. Results suggest that the CCDRI score ranges from −12.73 (least resilient) to 8.69 (most resilient), and northeastern communities are comparatively more resilient than southeastern communities in the study area. Additionally, resilience components used in this study have statistically significant impact on minimizing disaster losses. The GWR model performs much better in explaining the variances while regressing the disaster property damage against the resilience components (explains 72% variance) than the OLS (explains 32% variance) suggesting that spatial variations of resilience components should be accounted for an effective disaster management program. Moreover, findings from this study could provide local emergency managers and decision-makers with unique insights for enhancing overall community resilience to disasters and minimizing disaster impacts in the study area. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22209964
Volume :
9
Issue :
8
Database :
Academic Search Index
Journal :
ISPRS International Journal of Geo-Information
Publication Type :
Academic Journal
Accession number :
145370142
Full Text :
https://doi.org/10.3390/ijgi9080469