Next Article in Journal
Spatial Analysis of Asymmetry in the Development of Tourism Infrastructure in the Borderlands: The Case of the Bystrzyckie and Orlickie Mountains
Next Article in Special Issue
Integrating a Three-Level GIS Framework and a Graph Model to Track, Represent, and Analyze the Dynamic Activities of Tidal Flats
Previous Article in Journal
Map Generalization for the Future: Editorial Comments on the Special Issue
Article

Measuring Community Disaster Resilience in the Conterminous Coastal United States

Department of Geosciences, Florida Atlantic University, Boca Raton, FL 33431, USA
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(8), 469; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9080469
Received: 27 June 2020 / Revised: 20 July 2020 / Accepted: 21 July 2020 / Published: 23 July 2020
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. View Full-Text
Keywords: composite community disaster resilience index (CCDRI); coastal United States; ordinary least squares (OLS); geographically weighted regression (GWR) composite community disaster resilience index (CCDRI); coastal United States; ordinary least squares (OLS); geographically weighted regression (GWR)
Show Figures

Figure 1

MDPI and ACS Style

Rifat, S.A.A.; Liu, W. Measuring Community Disaster Resilience in the Conterminous Coastal United States. ISPRS Int. J. Geo-Inf. 2020, 9, 469. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9080469

AMA Style

Rifat SAA, Liu W. Measuring Community Disaster Resilience in the Conterminous Coastal United States. ISPRS International Journal of Geo-Information. 2020; 9(8):469. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9080469

Chicago/Turabian Style

Rifat, Shaikh A.A., and Weibo Liu. 2020. "Measuring Community Disaster Resilience in the Conterminous Coastal United States" ISPRS International Journal of Geo-Information 9, no. 8: 469. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9080469

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop