Work

A holistic geospatial framework for assessing disaster resilience in coastal Bangladesh

Year: 2025
Type: article
Abstract: Coastal regions, while highly productive, are increasingly exposed to natural and anthropogenic stressors. Hence, strengthening their resilience is vital for sustainable development. This study evaluates the resilience of coastal Bangladesh through a geospatial framework integrating three critical yet often independently analyzed dimensions: ecosystems, social attributes, and critical infrastructure. Three indices were constructed using distinct methods: The ecosystem resilience index (EsRI) via weighted overlay analysis, the social resilience index (SoRI) through Principal Component Analysis (PCA), and the critical infrastructure resilience index (CiRI) using network analysis, addressing limitations of one-size-fits-all approaches common in earlier studies. These were integrated into a composite Coastal Disaster Resilience Index (CDRI) for a holistic resilience-assessment. The CDRI revealed pronounced spatial disparities: 62% of the coastal region fell into very low (15%) or low (47%) resilience categories, 33% was moderate, and only 5% high, with almost no area attaining very high resilience. The western zone showed comparatively higher resilience (7% high, 37% moderate), though districts such as Bagerhat, Satkhira, and Barguna remained largely low-resilient. The central zone was the most vulnerable, with 71% of its area in very low or low categories, notably Bhola, Chandpur, and Noakhali. The eastern zone also exhibited 71% low resilience, though localized higher resilience was observed in Chattogram City Corporation. A bivariate resilience-threat analysis identified Satkhira, Khulna, and Noakhali as priority districts for urgent interventions, while Chattogram and Cox’s Bazar for long-term resilience planning. The current study advances resilience research and provides policymakers with a rigorous and transferable decision-support tool for targeted interventions aligned with the SDGs and Sendai Framework.
Institution: University of Dhaka
Language: English
Open Access status: diamond
OpenAlex ID: W4414805920
FWCI: 3.592
Cites: 109
Cited by: 2
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