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Measuring Community Disaster Resilience in the Latvian Context: An Apply Case Using a Composite Indicator Approach

Abstract Despite a growing and considerable interest and implementation of disaster resilience framework methods in research, policy programs and engineering design, metrics and standards for a quantitative measuring of resilience are still an open issue. Recent literatures on hazard and disaster show that the resilience concept represents a guideline toward a valuable hazard risk management and mitigation. For the Latvian context this also represents a beneficial approach for the implementation of policy strategies based on (semi)quantitative framework aiming to enhance resilience within communities in order to properly and most efficient spend a limited availability of funds. In fact man-made and natural disasters are usually preceded by periods where communities develop toward increasing risk states until a loss occurred due to a specific disaster event. In regard to this aspect this study, principally based on the definition of the Community Disaster Resilience Framework (CDRF) developed by Mayunga, is aiming to evaluate the level of community resilience to disaster at the Latvian national level for a specific set of social, economic, human, physical, and environmental indicators. The method implements the concept of a composite-based, multi-criteria analysis aiming to measure baseline quantitative characteristics of the communities under investigation to potentially further enhance resilience within specific actions plans and/or policy mechanisms. The results are applied to the Latvian context and provide a tool to assess the variation in resilience in places giving a ranking from the most resilient region to the least.
- Riga Technical University Latvia
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).21 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
