Community resilience is becoming a growing concern for authorities and decision makers.This paper introduces two indicator-based methods to evaluate the resilience of communities based on the PEOPLES framework.PEOPLES...Community resilience is becoming a growing concern for authorities and decision makers.This paper introduces two indicator-based methods to evaluate the resilience of communities based on the PEOPLES framework.PEOPLES is a multi-layered framework that defines community resilience using seven dimensions.Each of the dimensions is described through a set of resilience indicators collected from literature and they are linked to a measure allowing the analytical computation of the indicator’s performance.The first method proposed in this paper requires data on previous disasters as an input and returns as output a performance function for each indicator and a performance function for the whole community.The second method exploits a knowledge-based fuzzy modeling for its implementation.This method allows a quantitative evaluation of the PEOPLES indicators using descriptive knowledge rather than deterministic data including the uncertainty involved in the analysis.The output of the fuzzy-based method is a resilience index for each indicator as well as a resilience index for the community.The paper also introduces an open source online tool in which the first method is implemented.A case study illustrating the application of the first method and the usage of the tool is also provided in the paper.展开更多
基金European Research Council under Grant Agreement No.ERC_IDEAL RESCUE_637842 of the project IDEAL RESCUE-Integrated Design and Control of Sustainable Communities during Emergencies
文摘Community resilience is becoming a growing concern for authorities and decision makers.This paper introduces two indicator-based methods to evaluate the resilience of communities based on the PEOPLES framework.PEOPLES is a multi-layered framework that defines community resilience using seven dimensions.Each of the dimensions is described through a set of resilience indicators collected from literature and they are linked to a measure allowing the analytical computation of the indicator’s performance.The first method proposed in this paper requires data on previous disasters as an input and returns as output a performance function for each indicator and a performance function for the whole community.The second method exploits a knowledge-based fuzzy modeling for its implementation.This method allows a quantitative evaluation of the PEOPLES indicators using descriptive knowledge rather than deterministic data including the uncertainty involved in the analysis.The output of the fuzzy-based method is a resilience index for each indicator as well as a resilience index for the community.The paper also introduces an open source online tool in which the first method is implemented.A case study illustrating the application of the first method and the usage of the tool is also provided in the paper.
