The landscape of disaster resilience indicators in the USA
The landscape of disaster resilience indicators in the USA
复制标题
DOI：
10.1007/s11069-015-1993-2
复制
发表时间：
2016-01-01
期刊：
影响因子：
3.7
通讯作者：
Cutter, Susan L.
中科院分区：
文献类型：
--
作者：
Cutter, Susan L.
抗灾能力指标领域充斥着各种旨在以某种方式衡量抗灾能力的工具、记分卡和指数。本文探讨了现有的弹性评估定性和定量方法，以界定共同的概念和变量。研究了27种不同的复原力评估工具、指数和记分卡。四个不同的参数被用来区分他们的重点（资产基线条件），空间方向（本地到全球），方法（自上而下或自下而上），和域面积（特性的能力）。在这些特征中没有占主导地位的方法。在一个更详细的程序中，对14个基于经验的案例研究进行了检查，这些案例研究实际上使用了上述工具、指数或记分卡之一，以寻找测量概念和变量的重叠。所有评估方法中最常见的要素可分为属性和资产（经济、社会、环境、基础设施）以及能力（社会资本、社区功能、连通性和规划）。案例研究中最大的变量重叠是基于宗教信仰和民间组织的社会资本的具体措施，以及医疗服务的获得（以医生人数衡量）。在分析的基础上，提出了一套核心属性/资产、能力和替代措施，作为前进的道路，认识到可能需要新的数据来充分衡量社区抗灾能力的许多方面。
The landscape of disaster resilience indicators is littered with wide range of tools, scorecards, indices that purport to measure disaster resilience in some manner. This paper examines the existing qualitative and quantitative approaches to resilience assessment in order to delineate common concepts and variables. Twenty seven different resilience assessment tools, indices, and scorecards were examined. Four different parameters were used to distinguish between them-focus (on assets baseline conditions); spatial orientation (local to global), methodology (top down or bottom up), and domain area (characteristics to capacities). There is no dominant approach across these characteristics. In a more detailed procedure, fourteen empirically based case studies were examined that had actually implemented one of the aforementioned tools, indices, or scorecards to look for overlaps in both concepts measured and variables. The most common elements in all the assessment approaches can be divided into attributes and assets (economic, social, environmental, infrastructure) and capacities (social capital, community functions, connectivity, and planning). The greatest variable overlap in the case studies is with specific measures of social capital based on religious affiliation and civic organizations, and for health access (measured by the number of physicians). Based on the analysis a core set of attributes/assets, capacities, and proxy measures are presented as a path forward, recognizing that new data may be required to adequately measure many of the dimensions of community disaster resilience.