Constructing a comprehensive disaster resilience index: The case of Italy

Measuring disaster resilience is a key component of successful disaster risk management and climate change adaptation. Quantitative, indicator-based assessments are typically applied to evaluate resilience by combining various indicators of performance into a single composite index. Building upon extensive research on social vulnerability and coping/adaptive capacity, we first develop an original, comprehensive disaster resilience index (CDRI) at municipal level across Italy, to support the implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030. As next, we perform extensive sensitivity and robustness analysis to assess how various methodological choices, especially the normalisation and aggregation methods applied, influence the ensuing rankings. The results show patterns of social vulnerability and resilience with sizeable variability across the northern and southern regions. We propose several statistical methods to allow decision makers to explore the territorial, social and economic disparities, and choose aggregation methods best suitable for the various policy purposes. These methods are based on linear and non-liner normalization approaches combining the OWA and LSP aggregators. Robust resilience rankings are determined by relative dominance across multiple methods. The dominance measures can be used as a decision-making benchmark for climate change adaptation and disaster risk management strategies and plans.

灾害韧性（disaster resilience）评估是成功实施灾害风险管理与气候变化适应举措的核心组成部分。当前学界普遍采用基于指标的定量评估范式，将多维度绩效指标整合为单一综合指数，以此开展韧性水平评估。基于社会脆弱性与应对/适应能力领域的深厚研究积淀，本研究率先构建了覆盖意大利全域市域尺度的原创性综合灾害韧性指数（Comprehensive Disaster Resilience Index, CDRI），以支撑《2015-2030年仙台减少灾害风险框架》的落地执行。后续，本研究开展了系统性敏感性与稳健性分析，以研判不同方法论选择——尤其是所采用的标准化与聚合方法——对最终韧性排名的影响机制。研究结果揭示了社会脆弱性与灾害韧性的空间分布规律，意大利南北区域间二者的异质性特征十分显著。本研究提出了多套统计分析方法，助力决策者探究区域、社会与经济维度的发展差距，并遴选适配不同政策目标的最优聚合方案。该类方法依托线性与非线性标准化路径，整合了有序加权平均（Ordered Weighted Averaging, OWA）与LSP聚合器。基于多方法相对占优性，可生成稳健可靠的韧性排名结果。该占优性测度指标可作为气候变化适应与灾害风险管理战略及规划的决策基准。