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Disaster resilience in Pakistan: A comprehensive multi-dimensional spatial profiling
Applied Geography ( IF 4.732 ) Pub Date : 2021-01-01 , DOI: 10.1016/j.apgeog.2020.102367
Muhammad Sajjad

Abstract Building disaster-resilient communities require operative resilience frameworks enabling factual decision-making and resource allocation at national and sub-national scales. While Pakistan is frequently hit by several natural hazards (i.e., floods, droughts, earthquakes, and extreme heatwaves) resulting in devastating impacts, no national-level higher-resolution disaster resilience information is available to provide references for informed planning. Hence, this study provides a, first of its kind, multi-level comprehensive disaster resilience evaluation in Pakistan. To do so, data on a customized list of indicators within three key resilience sub-components (i.e., economic, institutional, and social) are acquired to compute a resilience index. Frequency distribution and the Analysis of Variance (ANOVA) methods are employed to analyse the differences between different resilience indices and a cross-regional assessment is carried out at the sub-national level. Subsequently, an extensive spatial assessment is performed using geo-information models (i.e., Global Moran's I, Local Indicators of Spatial Association, and machine learning-based multivariate clustering) to explore the global and local geographies of the resilience. Based on ANOVA, significant differences between the resilience sub-components are found (95% confidence). The geographical distribution of resilience scores ascertains a large spatial heterogeneity across the study area with the least resilient regions belonging to Sindh and Balochistan provinces (95% confidence). As shown by the machine learning-based multivariate clustering, the least resilient regions particularly lack in economic and institutional aspects of disaster resilience. The findings provide important references to ensure resilience management-related cross-regional equity and justice. The rigorous analyses regarding the geographies of disaster resilience in Pakistan are important to support the country's disaster risk reduction efforts. While the results are useful for practitioners, decision-makers, and professionals in the risk management field, the study has important policy-relevant implications in the context of disaster risk mitigation strategies.

中文翻译:

巴基斯坦的抗灾能力:全面的多维空间分析

摘要 建设抗灾社区需要有效的抗灾框架,能够在国家和次国家范围内进行实际决策和资源分配。虽然巴基斯坦经常遭受多种自然灾害(即洪水、干旱、地震和极端热浪)的袭击,造成毁灭性影响,但尚无国家级更高分辨率的抗灾能力信息可用于为知情规划提供参考。因此,本研究提供了巴基斯坦首创的多层次综合灾害复原力评估。为此,需要获取三个关键复原力子组成部分(即经济、制度和社会)内的自定义指标列表的数据,以计算复原力指数。采用频率分布和方差分析 (ANOVA) 方法来分析不同复原力指数之间的差异,并在次国家级进行跨区域评估。随后,使用地理信息模型(即 Global Moran's I、空间关联的本地指标和基于机器学习的多元聚类)进行广泛的空间评估,以探索弹性的全球和本地地理。基于方差分析,发现弹性子组件之间存在显着差异(95% 置信度)。复原力分数的地理分布确定了整个研究区域的巨大空间异质性,其中复原力最低的地区属于信德省和俾路支省(95% 置信度)。正如基于机器学习的多元聚类所表明的那样,复原力最差的地区尤其缺乏灾害复原力的经济和制度方面。研究结果为确保与弹性管理相关的跨区域公平和正义提供了重要参考。对巴基斯坦抗灾能力地理的严格分析对于支持该国减少灾害风险的努力非常重要。虽然结果对风险管理领域的从业者、决策者和专业人士有用,但该研究在减轻灾害风险战略的背景下具有重要的政策相关意义。研究结果为确保与弹性管理相关的跨区域公平和正义提供了重要参考。对巴基斯坦抗灾能力地理的严格分析对于支持该国减少灾害风险的努力非常重要。虽然结果对风险管理领域的从业者、决策者和专业人士有用,但该研究在减轻灾害风险战略的背景下具有重要的政策相关意义。研究结果为确保与弹性管理相关的跨区域公平和正义提供了重要参考。对巴基斯坦抗灾能力地理的严格分析对于支持该国减少灾害风险的努力非常重要。虽然结果对风险管理领域的从业者、决策者和专业人士有用,但该研究在减轻灾害风险战略的背景下具有重要的政策相关意义。
更新日期:2021-01-01
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