人口密集沿海城市地区的灾害脆弱性映射:在印度孟买的应用

M. A. Sherly, S. Karmakar, D. Parthasarathy, T. Chan, C. Rau
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引用次数: 55

摘要

沿海城市经常面临多种灾害,包括潜在的灾难性极端事件。为解决这一问题,脆弱性评估对于制定有效的缓解战略至关重要。本研究提出了一个框架,通过考虑人口和面临风险的资产,来评估任何人口密集的城市地区对灾害的脆弱性。还提出了一套指标来评估社会和社会经济系统、基础设施、关键设施和适应能力的脆弱性。利用可访问的开源地理信息系统,在精细的1公里网格尺度上对脆弱性的组成部分进行了单独评估,从而深入了解脆弱性的空间变异性。使用数据包络分析为各个指标分配最佳权重,以最大限度地减少主观判断并建立对所得结果的置信度。为了去关联并降低多变量数据的维数,我们进行了主成分分析。所提出的方法在大孟买市政公司管辖下的孟买24个区进行了演示,结果显示孟买的中部地区是最脆弱的——主要是由于人口和边缘工人比例的增加。然而,通过提高识字率和主要工人的比例,整个城市的社会脆弱性都有所降低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Disaster Vulnerability Mapping for a Densely Populated Coastal Urban Area: An Application to Mumbai, India
Coastal urban cities frequently face multiple hazards, including potentially disastrous extreme events. To combat this, vulnerability assessment is essential to developing an effective mitigation strategy. This study proposes a framework to assess the vulnerability of any densely populated urban area to disasters by considering both the population and the assets that are at risk. A set of indicators is also proposed to assess the vulnerability of social and socioeconomic systems, infrastructure, critical facilities, and adaptive capacity. The components of vulnerability were evaluated individually, using an accessible open source geographic information system at a fine 1-km grid scale, providing an insight into the spatial variability of the vulnerability. The optimal weight for individual indicators was assigned using data envelopment analysis to minimize subjective judgment and establish confidence in the results obtained. To decorrelate and reduce the dimensionality of the multivariate data, principal component analysis was performed. The proposed methodology was demonstrated on the twenty-four wards of Mumbai under the jurisdiction of the Municipal Corporation of Greater Mumbai and showed the mideastern part of Mumbai as the most vulnerable—mainly due to the increase in population and the marginal workers' ratio. A reduction in social vulnerability has been observed, however, across the city through improvement in the literacy rate and the main workers' ratio.
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