Urban flooding is a growing source of natural hazards, significantly threatening the safety of sustainable development in cities. The distribution of flood risks is heterogeneous, so it is crucial to allocate emergency resources reasonably. This article develops an analytical framework to evaluate the effect of urban flooding on emergency responses based on social sensing data. Initially, we designed a Weibo search pattern and used natural language processing technologies to get high-risk flood points. Then, assuming that such high-risk flood points can disrupt traffic, we assessed urban emergency shelter accessibility after flooding events. Finally, we carried out an evaluation of spatial fairness between population and emergency shelter accessibility through spatial correlation analysis. We analyzed the urban area of Nanjing as a case study, extracting 37 high-risk flood points from the past 5 years. The results highlight that existing emergency shelters fall short in accommodating the needs of urban residents under disaster conditions. This disparity is notably amplified in high-risk flood points. By measuring the impact of flooding quantitatively, we expect to promote a more comprehensive management on urban flood risks.

中文翻译：

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基于社会感知数据评估城市洪水对应急避难所空间可达性的影响

城市洪水是日益严重的自然灾害来源，严重威胁着城市可持续发展的安全。洪水风险分布具有异质性，合理配置应急资源至关重要。本文开发了一个分析框架，根据社会感知数据评估城市洪水对应急响应的影响。最初，我们设计了微博搜索模式，并使用自然语言处理技术来获取高风险洪水点。然后，假设此类高风险洪水点会扰乱交通，我们评估了洪水事件后城市应急避难所的可达性。最后，通过空间相关分析，对人口与应急避难场所可达性之间的空间公平性进行了评价。我们以南京市区为例进行分析，提取了过去5年的37个高风险洪水点。结果表明，现有的应急避难所无法满足城市居民在灾害情况下的需求。这种差异在高风险洪水点尤其明显。通过定量衡量洪水的影响，我们期望促进城市洪水风险更加全面的管理。