加强城市应急响应：基于欧几里得距离的优化救援设施布局框架
Chengye Ma, Mingxing Song, Weitao Zeng, Xinuo Wang, Tao Chen, Shihai Wu (Corresponding Author)
原文发表于Sustainable Cities and Society
Ma, C., Song, M., Zeng, W., Wang, X., Chen, T., & Wu, S. (2025). Enhancing urban emergency response: A Euclidean distance-based framework for optimizing rescue facility layouts. Sustainable Cities and Society, 118, 106006. https://doi.org/10.1016/j.scs.2024.106006
Abstract：This study presents a Euclidean distance-based framework for optimizing the layout of urban emergency rescue facilities. Traditional precinct-based (Type 1) and dynamic time-based (Type 2) models are compared with the proposed Euclidean distance-based (Type 3) model. The analysis uses geospatial and statistical methods to evaluate accessibility, variability, and fairness across different times of the day. The results indicate that the Euclidean distance-based model enhances rescue response efficiency and maintains a more equitable service distribution relative to traditional models. The study identifies a “threshold effect” in rescue times, emphasizing the critical distance beyond which rescue efficiency declines. By leveraging real-time traffic data and integrating Euclidean distance principles, the proposed framework offers a robust and practical approach for urban planners to improve emergency response capabilities and urban resilience. This research underscores the importance of considering both geometric proximity and dynamic traffic conditions in the strategic placement of rescue facilities, providing valuable insights for future urban emergency management and planning.
摘要：本文提出了一个基于距离的欧氏距离框架，用于优化城市应急救援设施的布局。将传统的基于辖区（Type 1）和基于动态时间（Type 2）的模型与所提出的基于距离的欧几里得距离（Type 3）模型进行了比较。该分析使用地理空间和统计学方法来评估一天中不同时间的可达性、时变性和公平性。结果表明，与传统模型相比，基于欧氏距离的模型提高了救援响应效率，并实现了更公平的服务分配。该研究发现了救援时间与距离的“阈值效应”，强调了救援效率下降的临界距离。通过利用实时交通数据并整合欧几里得距离原则，拟议的框架为城市规划者提供了一种强大而实用的方法，以提高应急响应能力和城市韧性。本研究强调了在救援设施的战略布局中同时考虑几何布局和动态交通状况的重要性，为未来的城市应急管理和规划提供了有价值的建议。
论文主要图表
Fig. 1. The framework of this study, including three steps: (1) extraction and acquisition of data related to urban emergency rescue; (2) acquisition of spatiotemporal accessibility and travel time costs calculation; (3) data analysis including accessibility analysis, fairness analysis, standard deviation analysis, and the threshold effect of the Euclidean distance.
图1.本研究的框架，包括三个步骤：（1） 提取和获取城市应急救援相关数据;（2） 时空可达性和旅行时间成本的获取计算;（3） 数据分析，包括可达性分析、公平性分析、标准差分析和欧几里得距离的阈值效应。
表 2 三种应急响应模式的描述和图形表示
Fig. 2. Location of the study area and the spatial distribution of the settlement AOI, facilities POI and the precinct of the facility (right panel)
图 2.研究区域的位置和聚落 AOI、设施点 POI 和设施区的空间分布（右）
Fig. 3. Reachability analysis for Type1, Type2, and Type3 emergency rescue networks at different times of the day.
图 3.Type1、Type2 和 Type3 紧急救援网络在一天中不同时间的可达性分析。
图 4.散点图和分布曲线显示了Type1、Type2和Type3响应模式在一天中六个不同时间的距离（单位：公里）与旅行时间成本（单位：秒）之间的相关性。
Fig. 5. Violin plots depicting the distribution of rescue travel time costs (in seconds) for Type1, Type2, and Type3 response modes at six representative times.
图 5.提琴图描述了Type1、Type2和Type3响应模式在6个时间切片的救援交通时间成本（单位：秒）的分布。
Fig. 6. Accessibility Lorenz curve and accessibility Gini coefficient in 6 moments.
图 6.选取的6个时刻的可达性洛伦兹曲线和可达性基尼系数。
Fig. 7. Scatter plots illustrating the correlation between distance (km) and time cost (seconds) for six different times of the day
图 7.散点图说明了一天中 6 个不同时间的距离（单位：公里）和时间成本（单位：秒）之间的相关性
Fig. 8. Combined regression analysis of threshold changes in time/distance for all data across six time periods.
图 8.对6个时间切片的所有数据的时间-距离阈值变化进行组合回归分析。
Fig. 9. Spatial distribution of accessibility standard deviation of dynamic network in 6 moments.
图 9.动态时间网络下6个时间切片的可达性标准差的空间分布
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