主管：中华人民共和国应急管理部
主办：应急管理部天津消防研究所
ISSN 1009-0029  CN 12-1311/TU
消防科学与技术

消防科学与技术 ›› 2026, Vol. 45 ›› Issue (5): 107-115.

• • 上一篇    下一篇

基于可达性的县域消防站布局优化研究

赵文涛1,2, 刘顶立1,2, 杨婧1,2, 袁狄平2   

  1. （1.长沙理工大学 交通学院，湖南 长沙 410114； 2.中国矿业大学深圳研究院，广东 深圳 518000）
  • 收稿日期:2025-02-08 修回日期:2025-06-06 出版日期:2026-05-15 发布日期:2026-05-15
  • 作者简介:赵文涛，长沙理工大学交通学院硕士研究生，主要从事消防救援资源配置及优化研究，湖南省长沙市天心区万家丽南路二段960号，410114。
  • 基金资助:
    国家自然科学基金青年项目（52204202）；湖南省自然科学基金青年科学基金项目（B类）（2026JJ40069）；深圳市科技计划资助（KCXFZ20230731093902005）；长沙理工大学研究生科研创新项目（CLKYCX25004）

Optimization study of county fire station layout based on accessibility

Zhao Wentao1,2, Liu Dingli1,2, Yang Jing1,2, Yuan Diping2   

  1. (1. School of Transportation, Changsha University of Science and Technology, Changsha Hunan 410114, China; 2. Shenzhen Research Institute, China University of Mining and Technology, Shenzhen Guangdong 518000, China)
  • Received:2025-02-08 Revised:2025-06-06 Online:2026-05-15 Published:2026-05-15

摘要： 现有的消防站布局方面的研究主要集中于城区，鲜有关注以乡村为主体的县域。本文针对县域消防站布局优化的需求，提出了城乡消防救援可达性综合评价方法。针对城乡火灾风险的差异，分别制定了城乡可达性等级划分标准。通过融合历史火灾数据和POI（兴趣点）数据确定消防救援需求点，以城市消防站和乡镇专职消防站为消防救援供应点。根据城乡平均火灾直接财产损失比值加权综合计算县域消防救援可达性。以SD县为例，收集了16 040个需求点，并以既有的2个城市消防站和13个乡镇专职消防站为供应点，基于在线地图实时路况仿真计算消防救援行驶时间。在一个完整的工作日内设置29个评估场景，每个场景包含16 040个样本，总计465 160个样本。结果表明，可达性等级为Ⅰ级和Ⅱ级的需求点数量累计占比为50.30%，且存在多个响应时间过长区域。分析发现，这是由于该区域缺少乡镇专职消防站。因此，提出在这些区域建设8个乡镇专职消防站为优化方案。经再次评价，优化方案实施后可达性等级为Ⅰ级和Ⅱ级的需求点数量累计占比提升了10.76%，达到61.06%。本文提出的城乡消防救援可达性综合评价方法还可应用于其他县域的消防站布局优化。

关键词: 县域, 消防站, 可达性, 消防救援, 火灾数据统计

Abstract: Previous studies on the layout of fire stations predominantly focuses on urban areas, with limited attention given to counties primarily composed of rural regions. In response to the need for optimizing the layout of fire stations in counties, a comprehensive evaluation method for the accessibility of urban and rural fire rescue is proposed in this paper. Considering the differences in fire risks between urban and rural areas, different standards for accessibility classification are established. Fire rescue demand points are identified by integrating fire data and point of interest data, with urban fire stations and township full-time fire stations serving as supply points for fire rescue. The accessibility of fire rescue in the county is then weighted and comprehensively calculated based on the average ratio of fire direct property losses in urban and rural areas. Taking SD County as an example, 16 040 demand points were collected, and the existing 2 urban fire stations and 13 township full-time fire stations were used as supply points. The travel time for fire rescue was simulated based on real-time road conditions from online maps. A total of 29 evaluation scenarios were set within a full working day, each containing 16 040 samples, amounting to 465 160 samples in total. The results indicate that the cumulative proportion of demand points with accessibility levels Ⅰ and Ⅱ is 50.30%, with several areas experiencing excessively long response times. Analysis reveals that this is due to the lack of township full-time fire stations in these regions. Therefore, a proposal is made to construct 8 township full-time fire stations in these areas as an optimization plan. Upon re-evaluation, the cumulative proportion of demand points with accessibility levels Ⅰ and Ⅱ increased by 10.76% to 61.06% after the implementation of the optimization plan. The comprehensive evaluation method for urban and rural fire rescue accessibility proposed in this study can also be applied to the optimization of fire station layouts in other counties.

Key words: county, fire station, accessibility, fire rescue, fire data statistics