| 摘要: |
| 消防救援空间可达性是衡量城市消
防救援效率及消防资源配置情况的重要指
标。文章运用了火灾统计数据、消防救援站
点地理空间数据、出行圈数据及百度街景数
据等多源大数据，构建了一种基于百度驾车
路线规划API 等时圈，街景图像分析为补充
的消防救援可达性评估方法。以柳州市为实
例，从火灾风险和消防救援可达性两方面对
城市消防安全进行评估，并通过实地调研与
走访消防管理部门验证评估结果有效性。结
果表明：消防安全风险最高区域集中在老市
区中心商业步行街及其周边老旧住宅区，原
因除该区域火灾隐患大外，步行街区各出入
口受违章停放车辆影响，道路通畅度低，老
旧住宅区由于早期规划欠考虑，道路曲折狭
窄严重影响消防救援车辆通行效率，从而降
低区域消防救援可达性，对此提出优化改进
建议。本文构建“火灾风险评价—救援等时
圈评价—道路通畅度评价”模型，从多元视
角展开论证，为更科学地开展城市消防安全
研究提供了一种方法借鉴。 |
| 关键词: 等时圈 街景图像 多源数据 百
度地图API 消防救援 可达性 |
| DOI：10.13791/j.cnki.hsfwest.20231016002 |
| 分类号: |
| 基金项目:国家自然科学基金项目（52168003） |
|
| Identification and enhancement of firefighting accessibility in urban street based on multisourcedata: Case of Liuzhou |
|
ZHAI Yingying,ZHAI Hui,TENG Shaoxian,LU Jie
|
| Abstract: |
| Accessibility to firefighting and rescue operations serves as a critical indicator for assessing
the efficiency of urban fire and rescue operations and the allocation of firefighting resources.
Functional departments can optimize and improve regions with areas lacking sufficient firefighting
services by analyzing the spatial accessibility of fire and rescue services, thereby enhancing the
overall efficiency of urban firefighting and rescue efforts. Utilizing the driving route planning
Application Programming Interface (API) of internet map technologies, it is possible to accurately
estimate the distance and time between any two points based on real-time traffic conditions. This
facilitates the calculation of fire and rescue accessibility on a macro urban scale. However, the driving
route planning API’s data collection samples are based on standard passenger vehicles and do not
comprehensively consider the real-world scenarios of fire trucks. Recently, the application of artificial
intelligence technologies has enabled the evaluation of urban environments based on street view
images across extensive spatial scales. Street view image data can intuitively reflect the accessibility
of urban streets, providing a basis for assessing the passability of fire and rescue vehicles. This offers
a more specific and realistic reflection of firefighting and rescue accessibility. Therefore, this study
proposes an urban firefighting and rescue accessibility evaluation approach based on isochrone
models with supplementary street view analysis. The research employs a multifaceted methodology
using diverse datasets including fire statistics, geospatial data of fire and rescue stations, isochrone
data, and Baidu street view data to develop a firefighting and rescue accessibility assessment method
based on Baidu’s driving route planning API isochrones and supplemented by street view image
analysis. Taking Liuzhou city as a case study, the fire safety of the city is assessed from the aspects of
fire risk and firefighting and rescue accessibility. Firstly, the fire risk levels of regions are determined
using historical fire data. Secondly, isochrones of fire stations are established using Baidu Maps
driving route planning API to preliminarily analyze the accessibility of central urban area fire stations.
This process aims to identify high-risk fire districts characterized by both high fire risk and low rescue
accessibility. Thirdly, utilizing the Baidu Open Platform Panoramic Static Map API to obtain the street
view of high-risk fire jurisdiction areas, conducting more precise isochronous analysis and street view
data analysis on high-risk fire jurisdiction areas, and combining expert scoring methods to supplement
and revise the accessibility of fire rescue within high-risk fire jurisdiction areas, obtaining the results
of fire safety assessment in the jurisdiction. Fourthly, the validity of the assessment results is verified
through field surveys and consultations with fire management departments, and suggestions forfirefighting planning and improvements are proposed. The results indicate that areas in Liuzhou City with high fire risk and low rescue accessibility are
primarily distributed around Beizhan Fire Station’s jurisdiction, with the highest fire safety risk concentrated in the central old city’s commercial pedestrian
streets and surrounding old residential areas. These regions have high population and building densities, frequent use of fire and electricity, and outdated
electrical facilities and equipment due to their age, thereby posing a high fire risk. Moreover, access points in pedestrian street areas are often obstructed by
illegally parked vehicles, which reduces road accessibility. In the old residential areas, inadequate early planning has resulted in narrow and winding roads, as
well as vertical obstructions such as community gates and overhead cables, severely impeding the efficiency of firefighting and rescue vehicle movement,
thereby reducing the accessibility of firefighting and rescue services in the area. Recommendations for optimization and improvement include: 1) areas within a
5-minute isochrone of fire stations that are accessible but have poor road conditions should focus on strengthening fire management, such as establishing
parking facilities and enhancing parking control at vehicle-restricted entry points of high-rise pedestrian commercial districts. Attention should also be paid to
clearing internal roads in old neighborhoods that are still in use, enhancing connectivity between these neighborhoods and city roads to provide more rescue
route options, and addressing vertical restrictions on firefighting vehicles, such as overhead cables and community gates; 2) areas outside the 5-minute
isochrone of fire stations should install intelligent early warning systems and establish small fire stations on the basis of improving the fire safety environment,
enhance community volunteer fire safety training, and ensure timely presence of rescue forces to tackle initial fires.This paper develops a “fire risk assessmentrescue
isochrone evaluation-road accessibility evaluation” model, arguing from qualitative and quantitative perspectives, planar and elevational views, macro
and micro levels, and “theoretical” (big data) and “practical” (field research) multidimensional perspectives, providing a methodological reference for
conducting more scientific urban fire safety research. |
| Key words: isochronous model street view image multi-source data Baidu Maps API fire rescue spatial accessibility |
