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.