A GIS–Analytic Network Process Framework for Fire Station Site Selection in Cities Experiencing Urban Sprawl

There is an interrelationship between community growth and the volume of emergency incidents. As the population increases, the chance of incidents rises as well. Urban sprawl reduces emergency accessibility and challenges equitable fire service coverage. Considering the fact that Mashhad and Calgary both are populated cities and are expanding in a fast-paced way, this expansion not only can heighten the response time for emergency services but also jeopardize the safety of the growing population. To prevent that, the proper placement of fire station is significant within these cities. In this study, the primary objective is to find the suitable sites for locating urban fire stations in Mashhad (Iran) and Calgary (Canada) which was achieved through the adaptation of GIS and ANP. Twelve sub-criteria were considered and categorized into four classes: "Service Area", "Accessibility", "Environment" and "Spatial Characteristics", also their weights were determined. Using the weight for each sub-criterion and ArcGIS PRO the optimal sites for fire stations were recognized. The final outcomes reveal that response time and distance from faults and rivers have the highest and the lowest weight respectively. 33% and 8% of city blocks are highly suitable for locating fire stations in Mashhad and Calgary respectively. The majority of the highly prioritized areas were centered in zones with higher response times obtaining the highest values in categories of spatial and environmental characteristics and accessibility. Moreover, 34% and 15% of existing fire stations in Mashhad and Calgary are located in highly prioritized blocks with values of 8 and 9. Therefore, generating optimal fire station site selection maps assists urban planners and decision-makers to keep more areas under cover and reduces the likelihood of dangers caused by a fire. The proposed framework provides a transferable decision-support tool for disaster risk reduction in rapidly growing cities.