Optimizing Fire Station Locations for the Istanbul Metropolitan Municipality

Abstract

The Istanbul Metropolitan Municipality (IMM) seeks to determine locations for additional fire stations to build in Istanbul; its objective is to make residences and historic sites reachable by emergency vehicles within five minutes of a fire station's receipt of a service request. In this paper, we discuss our development of a mathematical model to aid IMM in determining these locations by using data retrieved from its fire incident records. We use a geographic information system to implement the model on Istanbul's road network, and solve two location models, set covering and maximal covering, as what-if scenarios. We discuss 10 scenarios, including the situation that existed when we initiated the project and the scenario that IMM implemented. The scenario implemented increases the city's fire station coverage from 58.6 percent to 85.9 percent, based on a five-minute response time, with an implementation plan that spans three years.

Applications of Location Analysis

“…Badri et al (1998) structured a model to minimize the maximum distance demand was from a sited fire station, applying this in Dubai, United Arab Emirates. Coverage models were also used in Catay (2011) as well as Aktas et al (2013) for fire station planning in Istanbul, Turkey. In Singapore, separate studies by and Huang and Fan (2011) relied on an MCLP based approach for fire station siting.…”

“…Schilling et al (1980) detailed an approach to add a constraint restricting the number of existing facilities to utilize. This was done most recently in the study reported in Aktas et al (2013). A different sort of approach is to assume that no facilities exist in the first place, then carry out the analysis to provide comparison of what could be possible if a region were able to begin anew.…”

Obstacle‐limited service coverage: A new geospatial approach

“…A drone will fly directly to a destination unless it has to avoid an obstacle. For a service that is constrained to travel via a pre‐defined network, assessment is rather straightforward as the options are finite (Aktaş, Özaydın, Bozkaya, Ülengin, & Önsel, ). For services that move freely through space, such as drone‐based delivery (Pulver & Wei, ) and watercraft (Akbari, Eiselt, & Pelot, ), the number of options for travel are infinite.…”

Spatial optimisation of fire service coverage: a case study of Brisbane, Australia

“…Residential fires 1 pose a significant threat to human life and property, especially in large and rapidly growing cities (Aktaş et al, 2013). To mitigate fire risk, emergency services adopt a Service Delivery Standards (SDSs) framework that establishes a minimum response time to emergency calls (Chevalier et al, 2012).…”

“…While much of the existing literature on fire station planning has employed location models, to date no studies have drawn on small area population estimates to plan for and appropriately locate new fire stations. It is crucial to examine the optimal spatial coverage to maximise response to calls for fire services to determine the strategic location of new fire stations particularly in relation to current and future population demand (Aktaş et al, 2013).…”