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GIScience 2016 Short Paper Proceedings Location Optimization of Fire Stations: Trade-off between Accessibility and Service Coverage J. Yao 1 , X. Zhang 2 Urban Big Data Centre, University of Glasgow, 7 Lilybank Gardens, Glasgow, G12 8RZ, UK Email: Jing.Yao@glasgow.ac.uk Department of Geographical Information Science, Hohai University, 1 Xikang Road, Nanjing, 210098, China Email: Xiaoxiang@hhu.edu.cn Abstract Fire and rescue service is one of the fundamental public services provided by government in order to protect people, properties and environment from fires and other disasters, and thus promote a safe living environment. Efficient deployment of fire stations is necessary and essential if timely response to the emergencies is to be achieved. Spatial optimization approaches have been long employed in public facility location studies. In particular, coverage-based models, such as the location set covering problem (LSCP) and the maximum coverage location problem (MCLP), have been widely adopted to achieve complete or maximum coverage of service demand. This paper extends the LSCP by accounting for both partial coverage and access to the demand areas. The proposed model is applied to the optimization of fire station locations in Nanjing, China. The results can be used to assist future fire station location planning and rescue resource deployment. 1. Introduction Fire caused by humans or nature can pose hazard to people, properties and environment, and lead to psychological damage, physical injuries (even death) and significant economic losses. Fire prevention and protection is necessary and essential for a safe living environment. The associated fire and rescue service therefore needs to be properly deployed to ensure efficient fire safety management. A fundamental concern in this regard is the spatial configuration of fire stations as it is critical to timely response to emergency calls. Given the inherent spatial nature, fire station location problems have been well studied using geographical information system (GIS)-coupled location modelling (Chevalier et al. 2012; Aktas et al. 2013; Murray 2013). In particular, LSCP (Toregas et al. 1971), MCLP (Church and ReVelle 1974) and their extensions have long been employed to evaluate the locational efficiency of existing fire stations as well as seek sites for new fire stations (Chevalier et al. 2012; Murray 2013). Common goals of locating fire stations include maximizing the access to provided services, covering as much demand as possible and minimizing total costs of service provision, usually subject to available resources. In practice, two or more objectives are often considered to capture different aspects in relation to fire service delivery. The aim of this paper is to seek best locations of fire stations with spatial optimization approaches, particularly considering accessibility and service coverage. The proposed model is applied in an empirical study in Nanjing, China, to assist future fire station location planning and rescue resource deployment.