Fire and rescue services are among the most critical public services provided by governments to protect people, property and the environment. Efficient deployment of fire stations is essential to ensure timely response to calls for service. With GIS-based spatial analytics, this paper explores urban fire dynamics using a unique database of fire incidents (2002-2013) provided by the Fire Department of Ministry of Public Security of Nanjing, China. Based on the historical fire events, it evaluates locational efficiency of existing fire stations and seeks locations for future stations by a bi-objective spatial optimization model.
About the Speaker:
Dr Jing Yao (姚 静) is Lecturer in Urban Big Data and Quantitative Methods at the UK ESRC-funded Urban Big Data Centre. She has a PhD in Geography and a MSc in Industrial Engineering both from Arizona State University (ASU), USA. She also has a MSc degree and a BSc degree in Geographical Information System from Nanjing University, China. Previously she worked as a postdoctoral associate at the GeoDa Center for Geospatial Analysis and Computation at ASU in the US and a research fellow at Centre for Geoinformatics at University of St Andrews in UK. Jing’s research interests cover a wide range of areas in GIScience, including spatial statistics, spatial modeling, and spatial optimization, etc. Currently, she focuses on developing quantitative methods for spatially integrated analysis and modeling as well as their applications in urban studies.
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