Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 63-69, 2016
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B2/63/2016/
doi:10.5194/isprs-archives-XLI-B2-63-2016
 
07 Jun 2016
SPATIAL-TEMPORAL DYNAMICS OF URBAN FIRE INCIDENTS: A CASE STUDY OF NANJING, CHINA
J. Yao1 and X. Zhang2 1Urban Big Data Centre, University of Glasgow, 7 Lilybank Gardens, Glasgow, G12 8RZ UK
2Dept. of Geographical Information Science, Hohai University, 1 Xikang Road, Nanjing, 210098, China
Keywords: Urban Fire, ESDA, Spatial-temporal Analyses 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 safer living environment. Well understanding spatial-temporal dynamics of fire incidents can offer insights for potential determinants of various fire events and enable better fire risk estimation, assisting future allocation of prevention resources and strategic planning of mitigation programs. Using a 12-year (2002-2013) dataset containing the urban fire events in Nanjing, China, this research explores the spatial-temporal dynamics of urban fire incidents. A range of exploratory spatial data analysis (ESDA) approaches and tools, such as spatial kernel density and co-maps, are employed to examine the spatial, temporal and spatial-temporal variations of the fire events. Particular attention has been paid to two types of fire incidents: residential properties and local facilities, due to their relatively higher occurrence frequencies. The results demonstrated that the amount of urban fire has greatly increased in the last decade and spatial-temporal distribution of fire events vary among different incident types, which implies varying impact of potential influencing factors for further investigation.
Conference paper (PDF, 1203 KB)


Citation: Yao, J. and Zhang, X.: SPATIAL-TEMPORAL DYNAMICS OF URBAN FIRE INCIDENTS: A CASE STUDY OF NANJING, CHINA, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 63-69, doi:10.5194/isprs-archives-XLI-B2-63-2016, 2016.

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