Urban Fire Dynamics and Its Association with Urban Growth: Evidence from Nanjing, China

Abstract

Many Chinese cities currently are facing increased urban fire risks particularly at places such as urban villages, high-rise buildings and large warehouses. Using a unique historical fire incident dataset (2002–2013), this paper is intended to explore the urban fire dynamics and its association with urban growth in Nanjing, China, with a geographical information system (GIS)-based spatial analytics and remote sensing (RS) techniques. A new method is proposed to define a range of fire hot spots characterizing different phases of fire incident evolution, which are compared with the urban growth in the same periods. The results suggest that the fire events have been largely concentrated in the city proper and meanwhile expanding towards the suburbs, which has a similar temporal trend to the growth of population and urban land at the city level particularly since 2008. Most intensifying and persistent fire hot spots are found in the central districts, which have limited urban expansion but high population densities. Most new hot spots are located in the suburban districts, which have seen both rapid population growth and urban expansion in recent years. However, the analysis at a finer spatial scale (500 m × 500 m) shows no evidences of an explicit connection between the locations of new fire hot spots and recently developed urban land. The findings can inform future urban and emergency planning with respect to the deployment of fire and rescue resources, ultimately improving urban fire safety.

Cluster-Based Relocation of Stations for Efficient Forest Fire Management in the Province of Valencia (Spain)

“…As the number of clusters increases, the different k-means distributions produce faster times to reach fires with a clear trend. While in the interval [20,25] there is a gain of 57 in terms of t avg , in the interval [25,30] this gain is reduced to 38 . In order to display this data in a more visual way, Figure 6 represents the time saved for different numbers of clusters, each of them obtained with respect to the distribution with one cluster less.…”

“…Localization requirements are different depending on the scenario [ 17 ]. Travel times from fire stations are always critical, but even more so when the fire is located in the surroundings of a petrol station [ 18 ] or in high-density population areas [ 19 , 20 ].…”

Certainty Factor Analyses and Spatiotemporal Characteristics of Landslide Evolution: Case Studies in the Chishan River Watershed in Taiwan

“…The emerging hotspot analysis technique for spatiotemporal analysis has been used by several scholars to investigate the transmission of the COVID-19 virus [15][16][17], explore temporal changes in the volume of capture fisheries [18], investigate the distribution of traffic accidents [19,20], track pollutant emissions [21], and analyze the relationship between urban growth and urban fire [22]. Moreover, this new technique has been used to explain the patterns and characteristics of the long-term landslide evolution after extreme-rainfallinduced landslide events in Taiwan [12,13].…”

GIS-based urban village regional fire risk assessment and mapping

“…A fire in an area causes economic loss; therefore, it needs fire disaster management. Urban fire disaster management research is carried out in many countries such as China, India, Iran; with results showing that densely populated urban areas are at risk of fire (Chan et al, 2018;Kumar, Ramamritham, & Jana, 2019;Navitas, 2014;Waheed, 2014;Zhang, Yao, Sila-Nowicka, & Jin, 2020).…”