Search

The measurement of spatial accessibility of fire services is a key task in enhancing fire response efficiency and minimizing property losses and deaths. Recently, the two-step floating catchment area method and its modified versions have been widely applied. However, the circle catchment areas used in these methods are not suitable for measuring the accessibility of fire services because each fire station is often responsible for the fire incidents within its coverage. Meanwhile, most existing methods take the demographic data and their centroids of residential areas as the demands and locations, respectively, which makes it difficult to reflect the actual demands and locations of fire services. Thus, this paper proposes a fixed-coverage-based two-step floating catchment area (FC2SFCA) method that takes the fixed service coverage of fire stations as the catchment area and the locations and dispatched fire engines of historical fire incidents as the demand location and size, respectively, to measure the spatial accessibility of fire services. Using a case study area in Nanjing, China, the proposed FC2SFCA and enhanced two-step floating catchment area (E2SFCA) are employed to measure and compare the spatial accessibility of fire incidents and fire stations. The results show that (1) the spatial accessibility across Nanjing, China is unbalanced, with relatively high spatial accessibility in the areas around fire stations and the southwest and northeast at the city center area and relatively low spatial accessibility in the periphery and boundary of the service coverage areas and the core of the city center; (2) compared with E2SFCA, FC2SFCA is less influenced by other fire stations and provides greater actual fire service accessibility; (3) the spatial accessibility of fire services is more strongly affected by the number of fire incidents than firefighting capabilities, the area of service coverage, or the average number of crossroads (per kilometer). Suggestions are then made to improve the overall spatial access to fire services. [ABSTRACT FROM AUTHOR]

Pick-up and drop-off events of taxi trajectory data contain rich information about residents' travel activities and road traffic. Such data have been widely applied in urban hotspot detection in recent years. However, few studies have attempted to delimitate the urban hotspot scope using taxi trajectory data. On this basis, the current study firstly introduces a network-based spatiotemporal field (NSF) clustering approach to discover and identify hotspots. Our proposed method expands the notion from spatial to space–time dimension and from Euclidean to network space by comparing with traditional spatial clustering analyses. In addition, a concentration index of hotspot areas is presented to refine the surface of centredness to delimitate the hotspot scope further. This index supports the quantitative depiction of hotspot areas by generating two standard deviation isolines. In the case study, we analyze the spatiotemporal dynamic patterns of hotspots at different days and times of day using the NSF method. Meanwhile, we also validate the effectiveness of the proposed method in identifying hotspots to evaluate the delimitating results. Experimental results reveal that the proposed approach can not only help detect detailed microscale characteristics of urban hotspots but also identify high-concentration patterns of pick-up incidents in specific places. [ABSTRACT FROM AUTHOR]