Spatial heterogeneity and influencing factors of urban emergency services

TIAN Fengshi; SUN Zhanhui; ZHENG Xin; YIN Yanfu

doi:10.16511/j.cnki.qhdxxb.2023.22.004

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Journal of Tsinghua University(Science and Technology) ›› 2023, Vol. 63 ›› Issue (6) : 888-899. DOI: 10.16511/j.cnki.qhdxxb.2023.22.004

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Spatial heterogeneity and influencing factors of urban emergency services

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Abstract

[Objective] Urban emergency services are mainly divided into fire suppression and technical rescues. Relatively more studies have been conducted on fire suppression, whereas relatively fewer studies have focused on technical rescues. Thus, this study aims to map the spatial distribution of fire suppression and technical rescues on a city scale and build their connections quantitatively to the human population and mobility. The findings are expected to help in the planning of urban emergency services to follow the major task change from fire suppression to technical rescues.[Methods] The global spatial autocorrelation of fire suppression, technical rescues, and their totality — whole emergency services — was assessed using global spatial autocorrelation analysis Moran's I, whereas the local components were indexed with local indicators of spatial association and Getis-Ord G^*_i. The human population and mobility were modeled through the point of interest (POI) and visitor throughput, respectively. Through the stepwise regression method, five broad categories of POI data (14 minor categories of POI) of the highest sensitivities were selected from the available 30 categories of POI. Their associations with fire suppression, technical rescues, and the whole emergency services were established using the multiscale geographically weighted regression (MGWR) model.[Results] Both fire suppression and technical rescues were found to have a certain degree of spatial clustering, but some differences were noted in the spatial distribution of different emergency service types. Old towns were the concentrated hot spots for fire suppression, whereas the formation of additional clusters of technical rescues was extensively distributed; thus, more multiregional linkage and targeted prevention were required for technical rescues than fire suppression. The POI data of residential premises, office premises (such as office buildings, and public administration and public service institutions), industrial premises (such as industrial parks and mines), educational premises (such as schools, scientific research institutions, and training institutions), and commercial premises (such as supermarkets, convenience stores, home appliance stores, digital device stores, beauty salons), and visitor throughput were closely connected to emergency services. The applied MGWR model overtook both the traditional multiple linear regression and conventional GWR, with the goodness of fit R² exceeding 0.8 for fire suppression, technical rescues, and overall emergency services. The residual sum of squares and the corrected Akaike information criterion (AICc) had the smallest values in the MGWR model. The correlation of the local visitor throughput and POIs (e.g., residential buildings, offices, and retail stores) to local fire suppressions were approximately spatially uniform. By contrast, the connections of other POIs (e.g., offices, schools, and industrial parks) to fire suppression and technical rescues varied across the present city domain.[Conclusions] The findings indicate that targeted prevention should be employed in the present city's emergency services according to the local POI distribution and should be steered to technical rescues which have become the main part of the overall emergency services. This study provides an important reference for future emergency preparedness and response, regional prevention work, and location planning of new fire stations.

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fire safety / fire disaster / technical rescue / spatial analysis / multiscale geographically weighted regression (MGWR)

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TIAN Fengshi, SUN Zhanhui, ZHENG Xin, YIN Yanfu. Spatial heterogeneity and influencing factors of urban emergency services[J]. Journal of Tsinghua University(Science and Technology). 2023, 63(6): 888-899 https://doi.org/10.16511/j.cnki.qhdxxb.2023.22.004

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