Urban safety production risk assessment supported by spatial big data

doi:10.13474/j.cnki.11-2246.2023.0188

Abstract

Abstract: Most of the existing studies on urban safety production risk assessment are based on statistical survey data to assess a single enterprise or park, and without sufficiently considering the spatial effect of safety production accidents, which is difficult to adapt to the urban scale safety production risk assessment. Based on the H-V risk assessment framework, this paper constructs the urban safety production risk assessment system by comprehensively analyzing regional hazard factors, regional target exposure and regional rescue adaptation. With the support of multi-source geospatial data, the urban safety production risk index is quantified based on spatial analysis to reveal the distribution pattern of urban safety production risk, which could provide decision-making knowledge service for the prevention and control of urban production safety. Taking Kunshan as the study area, the urban safety production risk assessment supported by spatial big data is realized. The experimental results show that the high-risk areas of safety production in Kunshan are mainly concentrated in the east and south of Yushan Town, and the risk of disaster factors is higher in the south of Yushan Town, while the risk of disaster factors and regional target exposure are higher in the east of Yushan Town.

Key words: geographic big data, urban safety production, risk assessment

CLC Number:

P208

HE Keqin, CHENG Nanwei, DENG Min. Urban safety production risk assessment supported by spatial big data[J]. Bulletin of Surveying and Mapping, 2023, 0(6): 167-171.

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