Spatial Optimization of Urban Fire Stations Based on the SAVEE Model

Fire emergency service is an important part of urban public health and safety system,and the rationality of its layout directly affects the efficiency of disaster relief response. In this paper, the central urban area of Kunming City is selected as the study area, based on POI, road network and other geospatial data, through AHP hierarchical analysis method and SAVEE model, to realize the identification of potential fire risk area and suitable area for fire stations siting in the study area, and to use the model for minimizing the Number of facilities for spatial optimization of fire station siting. The results show that: 1) the fire risk assessment system is applicable to the study area, and the fire risk is mainly distributed in the northwestern part of the study area; 2) the layout of the existing fire stations is limited, and the existing coverage rate reaches only 71.47%; 3) 6 new fire station sites are added, and the coverage rate increases by 19.75%, and the total coverage rate reaches 91.22%, and the optimized indexes have been greatly improved.

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Publication Details

Journal
Academic Journal of Science and Technology
Published
2025-04-21
DOI
https://doi.org/10.54097/pjdrm911
Primary Topic
Evacuation and Crowd Dynamics
Type
article
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article

Spatial Optimization of Urban Fire Stations Based on the SAVEE Model

Han Yang, Aimei Chen
Academic Journal of Science and Technology
Evacuation and Crowd Dynamics
article

Spatial Optimization of Urban Fire Stations Based on the SAVEE Model

Han Yang, Aimei Chen
article en

Abstract

Fire emergency service is an important part of urban public health and safety system,and the rationality of its layout directly affects the efficiency of disaster relief response. In this paper, the central urban area of Kunming City is selected as the study area, based on POI, road network and other geospatial data, through AHP hierarchical analysis method and SAVEE model, to realize the identification of potential fire risk area and suitable area for fire stations siting in the study area, and to use the model for minimizing the Number of facilities for spatial optimization of fire station siting. The results show that: 1) the fire risk assessment system is applicable to the study area, and the fire risk is mainly distributed in the northwestern part of the study area; 2) the layout of the existing fire stations is limited, and the existing coverage rate reaches only 71.47%; 3) 6 new fire station sites are added, and the coverage rate increases by 19.75%, and the total coverage rate reaches 91.22%, and the optimized indexes have been greatly improved.

Academic Journal of Science and TechnologyVol. 15(1)
Southwest Forestry University (CN)
Openalex Percentile: Top 89%
Evacuation and Crowd Dynamics
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Spatial Optimization of Urban Fire Stations Based on the SAVEE Model — Han Yang, Aimei Chen · Academic Journal of Science and Technology (2025) | TGRS Research Map | TGRS