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Location Optimization of Urban Fire Stations Considering the Backup Coverage

Urban fires threaten the economic stability and safety of urban residents. Therefore, the limited number of fire stations should cover as many places as possible. Moreover, places with high fire risk should be covered by more fire stations. To optimize the location of urban fire stations, we constru...

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Detalles Bibliográficos
Autores principales: Tao, Liufeng, Cui, Yuqiong, Xu, Yongyang, Chen, Zhanlong, Guo, Han, Huang, Bo, Xie, Zhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9819386/
https://www.ncbi.nlm.nih.gov/pubmed/36612949
http://dx.doi.org/10.3390/ijerph20010627
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author Tao, Liufeng
Cui, Yuqiong
Xu, Yongyang
Chen, Zhanlong
Guo, Han
Huang, Bo
Xie, Zhong
author_facet Tao, Liufeng
Cui, Yuqiong
Xu, Yongyang
Chen, Zhanlong
Guo, Han
Huang, Bo
Xie, Zhong
author_sort Tao, Liufeng
collection PubMed
description Urban fires threaten the economic stability and safety of urban residents. Therefore, the limited number of fire stations should cover as many places as possible. Moreover, places with high fire risk should be covered by more fire stations. To optimize the location of urban fire stations, we construct a multi-objective optimization model for fire station planning based on the backup coverage model. The improved value of environment and ecosystem (SAVEE) model is introduced to quantify the spatial heterogeneity of urban fires. The main city zone of Wuhan is used as the study area to validate the proposed method. The results show that, considering the existing fire stations (85 facilities), the proposed model achieves a significant 38.56% in high-risk areas that can be covered by more than one fire station. If the existing fire stations are not considered when building 95 fire stations, the proposed model can achieve coverage of 50.07% in high-risk areas by utilizing more than one fire station. As a result, the proposed backup coverage model would perform better if the protection of high-risk areas is improved with as few fire stations as possible to guarantee more places covered.
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spelling pubmed-98193862023-01-07 Location Optimization of Urban Fire Stations Considering the Backup Coverage Tao, Liufeng Cui, Yuqiong Xu, Yongyang Chen, Zhanlong Guo, Han Huang, Bo Xie, Zhong Int J Environ Res Public Health Article Urban fires threaten the economic stability and safety of urban residents. Therefore, the limited number of fire stations should cover as many places as possible. Moreover, places with high fire risk should be covered by more fire stations. To optimize the location of urban fire stations, we construct a multi-objective optimization model for fire station planning based on the backup coverage model. The improved value of environment and ecosystem (SAVEE) model is introduced to quantify the spatial heterogeneity of urban fires. The main city zone of Wuhan is used as the study area to validate the proposed method. The results show that, considering the existing fire stations (85 facilities), the proposed model achieves a significant 38.56% in high-risk areas that can be covered by more than one fire station. If the existing fire stations are not considered when building 95 fire stations, the proposed model can achieve coverage of 50.07% in high-risk areas by utilizing more than one fire station. As a result, the proposed backup coverage model would perform better if the protection of high-risk areas is improved with as few fire stations as possible to guarantee more places covered. MDPI 2022-12-29 /pmc/articles/PMC9819386/ /pubmed/36612949 http://dx.doi.org/10.3390/ijerph20010627 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Tao, Liufeng
Cui, Yuqiong
Xu, Yongyang
Chen, Zhanlong
Guo, Han
Huang, Bo
Xie, Zhong
Location Optimization of Urban Fire Stations Considering the Backup Coverage
title Location Optimization of Urban Fire Stations Considering the Backup Coverage
title_full Location Optimization of Urban Fire Stations Considering the Backup Coverage
title_fullStr Location Optimization of Urban Fire Stations Considering the Backup Coverage
title_full_unstemmed Location Optimization of Urban Fire Stations Considering the Backup Coverage
title_short Location Optimization of Urban Fire Stations Considering the Backup Coverage
title_sort location optimization of urban fire stations considering the backup coverage
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9819386/
https://www.ncbi.nlm.nih.gov/pubmed/36612949
http://dx.doi.org/10.3390/ijerph20010627
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