A GIS-Based Multi-Criterion Decision-Making Method to Select City Fire Brigade: A Case Study of Wuhan, China

Rapid urban expansion has brought new challenges to firefighting, with the speed of firefighting rescue being crucial for the safety of property and life. Thus, fire prevention and rescuing people in distress have become more challenging for city managers and emergency responders. Unfortunately, exi...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Yuncheng Jiang, Aifeng Lv, Zhigang Yan, Zhen Yang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	spatial optimization point of interest potential fire-risk zone multi-criterion decision-making traffic situation Geography (General) G1-922
Acceso en línea:	https://doaj.org/article/7a0006c82df741078efdcdbf847d4a35
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:7a0006c82df741078efdcdbf847d4a35
record_format	dspace
spelling	oai:doaj.org-article:7a0006c82df741078efdcdbf847d4a352021-11-25T17:53:11ZA GIS-Based Multi-Criterion Decision-Making Method to Select City Fire Brigade: A Case Study of Wuhan, China10.3390/ijgi101107772220-9964https://doaj.org/article/7a0006c82df741078efdcdbf847d4a352021-11-01T00:00:00Zhttps://www.mdpi.com/2220-9964/10/11/777https://doaj.org/toc/2220-9964Rapid urban expansion has brought new challenges to firefighting, with the speed of firefighting rescue being crucial for the safety of property and life. Thus, fire prevention and rescuing people in distress have become more challenging for city managers and emergency responders. Unfortunately, existing research does not consider the negative effects of the current spatial distribution of fire-risk areas, land cover, location, and traffic congestion. To address these shortcomings, we use multiple methods (including geographic information system, multi-criterion decision-making, and location–allocation (L-A)) and multi-source geospatial data (including land cover, point-of-interest, drive time, and statistical yearbooks) to identify suitable areas for fire brigades. We propose a method for identifying potential fire-risk areas and to select suitable fire brigade zones. In this method, we first remove exclusion criteria to identify spatially undeveloped zones and use kernel density methods to evaluate the various fire-risk zones. Next, we use analytic hierarchy processes (AHPs) to comprehensively evaluate the undeveloped areas according to the location, orography, and potential fire-risk zones. In addition, based on the multi-time traffic situation, the average traffic speed during rush hour of each road is calculated, a traffic network model is established, and the travel time is calculated. Finally, the L-A model and network analysis are used to map the spatial coverage of the fire brigades, which is optimized by combining various objectives, such as the coverage rate of high-fire-risk zones, the coverage rate of building construction, and the maintenance of a sub-five-minute drive time between the proposed fire brigade and the demand point. The result shows that the top 50% of fire-risk zones in the central part of Wuhan are mainly concentrated to the west of the Yangtze River. Good overall rescue coverage is obtained with existing fire brigades, but the fire brigades in the north, south, southwest, and eastern areas of the study area lack rescue capabilities. The optimized results show that, to cover the high-fire-risk zones and building constructions, nine fire brigades should be added to increase the service coverage rate from 93.28% to 99.01%. The proposed method combines the viewpoint of big data, which provides new ideas and technical methods for the fire brigade site-selection model.Yuncheng JiangAifeng LvZhigang YanZhen YangMDPI AGarticlespatial optimizationpoint of interestpotential fire-risk zonemulti-criterion decision-makingtraffic situationGeography (General)G1-922ENISPRS International Journal of Geo-Information, Vol 10, Iss 777, p 777 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	spatial optimization point of interest potential fire-risk zone multi-criterion decision-making traffic situation Geography (General) G1-922
spellingShingle	spatial optimization point of interest potential fire-risk zone multi-criterion decision-making traffic situation Geography (General) G1-922 Yuncheng Jiang Aifeng Lv Zhigang Yan Zhen Yang A GIS-Based Multi-Criterion Decision-Making Method to Select City Fire Brigade: A Case Study of Wuhan, China
description	Rapid urban expansion has brought new challenges to firefighting, with the speed of firefighting rescue being crucial for the safety of property and life. Thus, fire prevention and rescuing people in distress have become more challenging for city managers and emergency responders. Unfortunately, existing research does not consider the negative effects of the current spatial distribution of fire-risk areas, land cover, location, and traffic congestion. To address these shortcomings, we use multiple methods (including geographic information system, multi-criterion decision-making, and location–allocation (L-A)) and multi-source geospatial data (including land cover, point-of-interest, drive time, and statistical yearbooks) to identify suitable areas for fire brigades. We propose a method for identifying potential fire-risk areas and to select suitable fire brigade zones. In this method, we first remove exclusion criteria to identify spatially undeveloped zones and use kernel density methods to evaluate the various fire-risk zones. Next, we use analytic hierarchy processes (AHPs) to comprehensively evaluate the undeveloped areas according to the location, orography, and potential fire-risk zones. In addition, based on the multi-time traffic situation, the average traffic speed during rush hour of each road is calculated, a traffic network model is established, and the travel time is calculated. Finally, the L-A model and network analysis are used to map the spatial coverage of the fire brigades, which is optimized by combining various objectives, such as the coverage rate of high-fire-risk zones, the coverage rate of building construction, and the maintenance of a sub-five-minute drive time between the proposed fire brigade and the demand point. The result shows that the top 50% of fire-risk zones in the central part of Wuhan are mainly concentrated to the west of the Yangtze River. Good overall rescue coverage is obtained with existing fire brigades, but the fire brigades in the north, south, southwest, and eastern areas of the study area lack rescue capabilities. The optimized results show that, to cover the high-fire-risk zones and building constructions, nine fire brigades should be added to increase the service coverage rate from 93.28% to 99.01%. The proposed method combines the viewpoint of big data, which provides new ideas and technical methods for the fire brigade site-selection model.
format	article
author	Yuncheng Jiang Aifeng Lv Zhigang Yan Zhen Yang
author_facet	Yuncheng Jiang Aifeng Lv Zhigang Yan Zhen Yang
author_sort	Yuncheng Jiang
title	A GIS-Based Multi-Criterion Decision-Making Method to Select City Fire Brigade: A Case Study of Wuhan, China
title_short	A GIS-Based Multi-Criterion Decision-Making Method to Select City Fire Brigade: A Case Study of Wuhan, China
title_full	A GIS-Based Multi-Criterion Decision-Making Method to Select City Fire Brigade: A Case Study of Wuhan, China
title_fullStr	A GIS-Based Multi-Criterion Decision-Making Method to Select City Fire Brigade: A Case Study of Wuhan, China
title_full_unstemmed	A GIS-Based Multi-Criterion Decision-Making Method to Select City Fire Brigade: A Case Study of Wuhan, China
title_sort	gis-based multi-criterion decision-making method to select city fire brigade: a case study of wuhan, china
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/7a0006c82df741078efdcdbf847d4a35
work_keys_str_mv	AT yunchengjiang agisbasedmulticriteriondecisionmakingmethodtoselectcityfirebrigadeacasestudyofwuhanchina AT aifenglv agisbasedmulticriteriondecisionmakingmethodtoselectcityfirebrigadeacasestudyofwuhanchina AT zhigangyan agisbasedmulticriteriondecisionmakingmethodtoselectcityfirebrigadeacasestudyofwuhanchina AT zhenyang agisbasedmulticriteriondecisionmakingmethodtoselectcityfirebrigadeacasestudyofwuhanchina AT yunchengjiang gisbasedmulticriteriondecisionmakingmethodtoselectcityfirebrigadeacasestudyofwuhanchina AT aifenglv gisbasedmulticriteriondecisionmakingmethodtoselectcityfirebrigadeacasestudyofwuhanchina AT zhigangyan gisbasedmulticriteriondecisionmakingmethodtoselectcityfirebrigadeacasestudyofwuhanchina AT zhenyang gisbasedmulticriteriondecisionmakingmethodtoselectcityfirebrigadeacasestudyofwuhanchina
_version_	1718411869920690176

A GIS-Based Multi-Criterion Decision-Making Method to Select City Fire Brigade: A Case Study of Wuhan, China

Ejemplares similares