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

被引:14
作者
Jiang, Yuncheng [1 ]
Lv, Aifeng [2 ,3 ]
Yan, Zhigang [1 ]
Yang, Zhen [4 ]
机构
[1] China Univ Min & Technol, Sch Environm Sci & Spatial Informat, Xuzhou 221116, Jiangsu, Peoples R China
[2] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res IGSNRR, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
[3] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[4] Liaoning Tech Univ, Sch Geomat, Fuxin 123000, Peoples R China
基金
中国国家自然科学基金;
关键词
spatial optimization; point of interest; potential fire-risk zone; multi-criterion decision-making; traffic situation; ANALYTIC HIERARCHY PROCESS; SITE SELECTION; OF-INTEREST; LOCATION; MODEL; URBAN; STATIONS; DESIGN; AHP;
D O I
10.3390/ijgi10110777
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:26
相关论文
共 61 条
[1]   Optimal Site Selection for a Solar Power Plant in the Central Anatolian Region of Turkey [J].
Akkas, Ozge Pinar ;
Erten, Mustafa Yasin ;
Cam, Ertugrul ;
Inanc, Nihat .
INTERNATIONAL JOURNAL OF PHOTOENERGY, 2017, 2017
[2]   Solar power potential of Tanzania: Identifying CSP and PV hot spots through a GIS multicriteria decision making analysis [J].
Aly, Ahmed ;
Jensen, Steen Solvang ;
Pedersen, Anders Branth .
RENEWABLE ENERGY, 2017, 113 :159-175
[3]   A multi-objective model for locating fire stations [J].
Badri, MA ;
Mortagy, AK ;
Alsayed, A .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1998, 110 (02) :243-260
[4]  
Barr R.C., 1996, FIRE PROTECTION HDB, P311
[5]   Exploratory and inferential methods for spatio-temporal analysis of residential fire clustering in urban areas [J].
Ceyhan, Elvan ;
Ertugay, Kivanc ;
Duzgun, Sebnem .
FIRE SAFETY JOURNAL, 2013, 58 :226-239
[6]  
Chainey S.P., 2013, Bulletin of the Geographical Society of Liege, V60, P7
[7]   Design of a material handling equipment selection model using analytic hierarchy process [J].
Chakraborty, S ;
Banik, D .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2006, 28 (11-12) :1237-1245
[8]   Application of an Analytic Hierarchy Process (AHP) in the GIS interface for suitable fire site selection: A case study from Kathmandu Metropolitan City, Nepal [J].
Chaudhary, Pandav ;
Chhetri, Sachin Kumar ;
Joshi, Kiran Man ;
Shrestha, Basanta Man ;
Kayastha, Prabin .
SOCIO-ECONOMIC PLANNING SCIENCES, 2016, 53 :60-71
[9]  
Chen Chi, 2003, Journal of Tsinghua University (Science and Technology), V43, P1390
[10]  
Chevalier P., 2012, Socioecon Plann Sci, V46, P173, DOI DOI 10.1016/J.SEPS.2012.02.003