Planning Emergency Shelters for Urban Disaster Resilience: An Integrated Location-Allocation Modeling Approach

After an earthquake, it is required to establish temporary relief centers in order to help the victims. Selection of proper sites for these centers has a significant effect on the processes of urban disaster management. In this paper, the location and allocation of relief centers in district 1 of Tehran are carried out using Geospatial Information System (GIS), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) decision model, a simple clustering method and the two meta-heuristic algorithms of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). First, using TOPSIS, the proposed clustering method and GIS analysis tools, sites satisfying initial conditions with adequate distribution in the area are chosen. Then, the selection of proper centers and the allocation of parcels to them are modelled as a location/allocation problem, which is solved using the meta-heuristic optimization algorithms. Also, in this research, PSO and ACO are compared using different criteria. The implementation results show the general adequacy of TOPSIS, the clustering method, and the optimization algorithms. This is an appropriate approach to solve such complex site selection and allocation problems. In view of the assessment results, the PSO finds better answers, converges faster, and shows higher consistency than the ACO.

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A Novel Evaluation Approach of County-Level City Disaster Resilience and Urban Environmental Cleanliness Based on SDG11 and Deqing County’s Situation

Sustainability ◽

10.3390/su11205713 ◽

2019 ◽

Vol 11 (20) ◽

pp. 5713 ◽

Cited By ~ 2

Author(s):

Yani Wang ◽

Mingyi Du ◽

Lei Zhou ◽

Guoyin Cai ◽

Yongliang Bai

Keyword(s):

Large Scale ◽

Time Series Prediction ◽

National Level ◽

Disaster Resilience ◽

County Level ◽

Local Data ◽

Human Settlements ◽

Evaluation Approach ◽

Urban Disaster ◽

Per Capita

City disaster resilience and urban environmental cleanliness are two representative indicators used to assess the safety of human settlements in China’s Sustainability Development Goals (SDGs). Traditional research on SDGs mainly concentrated at large-scale spatial level, such as global level or national level. It brings unclear significance to the implementation of SDGs in the county-level. The goal of this paper is to find a new calculation method to apply the index of urban disaster resilience and urban environmental cleanliness to the evaluation of county-level areas. A localization of county-level city disaster resilience and urban environmental cleanliness based on Deqing County’s situation was carried out. With quantification and projections of local data, the assessments of city disaster resilience and urban environmental cleanliness have completed. The evaluation showed that city disaster resilience is maintained at a low level, while indicators of urban cleanliness are lower than standards. The prediction of urban per capita environmental impact index based on Grey Time-Series Prediction Model was finished. The forecast showed that the urban per capita impact indicators in the next three years have not exceeded the standard line. The two indicators used to assess the safety of human settlements were consistent with the sustainable development of urban settlement. Partial results of this research were reported as a “county sample” at the first UN Geographic Information Conference held in Deqing in 2018.

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Decoding network patterns for urban disaster prevention by comparing Neihu district of Taipei and Sumida district of Tokyo

MATEC Web of Conferences ◽

10.1051/matecconf/201816901044 ◽

2018 ◽

Vol 169 ◽

pp. 01044 ◽

Cited By ~ 1

Author(s):

Hung-Wen Chang ◽

Wei-I Lee

Keyword(s):

Risk Reduction ◽

Case Studies ◽

Disaster Preparedness ◽

Disaster Risk Reduction ◽

Disaster Risk ◽

The Road ◽

Sendai Framework ◽

Emergency Shelters ◽

Urban Disaster ◽

Network Patterns

In this study, we performed routes network transport and emergency shelters capacity rate analyses to determine the accessibility and efficacy of urban patterns, and established a quantitative method for supplying priorities for actions of "Sendai Framework for Disaster Risk Reduction 2015-2030". By comparing two case studies, we used Space Syntax to develop two important indicators, Rn and CR, to present geographic information and hazard risk in a physical environment. This research also found potential function of Rn and decoded some patterns for urban planners or decision makers as follows：The most efficient configuration of the road network was not in the old areas of these two case studies because the several turns decreased the connectivity of the networks. And the CR indicator shown other findings about the quality of public facilities and services as follows：The service capacity of the emergency shelters was surveyed to indicate a higher correlation of residents population and preparedness security for disaster management. Therefore, with finding some risks that had not been encountered before, we addressed this proposed method is feasible and reliable to enhance the disaster preparedness for action regarding the 4th priority of “Sendai Framework for Disaster Risk Reduction 2015-2030”.

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The location of public logistic centers: an expanded capacity-limited fixed cost location-allocation modeling approach

Transportation Planning and Technology ◽

10.1080/03081060.2013.770945 ◽

2013 ◽

Vol 36 (2) ◽

pp. 218-229 ◽

Cited By ~ 2

Author(s):

Milosav Georgijevic ◽

Sanja Bojic ◽

Dejan Brcanov

Keyword(s):

Fixed Cost ◽

Location Allocation ◽

Modeling Approach

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A Scientometric Review of Urban Disaster Resilience Research

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18073677 ◽

2021 ◽

Vol 18 (7) ◽

pp. 3677

Author(s):

Hui Xu ◽

Yang Li ◽

Yongtao Tan ◽

Ninghui Deng

Keyword(s):

Sustainable Development ◽

Urban Areas ◽

Management Strategies ◽

High Growth ◽

Urban System ◽

Disaster Risk ◽

High Growth Rate ◽

Disaster Resilience ◽

Research Directions ◽

Urban Disaster

Natural disasters and human-made disasters are threatening urban areas globally. The resilience capacity of the urban system plays an important role in disaster risk response and recovery. Strengthening urban disaster resilience is also fundamental to ensuring sustainable development. Various practices and research for enhancing urban disaster resilience have been carried out worldwide but are yet to be reviewed. Accordingly, this paper gives a scientometric review of urban disaster resilience research by using CiteSpace. The time span (January 2001–January 2021) was selected and divided into three phases based on the number of publications. In addition, according to keyword statistics and clustering results, the collected articles are grouped into four hotspot topics: disaster risk reduction, specific disaster resilience research, resilience assessment, and combination research. The results show that most of the existing research is in the first two categories, and articles in the second and fourth categories both show a high growth rate and could be further research directions. The review indicates that urban disaster resilience is essential for a city’s sustainable development. Moreover, the findings provide scholars a full picture of the existing urban disaster resilience research which can help them identify promising research directions. The findings can also help urban government officials and policymakers review current urban disaster management strategies and make further improvements.

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