Assessing Emergency Shelter Demand Using POI Data and Evacuation Simulation

Chen, Wei; Yao, Fang; Zhai, Qixiao; Wang, Wei; Zhang, Yijie

doi:10.3390/ijgi9010041

Cited by 16 publications

(4 citation statements)

References 45 publications

(54 reference statements)

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“…Network analysts can determine the location of tsunami shelters and evacuation routes by optimizing evacuation time by following the road network and taking into account pedestrian speed, shelter location, and incident location [11]. Shelter demand location can be generally obtained through a superposition analysis of potential areas affected by disasters [12]. Incidents can also be identified using the Berryman approach and GIS in the case of a Tsunami.…”

Section: Introductionmentioning

confidence: 99%

Using GIS to Determine Tsunami Shelter Location in South Coast Pangandaran District, Pangandaran Regency, Indonesia

Nurwatik

Setiawan

2023

IOP Conf. Ser.: Earth Environ. Sci.

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The geographical condition of the Pangandaran Regency affects the coastal area, periodically suffering hydrological hazards. Based on the Regional Disaster Management Agency of Pangandaran, Pangandaran Regency experienced Tsunami with a run-up height of 8 to 15.7 meters in 2006. The Tsunami caused 664 people to die, many to be injured, and caused social environment disruption. Therefore, this research aims to support disaster mitigation by identifying additional shelter locations and generating evacuation routes sequentially. This research uses the network analyst method of Geographic Information System (GIS). The identification of evacuation shelters utilizes several parameters, e.g., tsunami hazard catchment area, land slope levels, land cover, and street network. In addition, the spatial analysis considers average travel time as the impedance to resemble the actual evacuation process. The result indicates that 11 evacuation shelters scattered over the study area were dominantly located in Pangandaran Village. Moreover, this research generates 24 evacuation routes from the incident location to each shelter. The closest shelters accessed 8 minutes from incidents 4 and 18 are shelters 3 and 9, respectively. On the contrary, the farthest shelter is shelter 9, with a maximum impedance of 22 minutes from incidents 14 and 15. Furthermore, the most appropriate shelters are shelters 2 and 8, considering the elevation height of 10 and 7 in the open space.

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Section: Introductionmentioning

confidence: 99%

Using GIS to Determine Tsunami Shelter Location in South Coast Pangandaran District, Pangandaran Regency, Indonesia

Nurwatik

Setiawan

2023

IOP Conf. Ser.: Earth Environ. Sci.

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“…The effective refuge area is a key indicator in research concerned with emergency shelter site selection planning, spatial layouts, and effectiveness analysis [16,17]. The effectiveness of emergency shelters refers to their ability to provide shelter for disaster victims during disasters [18].…”

Section: Introductionmentioning

confidence: 99%

Monitoring and Analyzing the Effectiveness of the Effective Refuge Area of Emergency Shelters by Using Remote Sensing: A Case Study of Beijing’s Fifth Ring Road

You

Wang

et al. 2023

Remote Sensing

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The effective refuge area is a key indicator in the study of emergency shelters. Accurately extracting the effective refuge area and analyzing the effectiveness of emergency shelters are of great significance for site selection, spatial distribution, and the evaluation of suitability. Beijing is one of only three capitals in the world located in a high-seismic-intensity zone of magnitude 8. The fast and accurate monitoring of effective refuge areas and an analysis of the effectiveness of emergency shelters are conducive to evacuation planning and disaster prevention and mitigation, and they promote the construction of a resilient city. However, the extraction of effective refuge areas in existing studies is not only a time-consuming and labor-intensive task but also has accuracy and efficiency problems, resulting in less precise validity analyses. In this paper, a remote sensing monitoring technology system for the effective refuge areas of emergency shelters is proposed based on multi-source data. Different methods were used to extract various land features, such as buildings and collapsed areas, water, dense areas of understory vegetation, and steep slope areas that cannot be evacuated, to obtain the effective refuge area at a detailed scale, in combination with the service radius of emergency shelters, the population distribution, and the actual road network, the criteria for effectiveness analysis were established for the effective open space ratio, capacity, per capita accessible effective refuge area, and population allocation gap. Taking the area within the Fifth Ring Road of Beijing as an example, the effectiveness of emergency shelters was analyzed at both the whole scale and a local scale. The results show that the effective refuge areas of different emergency shelters in Beijing vary significantly, with the smallest effective refuge area being located in Rings 2–3 and the largest one being located in Rings 4–5; between different regions, there are differences in the effectiveness. This study provides a feasible method for the fast, accurate, and detailed extraction of the effective refuge areas of emergency shelters and also provides a reference for emergency planning for disaster prevention and mitigation.

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“…Chen et al, in their research on assessing emergency shelter demand using POI data and evacuation simulation, state that in the field of disaster relief, determining the exact spatial distribution of the population is a challenge [5].…”

Section: Introductionmentioning

confidence: 99%

Cybernetics Approach Using Agent-Based Modeling in the Process of Evacuating Educational Institutions in Case of Disasters

2021

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In the context of an emergency, evacuating people from a location in the shortest possible time is essential, as is the high degree of safety that people should expect when evacuating. Lately, in Romania there have been more and more fire events generated by different causes. This article will use agent-based modeling to simulate an emergency evacuation model in NetLogo. The model has been used to perform and analyze various scenarios. With the help of NetLogo, we managed to perform 400 simulations with the evacuation of 180 people (students, teachers, and non-teaching staff) based on which we developed several recommendations to streamline the evacuation process in order to reduce the possibility of death. The present research will help to identify the evacuation times from a school, but it will also highlight certain aspects that may occur during the evacuation. The model that was used in this research took into account the individual particularities of the people taking part in the evacuation, emphasizing the effects that form in a crowd of people when evacuating; effects such as the funnel effect, which is caused by the formation of bottlenecks around narrow areas. All these things are part of the analysis of the measurement of entropy of the exhaust system, a problem that has captured all of the specialists’ attention. Finally, solutions have been proposed to improve evacuation time in case of disasters.

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Assessing Emergency Shelter Demand Using POI Data and Evacuation Simulation

Cited by 16 publications

References 45 publications

Using GIS to Determine Tsunami Shelter Location in South Coast Pangandaran District, Pangandaran Regency, Indonesia

Using GIS to Determine Tsunami Shelter Location in South Coast Pangandaran District, Pangandaran Regency, Indonesia

Monitoring and Analyzing the Effectiveness of the Effective Refuge Area of Emergency Shelters by Using Remote Sensing: A Case Study of Beijing’s Fifth Ring Road

Cybernetics Approach Using Agent-Based Modeling in the Process of Evacuating Educational Institutions in Case of Disasters

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