Evacuation Vulnerability Research Articles

Neighborhood-Scale Wildfire Evacuation Vulnerability in Hays County, TX

Neighborhood-Scale Wildfire Evacuation Vulnerability in Hays County, TX

Quantitative assessment of flooding risk based on predicted evacuation time: A case study in Joso city, Japan

Flooding is a frequent natural hazard, threatening people's lives and properties worldwide. Even though completely preventing damage from flooding is impossible, an appropriate evacuation can help minimize its impact and mitigate human casualties. However, analyzing various flooding information to make quick evacuation judgments is challenging for decision-makers. Therefore, a quantitative flooding risk assessment is needed to support appropriate evacuation decisions. This study introduces the travel time under ideal evacuation conditions to quantify evacuation vulnerability, with Dijkstra's algorithm finding the evacuation route and the Random Forest algorithm predicting the evacuation time. The evacuation vulnerability is then integrated with time-varying flooding hazards and estimated congestion levels to assess evacuation risk. Herein, a case study in Joso, Japan is used as an example to demonstrate the practicality and applicability of the proposed approach. As a result, the prediction model achieved high accuracy with an RMSE of 0.88min and a MAPE of 5.88 %. The proposed approach clearly illustrated the vulnerable areas and times that may hinder an efficient evacuation process. Also, this approach identified and visualized the individual evacuation risk distribution during a given flooding scenario: 49.38 % of buildings were assessed as having the highest-risk: no evacuation ability, while a maximum of 11.86 % and 3.83 % of the buildings were assessed as middle-risk and high-risk. Furthermore, the regional evacuation deadline and priorities were specified to ensure timely and effective evacuation. Overall, this study develops an approach for assessing evacuation vulnerability and risk that could facilitate awareness among the public and provide judgmental bases for evacuation preparedness and decision-making.

A nuclear emergency partition evacuation framework based on comprehensive risk assessment

Nuclear power has incomparable advantages over traditional fossil energy and has become one of major power sources. Meanwhile, the huge losses in nuclear accidents place higher requirements for emergency response. Nuclear emergency evacuation is an effective protective measure to prevent or reduce the public’s exposure to radioactive materials. However, nuclear emergency evacuation is affected by a variety of factors, including environment, resources, transportation, and radiation, etc. It is difficult for decision makers to analyze a large amount of complex information so as to design effective nuclear emergency evacuation schemes. Considering the potential risk and characteristics of emergency traffic evacuation, a partition evacuation framework based on risk assessment is proposed in this paper. First, to deal with nuclear radiation and traffic evacuation vulnerability, a comprehensive risk assessment method is put forward that can be used for potential risk quantification during nuclear emergency evacuation. Second, according to the risk assessment results, this paper proposes a partition evacuation organization strategy and a cell transmission model (CTM) to minimize the exposure risk of during nuclear emergency evacuation. Finally, taking a coastal nuclear power plant in China as the research object, extensive and in-depth analysis is performed. As suggested by the simulation results, the partition evacuation strategy we proposed could effectively reduce the exposure risk by 36.0% and the average delay is shortened by 50.4%. Compared with traditional evacuation strategies, our framework is useful for increasing the nuclear emergency evacuation efficiency and alleviating traffic congestion.

Sensor placement optimization for fenceline monitoring of toxic gases considering spatiotemporal risk of the plant-urban interface

Toxic gas leak accidents can lead to significant casualties. The damage from a leak accident will be greater if toxic gas spreads to places where population density is high or vulnerable facilities with people who have difficulty evacuating. And the damage from leak accidents will also be greater if there is no evacuation warning from the plant despite the significant leak. Therefore, it is necessary to design the fenceline monitoring system through sensor placement optimization that reduces the risk toward the community. In this study, a mixed-integer linear programming formulation is proposed for sensor placement minimizing the risk by reflecting the characteristics of nearby areas. In order to quantitatively estimate the risk toward the community, the risk is calculated using dispersion data from computational fluid dynamics simulations and evacuation vulnerability and population density that define characteristics of a community. A case study is conducted to validate the efficiency of the proposed method. Exposed area and residual risk fraction are compared according to sensor placements from different conditions. Top-3 risk leak scenarios are analyzed quantitatively to manage the worst leak accident. It is validated that the proposed method is more efficient especially for the community that has uneven characteristics distribution.

Evaluating rural Pacific Northwest towns for wildfire evacuation vulnerability

Evaluating rural Pacific Northwest towns for wildfire evacuation vulnerability

An enhanced model for evacuation vulnerability assessment in urban areas

Rapid urbanization has led to a massive influx of people into cities. When many people congregate in urban areas, crowd crushing emergencies are likely to occur. If vulnerable areas with potential evacuation problems are detected in advance, crowd crushing emergencies may be minimized or even avoided. Thus, an evacuation vulnerability assessment from a precautionary perspective is fundamental. However, the current evacuation vulnerability assessment models are limited in spreading time estimation and evacuation capacity evaluation. To mitigate these limitations, in this study, we propose an enhanced model to quantitatively assess the evacuation vulnerability in urban areas. Our model enhances the current models in two ways. First, we employ a hexagon gridding scheme to construct a network to meet the prerequisite of evacuation spreading at the equal time intervals. Second, we quantify the grid connectivity on the network by considering the grid capacity to avoid underestimation of the evacuation vulnerability. Using a mobile phone location dataset of Shanghai, we systematically investigate the evacuation vulnerability of urban areas in a fine-grained spatio-temporal scale. Areas that may encounter evacuation problems to various degrees can be identified in advance. This information can support emergency management agencies in monitoring dense crowds and ensure early warnings of potential crowd crushing emergencies.

Mobile home resident evacuation vulnerability and emergency medical service access during tornado events in the Southeast United States

Tornado mortality is greatest in the Southeast United States (U.S.) due to an elevated tornado risk, a larger total developed land area, and a greater number of mobile and manufactured homes. The National Weather Service (NWS) and Federal Management Agency (FEMA) both recommend that mobile home residents evacuate to a nearby sturdier structure when tornado threats arise. However, previous research has indicated that less than 30% of mobile home residents evacuate their homes during tornado events despite their expressed willingness to flee. This study employs geospatial near and network analysis techniques from mobile and permanent homes to nearby potential sheltering locations to determine possible reasons for the less than ideal sheltering rates. Additionally, emergency medical service response times for mobile and permanent homes are also assessed using a network analysis methodology. Results indicate that the distances and travel times from mobile homes to shelters are significantly greater than that of permanent homes to shelters. The distances and travel times from first responder stations to mobile homes are also greater compared to those associated with permanent home residents. Findings from this research illustrate that in addition to mobile home residents being more physically and socioeconomically vulnerable to tornadoes, they are also disproportionally less served by potential sheltering locations and emergency services due to being located more commonly in rural areas, especially in southern Alabama. Outcomes from this study may also be utilized by emergency managers and policy makers to refine and implement new tornado preparedness and mitigation plans within southeastern U.S. communities.

Research on emergency evacuation vulnerability of the traffic network model based on GIS

Research on emergency evacuation vulnerability of the traffic network model based on GIS

A proposed semi-quantitative framework for comprehensive risk assessment of urban hazard installations considering rescue accessibility and evacuation vulnerability

With rapid economic growth, previously less populated peripheral areas of major cities in China have now become densely populated. Many hazardous installations (e.g., chemical plants, tank farms, depots of explosive materials, etc.) that used to be in these less populated areas are now found in the backyards of millions of citizens going about their daily lives with minimal knowledge about the dangers these installations pose. A hazard mishap that may have been containable with no human loss just 30 years ago can now threaten the lives of millions.While numerous studies have assessed hazard-specific risks, few efforts have attempted to establish a comprehensive framework to assess multi-hazard scenarios. For this purpose, this study developed a framework for spatial risk assessment of multiple hazardous installations in a metropolitan area. The framework includes three quantitative models for the analysis of the inherent danger associated with, the accessibility for rescue operations at, and the potential effectiveness of mass evacuation from these hazardous installations. Based on this framework and its quantitative models, a case study of the city of Beijing was conducted in this research.

Social Factors and Evacuation Vulnerability: An Application in Pinellas County, Florida

ABSTRACTEvacuation decisions by people at risk are dependent on a variety of social factors that can define the success and failure of such practices. Many previous studies have identified the role of these social factors in decision making on an individual basis, which has helped us understand evacuation. In reality, however, these factors act jointly to influence decisions. Thus, measuring the roles of individual factors and combining them can help detect areas most in need of evacuation assistance by the emergency managers. This research identified those areas of high evacuation assistance need for Pinellas County, Florida, based on indexes of accepted social vulnerability factors derived from census block data. From a final index that combined nine variables, four particularly vulnerable areas were identified. Census blocks in Largo were vulnerable primarily due to demographics, structural conditions, and limited accessibility to resources. The blocks in South St. Petersburg were vulnerable because of groups of concern. The blocks of Safety Harbor and Pinellas Park were vulnerable because of demographic and structural conditions, and limited accessibility to resources influenced the blocks in Pinellas Park. These results can be used by emergency managers in resource allocation, risk reduction, and providing special services. Further research should test the validity of the combined index in effecting efficient evacuation.

An urban form response to disaster vulnerability: Improving tsunami evacuation in Iquique, Chile

As urbanization gathers pace and climate change increases the number and magnitude of many natural hazards, cities are increasingly becoming hot spots for disasters. Although the role of appropriate urban forms in reducing disaster vulnerability has been recognized for some time, the majority of its potential remains focused on long-term mitigation efforts. In contrast, examination of the relationships with short-term disaster management activities such as response and immediate recovery has not been thoroughly conducted. This paper contributes to this shortfall by analysing a critical type of rapid onset disaster, a near-field tsunami, and the role of urban form in supporting the populations’ core response activities of evacuation and sheltering. The Chilean city of Iquique (affected by a severe earthquake and minor tsunami in 2014) is examined using a mixed methods approach that provides the basis for proposed macro-scale and micro-scale changes in its urban form; these modifications, in turn, are assessed with geographic information system (GIS) and agent-based computer models. The results show important existing evacuation vulnerability throughout major areas of the city (as the result of interrelated critical conditions), which nonetheless could be significantly reduced by the changes proposed. Further steps in this iterative process, in turn, could lead to the development of evacuation-based urban design standards capable of being transferred to different tsunami-prone contexts around the world.

A new assessment model for evacuation vulnerability in urban areas

ABSTRACTIn the high-speed urbanization process of China, the urban population has been increasing significantly, leading to a high-density aggregation of population. However, the sharp increase in population density has not produced commensurate improvements in the road networks. On the contrary, the population increase induced a serious evacuation vulnerability, which cities experience during various hazards and catastrophic events. Therefore, research on evacuation vulnerability is important to urban planning. To assess the evacuation vulnerability, the optimal and worst scenarios should be considered because all possible evacuation plans occur between these extremes. However, most previous evacuation vulnerability studies are based on the worst-case scenario, only providing an upper bound of a potential evacuation assessment. To provide a more comprehensive theoretical basis for decision-makers to understand the consequences caused by all possible evacuations, this paper proposes an optimal evacuation vulnerability assessment model that provides the lower bound on potential evacuation difficulties. The model is solved by a stepwise spreading algorithm based on Graph Theory. Subsequently, to evaluate the effectiveness of the model, the study adopts the model to assess the evacuation capability of different road network topologies. A comparison with previous research was performed. The model was demonstrated in an application to the South Luogu Alley of Beijing, China. The significance of this paper is that the combination of our model with previous research may provide a more complete theoretical basis for an evacuation vulnerability assessment.

Living in Mansions and Evacuation Vulnerability

Living in Mansions and Evacuation Vulnerability

Mapping wildfire evacuation vulnerability in the western US: the limits of infrastructure

Residential development in fire-prone areas of the western United States is a growing concern. The steady addition of homes to this region places more people and property at risk each year. In many areas housing is increasing without commensurate improvements in the road network, particularly in regards to the number, capacity and arrangement of community exit roads. This results in steadily increasing minimum evacuation times, as each additional household contributes to potential evacuation travel-demand in a wildfire. The goal of this research is to perform a comprehensive geographic search of the western U.S. for communities in wildfire-prone areas that may represent difficult evacuations due to constrained egress. The problem is formulated as a spatial search for fire-prone communities with a high ratio of households-to-exits and solved using methods in spatial optimization and geographic information systems (GIS). The results reveal an initial inventory and ranking of the most difficult wildfire evacuations in the West. These communities share a unique vulnerability in that all residents may not be able to evacuate in scenarios with short warning time. For this reason they represent prime candidates for emergency planning, and monitoring their development is a growing need.

Istanbul Grand Bazaar Evacuation System Vulnerability Assessment

The Grand Bazaar is a historical trade centre more than 500 years in the historical peninsula of Istanbul, Turkey. It consists of almost 3,600 small shops from different sectors (such as jewellery, carpet, leather, souvenir, finance, restaurant, café, confection etc.), two Bedesten, 64 street and 16 Han (inn) buildings. The Bazaar has 21 main gates that open to different streets and have different relation with outside. More than 25000 staff work in the shops and 300-500 thousand users come to Bazaar daily depending on the season and day. The pedestrian density is changeable, depending on the place of the inner street and the type of the sector. The historical disaster records (earthquake, dated 1766 and 1894, the grand bazaar fire, dated 1954) show that there was evacuation vulnerability. The main gates (exit doors) and exit route need some rehabilitation for safety evacuation during any disaster. The aim of this study is to evaluate the Grand Bazaar’s emergency evacuation vulnerability. The evacuation vulnerability factors question the width, length and natural illumination of the evacuation route, maintenance of the roof, presence of hazardous materials, door specifications as size, material, opening direction, maintenance and difference in elevation on the route and exit area such as staircase and thresholds.

Evaluating Evacuation Vulnerability Considering the Risk of Fire in Large Earthquake

Evaluating Evacuation Vulnerability Considering the Risk of Fire in Large Earthquake

Evaluating Evacuation Vulnerability Considering the Risk of Fire in Large Earthquake

Evaluating Evacuation Vulnerability Considering the Risk of Fire in Large Earthquake

Modelling community evacuation vulnerability using GIS

We present a method for systematically identifying neighbourhoods that may face transportation difficulties during an evacuation. A classification of this nature offers a unique approach to assessing community vulnerability in regions subject to fast-moving hazards of uncertain spatial impact (e.g., urban firestorms and toxic spills on highways). The approach is founded on an integer programming (IP) model called the critical cluster model (CCM). An heuristic algorithm is described which is capable of producing efficient, high-quality solutions to this model in a GIS context. The paper concludes with an application of the method to Santa Barbara, California.