Methodology and its application for community-scale evacuation planning against earthquake disaster

In urban area, popular and property is accumulated in a small area, potential risk of earthquake disaster in urban community is great. Pre-disaster emergency evacuation zoning has become a significant topic of disaster prevention and mitigation research. Based on the present layout of evacuation facilities and shelters as well as the evacuation demands in urban communities, a systematical methodology for occupant evacuation against earthquakes on community scale was developed by employing spatial analysis techniques of Geographical Information System (GIS). The methodology included the following aspects: the distribution analysis of emergency evacuation demands, the calculation of shelter space accessibility, and the optimization of evacuation destinations. This methodology was applied to Lujiazui Street in Pudong, a new district located in Shanghai, China. It was found that the proposed methodology could be used to formulate pre-event planning for earthquake disaster prevention and mitigation on a community scale, especially for organizing a rapid and smooth evacuation and optimizing the location allocation of shelters.     

A GIS-based analysis of constraints on pedestrian tsunami evacuation routes: Cascais case study (Portugal)

Tsunami hazard in coastal areas susceptible to flooding, although reduced (in terms of probability of occurrence), may pose a high risk. Therefore, in these areas, a detailed evacuation planning of the affected population is required as a risk mitigation measure. The knowledge and enforcement of evacuation routes may reduce the population vulnerability, making it more resilient and reducing risk. This paper presents a GIS approach for modelling evacuation routes based on the optimal path search problem, of the graph theory, which is implemented on ArcCasper tool. The methodology proposed considers the elements involved in the evacuation process, the worst credible tsunami inundation scenario (hazard extent and travel time), the number of people that needs to be evacuated in different time scenarios, the safe areas or destination points of the evacuation routes, the roads network characteristics and finally the time available to evacuate. The knowledge of those elements allows predicting some possible outcomes of the evacuation, such as the arrival time of the evacuees to a shelter and the identification of congestion hot spots resulting from the application of a flocking model which simulates the path to be used by evacuees avoiding obstacles. The municipality of Cascais was used to test the methodology proposed in this study. Cascais is one of the largest urban centres located about 25 km west of Lisbon, Portugal, with a high density of infrastructure along the coastline whereby most of the population and economic activities are exposed to a tsunami. The results, presented in the form of maps, allow identifying the optimal evacuation routes as well as the unfeasible routes. This crucial information could be used to the evacuation optimization regarding the location of meeting points and vertical shelters as well as to improve the accessibility of the areas to be evacuated.     

Location-allocation modeling for emergency evacuation planning with GIS and remote sensing: A case study of Northeast Bangladesh

This work developed models to identify optimal spatial distribution of emergency evacuation centers(EECs) such as schools, colleges, hospitals, and fire stations to improve flood emergency planning in the Sylhet region of northeastern Bangladesh.The use of location-allocation models(LAMs) for evacuation in regard to flood victims is essential to minimize disaster risk.In the first step, flood susceptibility maps were developed using machine learning models(MLMs), including: Levenberg–Marquardt back propagation(LM-BP) neural network and decision trees(DT) and multi-criteria decision making(MCDM) method.Performance of the MLMs and MCDM techniques were assessed considering the area under the receiver operating characteristic(AUROC) curve.Mathematical approaches in a geographic information system(GIS) for four well-known LAM problems affecting emergency rescue time are proposed: maximal covering location problem(MCLP), the maximize attendance(MA), p-median problem(PMP), and the location set covering problem(LSCP).The results showed that existing EECs were not optimally distributed, and that some areas were not adequately served by EECs(i.e., not all demand points could be reached within a 60-min travel time).We concluded that the proposed models can be used to improve planning of the distribution of EECs, and that application of the models could contribute to reducing human casualties, property losses, and improve emergency operation.     

The relationship between fire behaviour measures and community loss: an exploratory analysis for developing a bushfire severity scale

Current fire danger scales do not adequately reflect the potential destructive force of a bushfire in Australia and, therefore, do not provide fire prone communities with an adequate warning for the potential loss of human life and property. To determine options for developing a bushfire severity scale based on community impact and whether a link exists between the energy release rate (power) of a fire and community loss, this paper reviewed observations of 79 wildfires (from 1939 to 2009) across Victoria and other southern states of Australia. A methodology for estimating fire power based on fuel loading, fire size and progression rate is presented. McArthur??s existing fire danger indices (FDIs) as well as fuel- and slope-adjusted FDIs were calculated using fire weather data. Analysis of possible relationships between fire power, FDIs, rate of spread and Byram??s fireline intensity and community loss was performed using exposure as a covariate. Preliminary results showed that a stronger relationship exists between community loss and the power of the fire than between loss and FDI, although fuel-adjusted FDI was also a good predictor of loss. The database developed for this study and the relationships established are essential for undertaking future studies that require observations of past fire behaviour and losses and also to form the basis of developing a new severity scale.     

Spatial and temporal variations in the incidence of dust events over Iran

Large near-field tsunamis pose a significant threat to the Canadian West Coast due to its proximity to the circum-Pacific belt where a significant tsunami-inducing earthquake event from the Cascadia subduction zone is expected. This study investigated the risks associated with such an event in terms of pedestrian evacuation needs and plans for the Town of Tofino, a small community located on the West Coast of Vancouver Island. The population-at-risk within the hazard zone and its ability to evacuate to safety is evaluated using anisotropic path-distance modelling. Mitigation measures, such as vertical evacuation buildings, are quantitatively evaluated. Site-specific inundation modelling was not performed as part of this study; tsunami hazard and safe zones were computed using a range of run-ups varying between 3 and 25 m. It was established that up to 80% of the population is within the maximum hazard zone considered. This evacuation modelling exercise indicates that a maximum of 13% of the population would have insufficient time to reach safety when using a mobility-impaired ambulatory speed. The use of three vertical evacuation buildings can reduce the risk of losing population in this category by 99%. Although some conservative assumptions were used (vertical datum at higher high water, reductions in safe zones by generalization process and mobility-impaired evacuation speeds), the evacuation potential is likely overestimated due to the coarseness of the topographic data used in the evacuation modelling and from an overestimated first wave arrival time. This is the first Canadian study which used anisotropic evacuation modelling to evaluate the vulnerability of a Canadian community to tsunami inundation.

     

Computer-based Model for Flood Evacuation Emergency Planning

A computerized simulation model for capturing human behavior during flood emergency evacuation is developed using a system dynamics approach. It simulates the acceptance of evacuation orders by the residents of the area under threat; number of families in the process of evacuation; and time required for all evacuees to reach safety. The model is conceptualized around the flooding conditions (physical and management) and the main set of social and mental factors that determine human behavior before and during the flood evacuation. The number of families under the flood threat, population in the process of evacuation, inundation of refuge routes, flood conditions (precipitation, river elevation, etc.), and different flood warnings and evacuation orders related variables are among the large set of variables included in the model. They are linked to the concern that leads to the danger recognition, which triggers evacuation decisions that determine the number of people being evacuated. The main purpose of the model is to assess the effectiveness of different flood emergency management procedures. Each procedure consists of the choice of flood warning method, warning consistency, timing of evacuation order, coherence of the community, upstream flooding conditions, and set of weights assigned to different warning distribution methods. Model use and effectiveness are tested through the evaluation of the effectiveness of different flood evacuation emergency options in the Red River Basin, Canada.     

Virtual tools for volcanic crisis management, and evacuation decision support: applications to El Chichón volcano (Chiapas, México)

Decision making regarding massive evacuation of a population threatened by a probable volcanic eruption is a major problem in crisis management. Such a decision is general on the number of people to be evacuated, available resources and infrastructure, quantity and quality of the escape routes and shelters, and the economic, social and political costs involved in the operation, coupled with the updated information provided by scientists about the forecast of future activity and probable eruption scenarios. Knowing time-lapse between the evacuation decision-making time and the time in which the evacuation is completed is another critical issue that must be carefully considered in densely populated areas. In such areas, it is really important to estimate in advance this time-lapse, as the forecast must be released with enough time to complete all the evacuation process before the destructive manifestations of the eruption begin. In this context, evacuation planning is a crucial component of emergency management. It is common for Emergency Plans to include pre-established strategies. However, an evacuation procedure should be flexible, depending on the above-mentioned timing, and on the decisions, evacuation schemes, environmental characteristics and other factors. In this work, several hazard models such as a lava flow model based on a Monte Carlo algorithm, a pyroclastic density current based on energy cone model, a semi-empirical inversion model to estimate the thickness of ash deposits, and all available information about the El Chión volcano have been used to obtain the area that should be evacuated in case of an eruption. Then, multiple evacuation strategies at El Chichón volcano have been designed, considering not only the characteristics of the eruption forecast, but also environmental factors (e.g., weather conditions) and social factors (e.g., tourism and farming seasons). The variable scale evacuation model has been used to estimate the evacuation time. In the paper, those virtual tools are briefly described as well as the information obtained from the drill of 2009. In addition to the optimization of evacuation under variable conditions and situations, one of the main objectives of this work is to provide a reliable estimation of the mitigation action time, for an Emergency Plan.     

Wildfire evacuation experiences of band members of Whitefish Lake First Nation 459, Alberta,Canada

This paper presents results of a study which examined how a mandatory wildfire evacuation affected members of Whitefish Lake First Nation 459, in Alberta, Canada. A qualitative case study approach was used, and semi-structured interviews were completed with 45 band members to learn about their evacuation experiences during the wildfire evacuation in May 2011 and explore the factors that complicated the evacuation process and put further strain on the evacuees and First Nation. This evacuation caused considerable distress for evacuees and had negative effects for the First Nation. Factors that affected evacuation experiences included: (1) transportation issues compounded by cultural land-use activities, (2) fear of home loss compounded by existing housing shortages, (3) information and lack of media interest, (4) language, (5) poverty, (6) large multi-generational families, (7) health concerns, and (8) reimbursement of evacuation-related expenses to the community. An overarching factor that affected the entire evacuation was jurisdiction. Based on these findings, recommendations are provided for emergency managers on improving wildfire evacuation experiences for Indigenous peoples.

     

A DEM-based evaluation of potential flood risk to enhance decision support system for safe evacuation

A practical, DEM-based practical method is proposed to enhance flood risk management in fluvial areas by quantifying relative risk as a function of vulnerability to inland and evacuation difficulty. Both measures are based mainly on the topography of the region, so the method does not require detailed data on the physical characteristics of the land. First, we use the deterministic 8-node method on a digital elevation map (DEM) to trace storm waterways. Second, we repeat the process on a reversed DEM to trace evacuation routes that avoid the waterways and zones dangerously close to the rivers. Finally, on the basis of such two flow lines of evacuee and storm water, we proposed the protocol to evaluate the flood risk at every point on the map taking into account both the minimum time required for floodwater to arrive and duration of an evacuation from that location. The time that must be allocated for safe evacuation is defined as the potential flood risk of evacuation (PFRE). The method is demonstrated on a fluvial area of the Kaki River in Nagaoka city, Japan. In addition, we illustrated the application of the PFRE map to divide the region into areas of greater or lesser evacuation urgency.     

Supportive elements to the decision-making process in the emergency planning of the Angra dos Reis Nuclear Power Complex,Brazil

Accidents in nuclear power plants are problems of great complexity, mainly due to their consequences, such as the population evacuation from the enterprise influence area. The decision-making and emergency plans must be well articulated and require good local geographic space knowledge and the interactions of their environments. This study is a contribution to the emergency plans for the Almirante Álvaro Alberto Nuclear Power Plant, currently the only nuclear complex in Brazil, located in Angra dos Reis, Rio de Janeiro. The study confirmed the region’s main geoenvironmental aspects as winds and rainfall, landslides and population density were evaluated as important elements in the local emergency process. Their integrated analysis supported scenario identification and critical regional points and highlighted population evacuation escape routes. These important results characterized the support to local emergency management actions and guidelines. Furthermore, the geographic information systems was configured as an integrated spatial and temporal analysis platform to associate meteorological, geological/geomorphological and socio-economic data, playing a key role to support the evacuation planning in the event of nuclear power plant accidents.     

Prioritization of disaster risk in a community using GIS

Prioritization of disaster risk was carried out for a community in Toronto, Canada. Geographic information systems (GIS) were used for spatial analysis, including spatial overlays and clipping for extracting spatial and attribute information related to people’s vulnerability, critical infrastructure and landuse. In order to determine disaster risk, the overall community vulnerability was evaluated by combining social, economic, physical and environmental vulnerabilities. This paper uses the propane explosion incident as the case in point to demonstrate the methodology and procedure used to evaluate risk using GIS techniques. City of Toronto spatial data have been integrated with the study area to gather landuse information, identify risk zones based on the propane storage facility location and evaluate risks. Statistics Canada 2006 census data have been used for area demographics and people’s social and economic status. Vulnerability indicators were determined based on the GIS-derived spatial and attribute data for the hazard and evacuation zones followed by a quantitative spatial risk estimation and ranking. The methodology of this study, based on the risk evaluation and prioritization conducted, can be applied to future decision making in effective landuse planning and the development of risk management strategies.     

Potential impacts of long-term subsidence on the wetlands and evacuation routes in coastal Louisiana

A steady-state subsidence forecast model was developed as a proof of concept to estimate changes in surface elevations of the wetlands and evacuation routes across coastal Louisiana for the years 2015, 2025, 2050, and 2100. Subsidence estimates were derived from an empirical study published by the National Geodetic Survey. Forecasted vertical change was subtracted from current surface elevations. Land and evacuation routes estimated to have surfaces at or below 0 m in elevation, NAVD88, were quantified and classified as vulnerable to inundation hazards. The extent of the coastal zone susceptible to hurricane induced storm surge was also evaluated relative to surge models published by the National Weather Service. The results indicate spatially heterogeneous rates of subsidence that are forecasted to consume nearly 50 % of the existing coastal margin wetlands by 2100. The most significant rate increases are anticipated between 2015 and 2050. Relative to the impact on evacuation routes, subsidence occurring between the 2015 and 2025 forecast years expanded at slower rates when compared to the latter half of the century. Subsidence adjusted storm surge forecasts reveal similar patterns. The methods employed and findings produced demonstrate forecasting capabilities that provide emergency managers and transportation engineers with resources applicable to evacuation modeling, hazard mitigation, environmental sustainability research, costal restoration efforts, and more.     

A risk-based approach for crowd evacuation performance evaluation under metro fire

This paper aims to evaluate the crowd evacuation performance in a metro fire by using the limit state equation to describe the egress process. The limit state equation is established by the available time margin in fire evacuation, which comprises the evacuee's response time, behaviour time and movement time to an exit. Here, the available time margin in a fire evacuation is determined by the duration of time the smoke takes to exceed the evacuee's respiration level, the time that the smoke is detected by fire alarm and the time that the evacuee needs to respond and move to an exit during evacuation. Further, Monte Carlo simulation approach has been employed to integrate the fatality rates and the probabilities of occurrence of different scenarios in a typical metro in Xiaobailou station of station-Tianjin Line 1. Through this case study, it is shown that the evacuee's response time, behaviour time and movement time to exits can be integrated in a stochastic process model.     

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.     

Method to determine the locations of tsunami vertical evacuation shelters

The 2004 Indian Ocean tsunami and the 2011 Great Tohoku Japan earthquake and tsunami focused a great deal of the world??s attention on the effect of tsunamis on buildings and infrastructure. When a tsunami impacts structures in a coastal community, the structures are often not strong enough to withstand the forces and may collapse. Therefore, to maximize the survival probability, people evacuate to higher ground or move outside the inundation zone. However, this is not always possible because of short warning times for near-field tsunamis. Thus, sheltering-in-place or ??sheltering-near-place?? using vertical evacuation should be considered as an alternative approach to lateral evacuation from a tsunami inundation zone. This paper presents the method and results of a study to develop and demonstrate a methodology that applied genetic optimization to determine optimal tsunami shelter locations with the goal of reducing evacuation time, thereby maximizing the probability of survival for the population in a coastal community. The City of Cannon Beach, Oregon, USA, was used as an illustrative example. Several cases were investigated ranging from a single shelter to multiple shelters with locations of high elevation already in place near the city. The method can provide decision-support for the determination of locations for tsunami vertical evacuation shelters. The optimum location of the shelter(s), which was found to vary depending on the number of shelters considered, can reduce the evacuation time significantly, thereby reducing the number of fatalities and increasing the safety of a community.     

Exploring how alternative mapping approaches influence fireshed assessment and human community exposure to wildfire

Attaining fire-adapted human communities has become a key focus of collaborative planning on landscapes across the western United States and elsewhere. The coupling of fire simulation with GIS has expanded the analytical base to support such planning efforts, particularly through the “fireshed” concept that identifies areas where wildfires could ignite and reach a human community. Previous research has identified mismatches in scale between localized community wildfire planning and the broader fireshed considering patterns of wildfire activity across landscapes. Here we expand upon this work by investigating the degree to which alternative geospatial characterizations of human communities could influence assessment of community exposure and characterization of the fireshed. We use three methods of mapping human communities (point, raster, and polygon) and develop three fireshed metrics (size, number of fires reaching houses, and number of houses exposed), and apply this analytical framework on a 2.3 million ha case study landscape encompassing the Sierra National Forest in California, USA. We simulated fire occurrence and growth using FSim for 10,000 iterations (fire seasons) at 180-m resolution. The simulation resulted in 3.9 large fires per million ha per year, with a mean size of 3432 ha. Results exhibit similarities and differences in how exposure is quantified, specifically indicating that polygons representing recognized community boundaries led to the lowest exposure levels. These results highlight how choice of the mapping approach could lead to misestimating the scope of the problem or targeting mitigation efforts in the wrong areas, and underscore the importance of clarity and spatial fidelity in geospatial data representing communities at risk.     

Influence of road network and population demand assumptions in evacuation modeling for distant tsunamis

Tsunami evacuation planning in coastal communities is typically focused on local events where at-risk individuals must move on foot in a matter of minutes to safety. Less attention has been placed on distant tsunamis, where evacuations unfold over several hours, are often dominated by vehicle use and are managed by public safety officials. Traditional traffic simulation models focus on estimating clearance times but often overlook the influence of varying population demand, alternative modes, background traffic, shadow evacuation, and traffic management alternatives. These factors are especially important for island communities with limited egress options to safety. We use the coastal community of Balboa Island, California (USA), as a case study to explore the range of potential clearance times prior to wave arrival for a distant tsunami scenario. We use a first-in–first-out queuing simulation environment to estimate variations in clearance times, given varying assumptions of the evacuating population (demand) and the road network over which they evacuate (supply). Results suggest clearance times are less than wave arrival times for a distant tsunami, except when we assume maximum vehicle usage for residents, employees, and tourists for a weekend scenario. A two-lane bridge to the mainland was the primary traffic bottleneck, thereby minimizing the effect of departure times, shadow evacuations, background traffic, boat-based evacuations, and traffic light timing on overall community clearance time. Reducing vehicular demand generally reduced clearance time, whereas improvements to road capacity had mixed results. Finally, failure to recognize non-residential employee and tourist populations in the vehicle demand substantially underestimated clearance time.     

A hurricane evacuation management decision support system (EMDSS)

This article describes the challenges confronting local authorities who must decide if and when to initiate evacuations from tropical cyclones. This problem can be decomposed into the behavior of the hurricane that is relevant to evacuation and the behavior of evacuees that is relevant to the hurricane. The uncertain behavior of these two systems can be modeled in an evacuation management decision support system (EMDSS). The hurricane EMDSS described here displays information about the minimum, most, and maximum probable evacuation time estimates (ETEs) in comparison to the earliest, most, and latest probable estimated times of arrival (ETAs) for storm conditions. In addition, EMDSS calculates the cost of false positive (the economic cost of an evacuation) and false negative (lives lost in a late evacuation) decision errors. EMDSS is being used in experiments to assess different information displays, team compositions, community characteristics, and hurricane scenarios. In addition, it will be used in training and actual hurricane operations. Finally, definition of the program’s requirements has identified further research needed to build a better empirical base for its input data.     

Probabilistic assessment of wildfire hazard and municipal watershed exposure

The occurrence of wildfires within municipal watersheds can result in significant impacts to water quality and ultimately human health and safety. In this paper, we illustrate the application of geospatial analysis and burn probability modeling to assess the exposure of municipal watersheds to wildfire. Our assessment of wildfire exposure consists of two primary components: (1) wildfire hazard, which we characterize with burn probability, fireline intensity, and a composite index, and (2) geospatial intersection of watershed polygons with spatially resolved wildfire hazard metrics. This effort enhances investigation into spatial patterns of fire occurrence and behavior and enables quantitative comparisons of exposure across watersheds on the basis of a novel, integrated measure of wildfire hazard. As a case study, we consider the municipal watersheds located on the Beaverhead-Deerlodge National Forest (BDNF) in Montana, United States. We present simulation results to highlight exposure across watersheds and generally demonstrate vast differences in fire likelihood, fire behavior, and expected area burned among the analyzed municipal watersheds. We describe how this information can be incorporated into risk-based strategic fuels management planning and across the broader wildfire management spectrum. To conclude, we discuss strengths and limitations of our approach and offer potential future expansions.     

Collaborative geomatics and the Mushkegowuk Cree First Nations: Fostering adaptive capacity for community-based sub-arctic natural resource management

The remote First Nation (FN) communities of the Mushkegowuk Territory on the west coast of James Bay, Ontario, Canada are currently facing increased development pressures and the imposition of a government land use planning process. The land use planning process is mandated in the Far North Act (received Royal Assent on September 23, 2010). There is a need for capacity enhancement for community-based natural resource planning and management in the Territory. A number of frameworks are emerging for addressing change brought on by resource development and building resilience to such change at the community level. Among these include the concept of adaptive capacity. In collaboration with FN community leaders, we explored the use of “collaborative geomatics” tools to foster adaptive capacity. Our action research suggests that collaborative geomatics technologies should enhance the Mushkegowuk First Nations’ adaptive capacity to address environmental and policy change by allowing them to collect and manage data collaboratively (e.g., traditional environmental knowledge, western science) to create opportunities for innovative community development, including natural resource development and management.