Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Routing Diverse Evacuees with Cognitive Packets

This paper explores the idea of smart building evacuation when evacuees can belong to different categories with respect to their ability to move and their health conditions. This leads to new algorithms that use the Cognitive Packet Network concept to tailor different quality of service needs to different evacuees. These ideas are implemented in a simulated environment and evaluated with regard to their effectiveness.Comment: 7 pages, 7 figure

A Spatial Agent-based Model for Volcanic Evacuation of Mt. Merapi

Natural disasters, especially volcanic eruptions, are hazardous events that frequently happen in Indonesia. As a country within the “Ring of Fire”, Indonesia has hundreds of volcanoes and Mount Merapi is the most active. Historical studies of this volcano have revealed that there is potential for a major eruption in the future. Therefore, long-term disaster management is needed. To support the disaster management, physical and socially-based research has been carried out, but there is still a gap in the development of evacuation models. This modelling is necessary to evaluate the possibility of unexpected problems in the evacuation process since the hazard occurrences and the population behaviour are uncertain. The aim of this research was to develop an agent-based model (ABM) of volcanic evacuation to improve the effectiveness of evacuation management in Merapi. Besides the potential use of the results locally in Merapi, the development process of this evacuation model contributes by advancing the knowledge of ABM development for large-scale evacuation simulation in other contexts. Its novelty lies in (1) integrating a hazard model derived from historical records of the spatial impact of eruptions, (2) formulating and validating an individual evacuation decision model in ABM based on various interrelated factors revealed from literature reviews and surveys that enable the modelling of reluctant people, (3) formulating the integration of multi-criteria evaluation (MCE) in ABM to model a spatio-temporal dynamic model of risk (STDMR) that enables representation of the changing of risk as a consequence of changing hazard level, hazard extent and movement of people, and (4) formulating an evacuation staging method based on MCE using geographic and demographic criteria. The volcanic evacuation model represents the relationships between physical and human agents, consisting of the volcano, stakeholders, the population at risk and the environment. The experimentation of several evacuation scenarios in Merapi using the developed ABM of evacuation shows that simultaneous strategy is superior in reducing the risk, but the staged scenario is the most effective in minimising the potential of road traffic problems during evacuation events in Merapi. Staged evacuation can be a good option when there is enough time to evacuate. However, if the evacuation time is limited, the simultaneous strategy is better to be implemented. Appropriate traffic management should be prepared to avoid traffic problems when the second option is chosen

Evaluating Human Driving Behavior and Traffic Operation Conditions during Wildfire Evacuation Using Connected Vehicles Data

With climate change and the resulting rise in temperatures, wildfire risk is increasing all over the world, particularly in the western United States, and the communities in wildland-urban interface (WUI) areas are at the greatest risk of fire. Understanding the driving behavior of individuals during evacuating fire-affected WUI areas is important because the evacuees may encounter difficult driving conditions and traffic congestions due to proximity to flammable vegetation and limited exit routes. Existing studies lack empirical data on evacuee driving behavior and traffic operation conditions during a wildfire evacuation. This study used two distinct connected vehicles (CV) datasets that contain lane-level precision historical vehicle trajectory and driving events datasets to investigate the traffic delays and driving behavior of individuals during historical wildfire evacuation events. The results of the study showed that the CV-datasets are a valuable source to accurately evaluate human driving behavior and calculate traffic delays in wildfire-caused evacuations

Simulating The Evacuation Of Students Attending Classes At The York University's Keele Campus

Since 1901, Canada has recorded over a thousand disasters (CDD, 2015). Ontario, a province possessing the highest number of incidents and evacuations, has adapted and learned from these experiences. The Emergency Movement and Civil Protection Act (1990) for example, legally obliged government organizations to maintain an emergency management program. Despite the measures set out by the government there were still a dominant paradigm of disaster, leading many to believe nothing could be done, when one occurs, or that they would not be affected one. Morris (2009) proved otherwise when it came to school shootings (a technological disaster). Morris illustrated awareness and preparedness in school led to resilient students who were less affected by the disasters. An important observation, as school disasters in particular have the ability to cause jarring impacts to a community. This Major Paper presents a simulation model that evacuates students attending classes at the York University Keele Campus. The agent-based model was constructed with data acquired from York University's Office of Institutional Planning & Analysis, York University?s Planning & Architectural Design branch of the Campus Services and Business Operation, and scientific journals. The model reproduces the number of registered students during the winter semester of 2014, from Monday to Sunday. This cycle stops, when a signal is given, informing of an evacuation. From this instance, students, proceeded through a series of steps before arriving to one of four predetermined evacuation zones. These steps included: 1) pre-movement 2) descend the corresponding multi-floored building and 3) travel at an assigned speed to the evacuation zone. Forty evacuation scenarios, ten for each evacuation zones, were generated at varying times of day, throughout the week. The gathered times were further analyzed with three variables: the student population, the number of buildings holding classes, and the percentage of buildings within the vicinity of an evacuation zone. The student population demonstrated a logarithmic relationship with time, where evacuation time became more consistent as the population sized increased. When it came to the analysis of the number of buildings holding classes, the greater number of buildings, meant the buildings were more spread out and resulted in similar evacuation time for all four evacuation zones. The last case examined the percentage of buildings within the vicinity of an evacuation zone, half of the evacuation zones possessed a linear relationship, where the greater percentages meant a shorter arrival time

Modelling Individual Evacuation Decisions during Natural Disasters: A Case Study of Volcanic Crisis in Merapi, Indonesia

As the size of human populations increases, so does the severity of the impacts of natural disasters. This is partly because more people are now occupying areas which are susceptible to hazardous natural events, hence, evacuation is needed when such events occur. Evacuation can be the most important action to minimise the impact of any disaster, but in many cases there are always people who are reluctant to leave. This paper describes an agent-based model (ABM) of evacuation decisions, focusing on the emergence of reluctant people in times of crisis and using Merapi, Indonesia as a case study. The individual evacuation decision model is influenced by several factors formulated from a literature review and survey. We categorised the factors influencing evacuation decisions into two opposing forces, namely, the driving factors to leave (evacuate) versus those to stay, to formulate the model. The evacuation decision (to stay/leave) of an agent is based on an evaluation of the strength of these driving factors using threshold-based rules. This ABM was utilised with a synthetic population from census microdata, in which everyone is characterised by the decision rule. Three scenarios with varying parameters are examined to calibrate the model. Validations were conducted using a retrodictive approach by performing spatial and temporal comparisons between the outputs of simulation and the real data. We present the results of the simulations and discuss the outcomes to conclude with the most plausible scenario

Urban flood simulation and integrated flood risk management

Climate change induces the probability of occurring natural disasters; e.g. floods, Sea Level Rise, Green House Gases. Flood is considered one of the most dangerous phenomena that tremendously and dramatically threatening the human being and environment worldwide. Rapid urban growth, demographic explosion, and unplanned land uses have exacerbated the problem of urban flooding, particularly in the cities of China. In addition to that, the concept of flood risk management and adaptation measures and strategies are still missed in the cities’ development future plans. The main objective of this Ph.D. dissertation is to investigate the flood risk analysis and assessment based on flood simulation and adaptive strategies for flood event through two case studies of Changsha city in south-central China. In case study I, fluvial flooding was considered on mesoscale and an MCA-based approach was proposed to assess the integrated flood risk of Changsha central city. HEC-RAS 1-D model was used to simulation the inundation characteristics for hazard analysis based on four risk dimensions: economic, social, environmental, and infrastructural risk. For infrastructural dimension, apart for direct damage on road segments, network analysis method was combined with inundation information and macroscopic traffic simulation to evaluate the impact on traffic volume as well as a decrease of road service level. Closeness centrality weighted with a travel time of pre- and after- flood was compared in order to measure the impact on urban accessibility. Integrated risk values were calculated using various weighting criteria sets. Sobol' indices were used as a tool of spatially-explicit global Uncertainty Analysis and Sensitivity Analysis (UA/SA) for damage models. In case study II, an agent-based modeling approach was proposed to simulate the emergency pluvial flood event caused by a short-time rainstorm in local areas of cities aiming at developing an interactive flood emergency management system capable of interpreting the risk and reduction strategy of the pluvial flood. The simulation integrated an inundation model with microscopic traffic simulation. It also reveals that all agents can benefit significantly from both engineering measures and the only pedestrian obtain relatively more benefits from risk warning with high awareness. The method provided potentials in studies on the adaptive emergency management and risk reduction, help both decision-makers and stakeholders to acquire deeper and comprehensive understanding of the flood risk. This Ph.D. study has investigated holistic methods and models’ selection in flood risk assessment and management to overcome data deficiency and to achieve the integration of different data. The results of the first case study reveal that the integrated methods have proved to be able to improved flood risk analysis and assessment especially for indirect damage of infrastructural system with network features. The global UA/SA based on Sobol' method and visualization with maps enable to gain the spatial distribution of uncertainty for various factors, the validation of damage models, and deeper and more comprehensive understanding of flood risk. Then based on the integrated risk assessment, functions of spatial planning in flood risk management were discussed, potentially providing guidance and support for decision-making. The results of the second case study denote that agent-based modeling and simulation can be effectively utilized for flood emergency management. Two scenarios focusing on specific risk reduction interventions were designed and compared. Engineering measures by improving capability of the drainage system and the surface permeability of waterlogging areas are the most effective means for damage mitigation. High public risk awareness still has great potential benefits of the in the event of emergencies, which can greatly enhance the effectiveness of the official warning. The agent-based modeling and simulation provided an effective method for analyzing the effectiveness of different strategies for reducing flood risk at the local scale and for supporting urban flood emergency management. The case studies also indicate the significance and necessity of establishing a platform and database to realize full sharing and synergies of spatial information resources for flood risk management, which is a vital issue to manage the urban flood risk and take effective measures correspondingly with responding to emergency extreme flood event. Keywords: urban flood; flood risk assessment; network analysis; flood simulation; flood risk managemen

e-Sanctuary: open multi-physics framework for modelling wildfire urban evacuation

The number of evacuees worldwide during wildfire keep rising, year after year. Fire evacuations at the wildland-urban interfaces (WUI) pose a serious challenge to fire and emergency services and are a global issue affecting thousands of communities around the world. But to date, there is a lack of comprehensive tools able to inform, train or aid the evacuation response and the decision making in case of wildfire. The present work describes a novel framework for modelling wildfire urban evacuations. The framework is based on multi-physics simulations that can quantify the evacuation performance. The work argues that an integrated approached requires considering and integrating all three important components of WUI evacuation, namely: fire spread, pedestrian movement, and traffic movement. The report includes a systematic review of each model component, and the key features needed for the integration into a comprehensive toolkit