Abstract: Source term estimation (STE) of hazardous material (HAZMAT) releases is critical for emergency response. Such problem is usually solved with the aid of atmospheric dispersion modelling and inversion algorithms accompanied with a variety of uncertainty, including uncertainty in atmospheric dispersion models, uncertainty in meteorological data, uncertainty in measurement process and uncertainty in inversion algorithms. Bayesian inference methods provide a unified framework for solving STE problem and quantifying the uncertainty at the same time. In this paper, three stochastic methods for STE, namely Markov chain Monte Carlo (MCMC), sequential Monte Carlo (SMC) and ensemble Kalman filter (EnKF), are compared in accuracy, time consumption as well as the quantification of uncertainty, based on which a kind of flip ambiguity phenomenon caused by various uncertainty in STE problems is pointed out. The advantage of non-Gaussian estimation methods like SMC is emphasized.

Abstract: Understanding critical infrastructures and in particular protecting them in case of natural or man-made threats or disasters is the objective of our research. As use case, the security of the power supply in the year 2030 for the city of Karlsruhe was selected. This scenario contains interdependencies between the electrical power grid and IT components as well as critical infrastructures such as water supply and health care. To simulate the critical infrastructure, their dependencies and potential measures to mitigate effects, agent based simulation models have been developed and applied. The ultimate objective of the research activity is to develop a holistic analysis framework to quantify and evaluate requirements and design decisions of the many players in such complex infrastructures.

Abstract: The preparation of high quality emergency plans to guide operational decisions is an approach to mitigate the emergency management complexity. In such multidisciplinary scenario, teams with different perspectives need to collaborate towards a common goal and interact within a common understanding. In this scenario, the characterization of the variability of the elements involved in these plans is an important issue, which is addressed by the emergency plans generation methodology Document Product Line for Emergency Plans (DPL(EP)). To increase common understanding of plans, we propose an adaptation of this methodology by applying a well-founded emergency ontology, termed OntoEmergePlan, which supports the domain engineering phase. It is grounded in a foundational ontology, which ensures a higher consistency degree to the process of plans generation.

Abstract: This paper discusses the practical aspects and resulting insights of the results of a two-stage mathematical network flow model to help make the decisions required to get humanitarian aid quickly to needy recipients as part of a disaster relief operation. The aim of model is to plan where to best place aid inventory in preparation for possible disasters, and to make fast decisions about how best to channel aid to recipients as fast as possible. Humanitarian supply chains differ from commercial supply chains in their greater urgency of response and in the poor quality of data and increased uncertainty about important inputs such as transportation resources, aid availability, and the suddenness and degree of “demand”. The context is usually more chaotic with poor information feedback and a multiplicity of decision-makers in different aid organizations. The model attempts to handle this complexity by incorporating practical decisions, such as pre-allocation of emergency goods, transportation policy, fleet management and procurement, in an uncertainty environment featured by a scenario-based approach. Preliminary results based on the floods and landslides disaster of the Mountain Region of Rio de Janeiro state, Brazil, point to how to cope with these challenges by using the mathematical model.

Abstract: The increasing number of victims from disasters in recent years results in several challenges for authorities aiming to protect and provide support to affected people. Humanitarian logistics represents one of the most important fields during preparedness and response in cases of disaster, seeking to provide relief, information and services to disaster victims. However, on top of the challenges of logistical activities, the successful completion of operations depends to a large extent on coordination. This is particularly important for developing countries, where disasters occur very often and resources are even scarcer.
This paper assumes a multi-agency approach to disaster preparedness that combines geographical information systems (GIS) and multi-objective optimization. The purpose of the tool is to determine the location of emergency facilities, stock prepositioning and distribution allocation for floods. We illustrate the application and the results using a case study centred on Acapulco, México.

Abstract: This paper reviews current work on a model of the cascading effects of Critical Infrastructure (CI) failures during disasters. Based upon the contributions of 26 professionals, we have created a reliable model for the interaction among sixteen CIs. An internal CI model can be used as a core part of a number of larger models, each of which are tailored to a specific disaster in a specific location.

Abstract: Forest fire risk assessment is an important task for forest fire management and planning. This paper presents current work on the definition and implementation of forest fire risk assessment models in the Wildfire AnalystTM software with the purpose of providing support and increased value in risk assessment. Three models are presented based on the concept of forest fire risk: forest fire structural hazard model that provides the assessment of the expected easiness that a fire has to spread in a certain area, a stochastic model that assesses the fire growth potential considering as potential ignition points critical elements of electric supply networks and a stochastic model that assesses the potential impact of forest fires on these infrastructures.

Abstract: In this paper, we use the fast marching method to solve the emergency evacuation in high-rise building fire. This method is a numerical method which is used to solve the Eikonal equation in rectangular grids. As we know, building fires are very common in the world. They have caused a great deal of personnel casualty and property losses. How to reduce the casualty and ensure the life safety of trapped persons and rescuers have become the most important problem of the fire department. We carry out fire experiment and FDS simulation to research the structure fire firstly. Second, we divide the construction into 0.4m*0.4m grid. This size is a person who occupied when he is standing. After that, we use interpolation method to analyze the experiment and FDS simulation data so that we can get the risk value of each grid. At last, we calculate the global potential energy field of the scene based on the fast marching method and obtain a safest path for the trapped persons. The safest path represents the fastest-risk-decline path. In the cause of fire rescue we can provide the safest path to the trapped persons through evacuation signals of the building in order to guide them to evacuate and self-rescue.

Abstract: This paper explores the added-value of using interactive head-mounted displays to support command and control of first responders during emergency response. Specifically, it describes and evaluates a prototype system that makes use of Google Glass to enable in-field receiving of information from a command center, as well as in-field navigation and video streaming. The viability and usefulness of the concept was evaluated through a set of end-user workshops and interviews. A small-scale experiment was also conducted to assess the efficiency of using head-mounted displays for in-field navigation, as compared to handheld devices. Findings from workshops and interviews suggest that head-mounted displays could be a valuable supplement to radio communication, with potential for reducing information misinterpretation, and for enhancing information quality. Results from the experiment indicate that head-mounted displays have the same level of efficiency as handheld devices when used for basic navigation tasks.

Abstract: This paper presents findings from an interdisciplinary research effort studying community resilience in Boulder, Colorado. Boulder is a progressive region with a history of environmental leadership. The area is currently in the process of recovering from major flooding and has launched several new initiatives related to building long-term resilience to natural disasters and other stressors. In our research, we consider the stakeholders involved in building local resilience as well as the different and often contradictory framings of the concept. This study takes a phenomenological and inductive approach to understanding resilience. In contrast to more reductionist frameworks that are frequently offered, we argue that this allows for greater understanding of the polyvocal and emergent qualities of resilience.

Abstract: In this paper we present Aurorasaurus: a website, a mobile application, and a citizen science initiative that allows a community of users to report and verify sightings of the Aurora Borealis. Through ad-hoc data indirectly offered through social media, a community of citizen scientists verify sightings of the Aurora Borealis. These verified data are tested against currently existing aurora-forecasting models. The insights these data provide are transformed into map and text-based forms. In addition, notifications are sent to interested participants in a timely manner. This is a design test-bed for an early warning system (EWS) that is capable of detecting and communicating the earliest signs of disaster to community members in near real time. Most importantly, this system incorporates community participation in improving the quality of data mined from Twitter and direct community contributions.

Abstract: A key challenge for research roadmapping in the crisis response and management domain is articulation of a shared vision that describes what the future can and should include. Visioning allows for far-reaching stakeholder engagement that can properly align research with stakeholders? needs. Engagement includes feedback from researchers, policy makers, general public, and end-users on technical and non-technical factors. This work articulates a process and framework for the construction and maintenance of a stakeholder-centric research vision and roadmap in the emergency management domain. This novel roadmapping process integrates three pieces: analysis of the research and technology landscape, visioning, and stakeholder engagement. Our structured engagement process elicits research foci for the roadmap based on relevance to stakeholder mission, identifies collaborators, and builds consensus around the roadmap priorities. We find that the vision process and vision storyboard helps SMEs conceptualize and discuss a technology?s strengths, weaknesses, and alignment with needs.