Abstract: Greene County in Dayton, OH houses Wright Patterson Air Force Base (WPAFB), whose estimated 2009 economic impact within its Metropolitan Statistical Area (MSA) is $5.17 million. Despite its military/strategic importance as the largest base in the U.S. Air Force, literature search did not uncover a published comprehensive risk analysis for WPAFB, or even Greene County, across the entire spectrum of hazards from natural to technological to man-made (including terrorism). This paper presents a summary report on risk determination and economic impact data for Greene County and WPAFB (within Greene County) in the context of riverine flooding, using FEMA's HAZUS-MH tool. It is hoped that the results will further the regional compilation of data and thus prove of use to the local disaster management community while generally growing the overall body of work in risk analysis. Future work aims to expand regional risk determination to other natural disasters and terrorism scenarios.

Abstract: In case of emergencies (e.g., earthquakes, flooding), rapid responses are needed in order to address victims' requests for help. Social media used around crises involves self-organizing behavior that can produce accurate results, often in advance of official communications. This allows affected population to send tweets or text messages, and hence, make them heard. The ability to classify tweets and text messages automatically, together with the ability to deliver the relevant information to the appropriate personnel are essential for enabling the personnel to timely and efficiently work to address the most urgent needs, and to understand the emergency situation better. In this study, we developed a reusable information technology infrastructure, called Enhanced Messaging for the Emergency Response Sector (EMERSE), which classifies and aggregates tweets and text messages about the Haiti disaster relief so that non-governmental organizations, relief workers, people in Haiti, and their friends and families can easily access them.

Abstract: One of the most important and costly aspects of recovery operations is debris collection and disposal. The unique nature of disaster debris and the extreme amounts generated as a result of the disaster event create challenges for decision makers that are not typically encountered during every day solid-waste disposal operations. This work-in-progress research is aimed at identifying the unique aspects of disaster debris disposal and the need for decision support, which addresses these unique aspects, to assist emergency management coordinators with allocating resources during on-going debris cleanup operations. We will present a decision support system framework, discuss aspects of the knowledge base, model base, and user interface, and show how an emergency management coordinator might use the system during ongoing daily operations using real-world data from a 2003 Atlantic hurricane.

Abstract: Several studies and observations regarding past earthquakes such as 1989 Loma Prieta, 1994 Northridge, or 1999 Marmara earthquakes have shown the importance of lifeline systems functionality on response and recovery efforts. The general direction of studies on simulating lifelines seismic performance is towards achieving more accurate models to represent the system behavior. The methodology presented in this paper is a product of research conducted in the Mid-America Earthquake Center. Electric power, potable water, and natural gas networks are modeled as interacting systems where the state of one network is influenced by the state of another network. Interdependent network analysis methodology provides information on operational aspects of lifeline networks in post-seismic conditions in addition to structural damage assessment. These results are achieved by different components of the tool which are classified as structural and topological. The topological component analyzes the post seismic operability of the lifeline networks based on the damage assessment outcome of the structural model. Following an overview of the models, potential utilizations in different phases of disaster management are briefly discussed.

Abstract: In the past a lot of researchers have defined criteria to determine information quality. Various criteria and dimensions have been identified and examined in different contexts. But very few of them focused on information quality in the context of complex situations, especially in the domain of crisis management. These complex situations demand for an extensive level of information as a basis to the difficult decisions an officer-in-charge has to make. Therefore, if we want to support the decision-making of the leading officers through an at least semi-automated process, we need first of all to find a set of criteria to assess the information quality considering the special requirements of such complex situations. In this paper we describe our approach of defining a criteria set by identifying the characteristics of complex situations, then we analyze existing models of information quality and map their aggregated criteria to the identified characteristics and finally first results of interviews to evaluate the set through the involvement of domain experts are presented.

Abstract: We have been using exploratory modeling to forecast multiple plausible outcomes for a set of decision options situated in the emergency response domain. Results were displayed as a set of box-plots illustrating outcome frequencies distributed across an evaluative dimension (e.g., cost, score, or utility). Our previous research showed that such displays provide what we termed “option awareness” – an ability to determine robust options that will have good outcomes across the broadest number of plausible futures. This paper describes an investigation into extending this approach to collaborative decision making by providing a visualization of both collaborative and individual decision spaces. We believe that providing such visualizations will be particularly important when each individuals decision space does not account for the synergy that may emerge from collaboration. We describe how providing collaborative decision spaces improves the robustness of joint decisions and engenders high confidence in these decisions.