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Understanding human mobility patterns is important for severe weather warning since these patterns can help identify where people are in time and in space when flash floods, tornados, high winds and hurricanes are occurring or are predicted to occur. A GIS (Geographic Information Science) data model was proposed to describe the spatial-temporal human activity. Based on this model, a metric was designed to represent the spatial-temporal activity intensity of human mobility, and an index was generated to quantitatively describe the change in human activities. By analyzing high-resolution human mobility data, the paper verified that human daily mobility patterns could be clearly described with the proposed methods. This research was part of a National Science Foundation grant on next generation severe weather warning systems. Data was collected from a specialized mobile app for severe weather warning, called CASA Alerts, which is being used to analyze different aspects of human behavior in response to severe weather warnings. The data set for this research uses GPS location data from more than 300 APP users during a 14 month period (location was reported at 2 minutes interval, or at based on a 100m change in location). A targeted weather warning strategy was proposed as a result of this research, and future research questions were discussed.

The intent of this study was to develop a sixty minute, mediated practical first aid teaching unit for the missionary system of the Church of Jesus Christ of Latter-day Saints.

It is critical to provide an efficient and accurate information system in the post-disaster phase for individuals' in order to access and obtain the necessary resources in a timely manner; but current map based post-disaster management systems provide all emergency resource lists without filtering them which usually leads to high levels of energy consumed in calculation. Also an effective post-disaster management system (PDMS) will result in distribution of all emergency resources such as, hospital, storage and transportation much more reasonably and be more beneficial to the individuals in the post disaster period. In this Dissertation, firstly, semi-supervised learning (SSL) based graph systems was constructed for PDMS. A Graph-based PDMS' resource map was converted to a directed graph that presented by adjacent matrix and then the decision information will be conducted from the PDMS by two ways, one is clustering operation, and another is graph-based semi-supervised optimization process. In this study, PDMS was applied for emergency resource distribution in post-disaster (responses phase), a path optimization algorithm based ant colony optimization (ACO) was used for minimizing the cost in post-disaster, simulation results show the effectiveness of the proposed methodology. This analysis was done by comparing it with clustering based algorithms under improvement ACO of tour improvement algorithm (TIA) and Min-Max Ant System (MMAS) and the results also show that the SSL based graph will be more effective for calculating the optimization path in PDMS. This research improved the map by combining the disaster map with the initial GIS based map which located the target area considering the influence of disaster. First, all initial map and disaster map will be under Gaussian transformation while we acquired the histogram of all map pictures. And then all pictures will be under discrete wavelet transform (DWT), a Gaussian fusion algorithm was applied in the DWT pictures. Second, inverse DWT (iDWT) was applied to generate a new map for a post-disaster management system. Finally, simulation works were proposed and the results showed the effectiveness of the proposed method by comparing it to other fusion algorithms, such as mean-mean fusion and max-UD fusion through the evaluation indices including entropy, spatial frequency (SF) and image quality index (IQI). Fuzzy set model were proposed to improve the presentation capacity of nodes in this GIS based PDMS.

In the event of a bioterrorist attack, emergency departments are considered the first line of response for all acute levels of care. This study focused on hospital emergency departments in Florida and the activities, policies, and procedures involved in preparing for a bioterrorist attack. Hospital size, location, and system affiliation were related to attaining these levels, and their impact was assessed. Through a cross-sectional survey design, the physical properties of the 77 hospitals (i.e. facilities, equipment, communication systems, etc.), and the social characteristics of the organizations (managerial functions including: planning, training, financial, and environmental characteristics) were examined. One-way analysis of variance and t-tests revealed that bed size was a significant predictor of mean levels of preparedness. In addition, although more hospitals are conducting training activities, a disconnect between plans and communications of said plans still exists along with many deficiencies still needing to be corrected. Study limitations are discussed and important policy implications are presented. Suggestions for improving preparedness levels and implementing new policies include: conducting training exercises, developing community ties and mutual aid agreements, and using information technology with detection of an event and communication of the information garnered from these efforts.

Emergency management coordination in the United States has fallen victim to over a century of strategies to organize, reorganize, consolidate, or decentralize disaster preparedness, planning and response. Regardless of the agency in charge at the federal level, individual citizens have been responsible for their own well-being immediately after any disaster or emergency event for more than 100 years because it takes time to mobilize and deliver aid. The system most often charged with managing that mobilization during an emergency event that exceeds the response capacity of local public safety agencies is the state emergency management network. Many entities in a state emergency management network have different responsibilities during disaster states vs. non-disaster states. Regardless of their role and function, entities need to be able to exchange resources and information with each other, often under time, economic, or other constraints during disasters. This resource exchange generates trust, an essential element of a resilient network. Resilient networks suffer fewer negative impacts from disaster related loss and are more likely to retain collective capacity to respond and help communities recover. The purpose of this study is to explore the ability of individual and state level attributes to explain variability in perception of network resilience. One-hundred fifty one state emergency management agency employees were surveyed regarding their perception of 5 constructs of network resilience (rapidity, redundancy, relationships, resourcefulness, and robustness) and individual level attributes. State level indicators from FEMA, NEMA, American Human Development Index, and Social Vulnerability Index were also analyzed. Overall, it was found that the individual attribute of perception of network integrity had the most influence on perception of network resilience, followed by perception of community resilience and state level attributes including disaster experience, state well-being, and number of full time state emergency management agency employees. These findings can improve network resilience by informing state emergency management network development activity. Networks that increase member opportunities to develop relationships of resource and information exchange will increase their resilience. That increased network resilience impacts community resilience because, as Winston Churchill's wise words during World War II reconstruction advise, "We shape our communities and then they shape us".

Catastrophic disasters are different than routine disasters and managing them requires the mobilization of inter-organizational, inter-governmental, cross-sectoral and international humanitarian support. The role of the international community through International Nongovernmental Organizations (INGOs), and multi-lateral organizations such as the United Nations (UN) becomes imperative when the scale of the disaster is unprecedented and difficult for a country to manage on its own. The initial response and relief phase of managing disasters is one in which many agencies with different expertise, capacities, working mandates, resources, skills, working cultures and norms come together to coordinate and collaborate to provide timely response and relief services. Thus, the terrain of managing catastrophic disasters is complex and requires a deeper study to understand and delineate the factors shaping and facilitating collaborative response and relief efforts. This study examines the multi-level and multi-layered collaborative response networks present at the national-international level, provincial and district/local level of disaster response and interactions. In this research the nature and effectiveness of collaboration is being studied through a relevant case study of a catastrophic natural disaster, the 2010 Pakistan Floods. The phase of immediate response is explored primarily through Network Theory perspectives including supportive theoretical perspectives such as Social Capital, Resource Dependency, and Institutional Collective Action Theory perspectives that help to explain collaborative interactions in disaster response networks. This study explores and describes factors that influence (either facilitate or hinder) collaboration is disaster response networks. iv The key research questions for this study are: What factors facilitate and impede collaborative response to catastrophic disasters at the local, provincial, national and international levels? What are the differences and similarities in response systems at different levels? Additional questions address how leadership support (attributed to government and political leaders and organizations), institutional support (in the form of plans, international appeals of response, and development of relief funds to manage aid), network capacity of different organizations (programmatic and relational), nature of resource dependencies between responding agencies, and structural configurations of response systems impact the collaborative response in disasters. A case study method has been applied in this research. The 2010 Pakistan Floods response network/system is identified through content analysis of various newspapers, situation reports and after-action reports using the Social Network Analysis (SNA) method via UCINET Software 6.1. The actual response network is analyzed and compared with existing national disaster response plans to examine the effectiveness of collaborative response through centrality measures, clique analysis and visual display. This approach is supplemented with semistructured interviews of key institutional representatives that responded to the 2010 Floods. These organizations and institutions were primarily identified through the networks formulated via SNA. Findings and results from the analysis reflect that the response networks at each level of analysis differ both in structural aspects and also in functional aspects. The nature of the international-national response system is focused on mobilizing donor support and receiving and v managing aid, both in-kind and cash. Also a major role at the international and national level is to mobilize the UN cluster approach and focus on broader aims of response such as providing shelter and food to affected areas. Some of the factors identified as facilitating collaborative response were leadership of both national and international leaders, and availability of donor support and funds. At the provincial level of analysis, the Chief Minister of Punjab is playing a central and influential role and is partnering closely with the Armed Forces and local district administration. Interviews conducted of provincial level officials help to support the hypotheses concerning leadership support’s influence on collaborative response and also the role of institutional support in the form of creation of plans, and policies that help to mobilize quick funds and resources for relief. At the local level of response, networks are highly influenced by local conditions and local capacities of the district administration. Thus, there are diverse factors impacting each level of collaborative disaster response. All in all, leadership support, institutional support and network structural aspects are important variables that impact the effectiveness of collaborative response. Today policy makers are trying to figure out ways to collaborate successfully across sector boundaries for better and effective service delivery, both in the mundane operational tasks and in uncertain and complex situations such as disasters and catastrophic events. Thus, this research helps in expanding the literature on collaborative public management, collaborative emergency management, and network management. Also the frequency of natural disasters throughout the world demonstrate the need to study and examine factors that contribute to or hinder the effectiveness of inter-organizational response in disasters.

The purpose of this descriptive study is to determine if there is a difference in citizen trust in Orange County government regarding the handling of disaster. Various dimensions like competence, benevolence, and integrity can determine a citizen's trust within its government. Disasters, such as man-made and natural, are described as a disruption to society through widespread damage to people and material. Counties experience man-made and natural disasters. Depending on its response to the incidents, counties can determine if the citizens view the county as a trustworthy and responsible government body. This study explored if there were differences in citizen trust in government response to different disasters and if citizens of different demographics had differing levels of trust. This study found that 1) there is no statistical difference between the average citizen trust scores between the two disasters 2) there is no statistical difference between the average citizen trust scores for the two groups, and 3) there is no statistical difference between the overall average citizen trust score between older and younger generations.

Disaster debris cleanup operations are commonly organized into two phases. During the first phase, the objective is to clear debris from evacuation and other important pathways to ensure access to the disaster-affected area. Practically, Phase 1 activities largely consist of pushing fallen trees, vehicles, and other debris blocking streets and highways to the curb. These activities begin immediately once the disaster has passed, with the goal of completion usually within 24 to 72 hours. In Phase 2 of debris removal, which is the focus of this study, completion can take months or years. Activities in this phase include organizing and managing curbside debris collection, reduction, recycling, and disposal operations (FEMA 2007). This dissertation research investigates methods for improving post-disaster debris cleanup operations—one of the most important and costly aspects of the least researched area of disaster operations management (Altay and Green 2006). The first objective is to identify the unique nature of the disaster debris cleanup problem and the important decisions faced by disaster debris coordinators. The second goal is to present three research projects that develop methods for assisting disaster management coordinators with debris cleanup operations. In the first project, which is the topic of Chapter 3, a facility location model is developed for addressing the problem of opening temporary disposal and storage reduction facilities, which are needed to ensure efficient and effective cleanup operations. In the second project, which is the topic of Chapter 4, a multiple objective mixed-integer linear programming model is developed to address the problem of assigning debris cleanup resources across the disaster-affected area at the onset of debris cleanup operations. The third project and the focus of Chapter 5 addresses the problem of equitably controlling ongoing cleanup operations in real-time. A self-balancing CUSUM statistical process control chart is developed to assist disaster management coordinators with equitably allocating cleanup resources as information becomes available in real-time. All of the models in this dissertation are evaluated using data from debris cleanup operations in Chesapeake, Virginia, completed after Hurricane Isabel in 2003. / Ph. D.

Yes / This study has addressed and identified the problems in managing the existing emergency supply chain of Bangladesh in all phases of operation in terms of the primary drivers of the supply chain. It has also attempted to conceptualize and suggest an effective emergency supply chain. In this context, a thorough field investigation in several districts was conducted among the employees of the organizations sharing common information with similar protocols and implications (interoperable). Information was collected from the employees of all the participating organizations involved in disaster management through a semi-structured questionnaire based survey. The respondents addressed and illustrated several interconnected reasons which are inhibiting proper forecasting, procurement, storage, identification of affected people, and distribution. The respondents pointed out that the mismatching of objectives in the different organizations resulted in non-interoperability among the participating organizations. These issues are related to the malfunctioning of management with multidimensional organizational conflicts. Reflecting those issues, an emergency supply chain for disaster management is proposed in this study