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Due to persistent and serious threats from natural disasters around the globe, many have turned to resilience and vulnerability research to guide disaster preparation, recovery, and adaptation decisions. In response, scholars and practitioners have put forth a variety of disaster indices, based on quantifiable metrics, to gauge levels of resilience and vulnerability. However, few indices are empirically validated using observed disaster impacts and, as a result, it is often unclear which index should be preferred for each decision at hand. Thus, we compare and empirically validate five of the top U.S. disaster indices, including three resilience indices and two vulnerability indices. We use observed disaster losses, fatalities, and disaster declarations from the southeastern United States to empirically validate each index. We find that disaster indices, though thoughtfully substantiated by literature and theoretically persuasive, are not all created equal. While four of the five indices perform as predicted in explaining damages, only three explain fatalities and only two explain disaster declarations as expected by theory. These results highlight the need for disaster indices to clearly state index objectives and structure underlying metrics to support validation of the results based on these goals. Further, policymakers should use index results carefully when developing regional policy or investing in resilience and vulnerability improvement projects.

In this study, we propose a mixed-integer linear programming model for a Heterogeneous Fixed Fleet Drone Routing problem (HFFDRP) that minimizes the post-disaster inspection cost of a disaster-affected area by accounting a number of drone trajectory-specific factors into consideration such as battery recharging costs, servicing costs, drone hovering, turning, acceleration, constant, and deceleration costs, and many others. The trajectories between each pair of nodes are constructed using a path construction model. Two heuristic algorithms are proposed, namely, Adaptive Large Neighborhood Search (ALNS) algorithm and Modified Backtracking Adaptive Threshold Accepting (MBATA) algorithm, to solve the largest instances of our proposed optimization model. Computational results indicate that the proposed MBATA algorithm is capable of producing high-quality solutions consistently within a reasonable amount of time. Finally, a real-life case study is used to visualize and validate the modeling.

Cameron Parish, Louisiana, was impacted by one of the most devastating hurricane seasons in U.S. history in 2005. Three weeks after Hurricane Katrina hit New Orleans, Hurricane Rita stormed over the Texas-Louisiana border delivering another debilitating blow to the Louisiana coast and creating devastation along the southwestern coastline. In March 2008, the Federal Emergency Management Agency (FEMA) updated the Flood Insurance Rate Maps (FIRMs) for Cameron Parish. These maps rezoned much of Cameron Parish by placing a majority of the parish's land in a flood zone rating of V or higher. FEMA's reluctance to provide federal disaster funds to substantially redevelop and newly construct buildings in areas classified as a flood zone rating of V or higher makes it difficult for Cameron Parish to redevelop as they desperately need federal assistance. This research analyzes Cameron Parish's resources to protect against the hurricane before it hit as well as roles of the federal, state, and local governing bodies on its future development through planning initiatives after the hurricane. Using literature review, state and local media coverage, and interviews with professionals in the field of planning and engineering, this report found that it took a massive hurricane to convey the need for planning in Cameron Parish, and that the flood maps used to provide risk do not communicate risk management as efficiently or accurately as intended. / text

Despite the devastation caused by environmental catastrophes, these phenomena have yet to garner significant attention as a subject of criminological inquiry. This thesis is framed by the following question: How can we problematize the notion of “natural” disaster to arrive at a criminological understanding of human culpability in the production of harm? I argue that the degree of human suffering caused by natural disasters is aggravated by imperialistic state crimes, which predispose populations to conditions of vulnerability and dependency. I substantiate this argument with an analysis of Haiti and demonstrate how its history of imperialistic exploitation by the US amounted to a pattern of state crime victimization that marginalized Haitians and, consequently, shaped their suffering from the 2010 earthquake. The story of Haiti exemplifies the relationship between the contemporary hardships of a natural disaster and the historical injustices of state crime, thus illuminating the relevance of a criminology of catastrophe. / UOIT

This Note asserts that natural disaster-affected populations have a right to call on the international community to protect basic subsistence interests where their sovereign government is unable or unwilling to do so in the wake of a catastrophic natural disaster. First, this Note situates the right to international humanitarian assistance following a natural disaster as a legitimate right under modern international human rights law, using the normative framework set out by renowned political theorist Charles Beitz. This Note then illustrates how the international humanitarian law doctrine of the Responsibility to Protect provides a clear and coherent way to operationalize the right to post-natural disaster humanitarian assistance, by providing a previously-determined structure for a definitive, yet circumstantially-flexible, determination of first- and second-level responsibilities for eligible international actors to take action in defence of this right.

This Note asserts that natural disaster-affected populations have a right to call on the international community to protect basic subsistence interests where their sovereign government is unable or unwilling to do so in the wake of a catastrophic natural disaster. First, this Note situates the right to international humanitarian assistance following a natural disaster as a legitimate right under modern international human rights law, using the normative framework set out by renowned political theorist Charles Beitz. This Note then illustrates how the international humanitarian law doctrine of the Responsibility to Protect provides a clear and coherent way to operationalize the right to post-natural disaster humanitarian assistance, by providing a previously-determined structure for a definitive, yet circumstantially-flexible, determination of first- and second-level responsibilities for eligible international actors to take action in defence of this right.

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An increasing trend in both the number of disasters and affected people has been observed, especially during the second half of the 20th century. The physical, economic and social impact that natural hazards have had on a global scale has prompted an increasing interest of governments, international institutions and the academia. This has immensely contributed to improve the knowledge on the subject and has helped multiply the number of initiatives to reduce the negative consequences of natural hazards on people. The scale on which studies supporting disaster risk reduction (DRR) actions are performed is a critical parameter. Given that disasters are recognized to be place-dependent, studying the geographical distribution of disasters on a local scale is essential to make DRR practical and feasible for local authorities, organizations and civilians. However, studying disasters on the local scale is still a challenge due to the constraints posed by scarce data availability. Social vulnerability in many disaster-prone areas is however a pressing issue that needs to be swiftly addressed despite of the many limitations of data for such studies. This thesis explored methodological alternatives to study the geographical distribution of natural disasters and their potential causes in disaster-prone and data-scarce areas. The Samala River catchment in Guatemala was selected as a case study, which is representative of areas with high social vulnerability and data scarcity.  Exploratory methods to derive critical disaster information in such areas were constructed using the geographical and social data available for the study area. The hindrances posed by the available data were evaluated and the use of non-traditional datasets such as nightlights imagery to complement the available data were explored as a way of overcoming the observed limitations. The exploratory methods developed in this thesis aim at (a) deriving information on natural disasters under data-scarce circumstances, (b) exploring the correlation between the spatial distribution of natural disasters and the physical context in order to look for causalities, (c) using open data to study the social context as a potential cause of disasters in data-scarce areas, and (d) mapping vulnerabilities to support actions for disaster risk reduction. Although the available data for the case study was limited in quantity and quality and many sources of uncertainty exist in the proposed methods, this thesis argues that the potential contribution to the development of DRR on a local scale is more important than the identified drawbacks. The use of non-traditional data such as remotely sensed imagery made it possible to derive information on the occurrences of disasters and, in particular, causal relationships between location of disasters and their physical and social context. / El número de desastres y personas afectadas por esos desastres en el mundo han mostrado una tendencia creciente, especialmente en la segunda mitad del siglo veinte. El impacto físico, económico y social que las amenazas naturales han causado a nivel global ha causado que gobiernos, instituciones internacionales y la academia se interesen cada vez más en los desastres causados por esas amenazas. Este interés ha contribuido a mejorar el conocimiento existente sobre desastres y ha contribuido a multiplicar las iniciativas orientadas a reducir sus efectos negativos en las personas. La escala en la cual las iniciativas para la reducción del riesgo de desastres (RRD) se llevan a cabo es un parámetro crítico para su materialización. Hoy en día se reconoce la estrecha relación que existe entre los desastres y los lugares donde éstos se registran. Por esta razón, estudiar la distribución de los desastres en una escala local es esencial para que la RRD sea práctica y factible para autoridades y organizaciones locales, y también para la sociedad civil. Sin embargo, estudiar los desastres en una escala local es aún un problema por resolver debido a las restricciones impuestas por la escasa disponibilidad de datos de alta resolución. A pesar de las dificultades y limitaciones identificadas, la vulnerabilidad social en las regiones propensas a desastres es un problema importante que necesita ser atendido con prontitud. La presente tesis exploró alternativas metodológicas para estudiar la distribución geográfica de los desastres naturales y sus causas potenciales, particularmente en áreas propensas a desastres y en condiciones de información limitada. La cuenca del Río Samalá fue seleccionada como caso de estudio debido a que es un área representativa de áreas propensa a desastres con alta vulnerabilidad social y además escasez de datos. El trabajo de investigación propone métodos exploratorios para extraer información crítica sobre desastres utilizando la información geográfica y social que esté disponible, evaluando los obstáculos impuestos por la reducida disponibilidad de datos. La información existente fue complementada con el uso de fuentes de información no tradicional, e.g. imágenes satelitales de luces nocturnas, como una manera de superar las limitaciones identificadas. Los métodos desarrollados en este trabajo de tesis tuvieron como objetivos (a) obtener información sobre desastres naturales en condiciones de escasez de datos, (b) explorar la correlación entre la distribución espacial de los desastres naturales y su contexto físico para identificar causalidades, (c) utilizar información de libre acceso para estudiar el contexto social de los desastres como causa potencial de los desastres en áreas con escasez de datos, y (d) mapear vulnerabilidades para sustentar acciones para la RRD. Este trabajo de tesis sostiene que la contribución potencial de los métodos propuestos al desarrollo de la RRD en la escala social es más importante que las incertidumbres que implican y las limitaciones creadas por la reducida calidad y cantidad de información para el caso de estudio. El uso de fuentes de información no tradicionales tales como imágenes satelitales hizo posible incrementar la información sobre las incidencias de desastres y, en particular, buscar relación de dependencia entre los lugares particulares en los que los desastres fueron registrados y su contexto físico y social.