Natural disasters and human capital accumulation

The author assesses empirically the relationship between natural disaster risk and investment in education. Although the results in the empirical literature tend to be inconclusive, using model averaging methods in the framework of cross-country and panel regressions, this paper finds an extremely robust negative partial correlation between secondary school enrollment and natural disaster risk. This result is exclusively driven by geological disasters. Natural disaster risk exposure is a robust determinant of differences in secondary school enrollment between countries, but not within countries, which implies that the effect can be interpreted as a long-run phenomenon.Natural Disasters,Hazard Risk Management,Disaster Management,Population Policies,Access to Finance

Building the University--Community Partnership in Disaster Management

The Center for Defense Integrated Data (CDID) and the Coastal Hazards Center of Excellence (CHC) at Jackson State University have developed the Disaster Response Intelligent System (DRIS) to ensure interoperable communication, rapid data processing for safe and timely evacuations, scenario analysis, and decision support during disaster events. With an increasing occurrence of both natural and man-made disasters, theoretical underpinnings have emerged to address not only how communities respond to disasters but also how they plan for such. Currently, there is a need to expand upon the existing paradigm in the highly specialized, practitioner driven field of emergency response and disaster management. Perhaps there are no better institutions to guide such expansion than institutions of higher education. The DRIS application has, as an extension, an education model wherein the system is installed at universities with disaster management programs or related curricula. Such installation builds on the university’s capacity to foster a multi-disciplinary approach to emergency response and disaster management by incorporating academic areas such as urban planning, computer science, environmental science, social science, geography, and various disciplines of engineering among others

Developing situation-aware applications for disaster management with a distributed rule-based platform

In order to enhance interoperability and productivity in the develop-ment of situation-aware applications for disaster management, proper mecha-nisms and guidelines are required. They must address the lack of semantics in modelling emergency situations. In addition, the ever changing and unpredicta-ble nature of disaster scenarios present challenges for information processing and collaboration. This paper proposes a framework that combines the follow-ing elements: (i) a foundational ontology for temporal conceptualization; (ii) well-founded specifications of structural and behavioral models; (iii) a CEP en-gine based on a distributed rule-based platform for situation management; (iv) a model-driven approach. We illustrate the operation of the framework with a scenario for monitoring tuberculosis epidemy

Citizen Science in Disaster and Conflict Resilience

*Background/Question/Methods*

Within the disaster and conflict response communities, concern about lack of effectiveness of outside responses has led to a debate about the role of local people in developing the capacity to prepare for a crisis and to respond after calamity has struck. Pelling (2007) points out the potential for participatory disaster risk assessment to build local capacity and for generating knowledge that, along with more expert-driven data collection, is used to identify and reduce the risk of disaster. Similarly, Weinstein and Tidball (2007) and Tidball et al. (2008) present an alternative model for post-crisis intervention based on local assets, including ongoing attempts of communities to manage their natural resources. For example, these authors suggest that civic ecology (CE) practices, including community forestry, watershed enhancement, community agriculture and gardening, and other participatory environmental restoration initiatives that emerge from the actions of local residents (Tidball and Krasny 2007), should be examined and perhaps leveraged by outsiders for their ability to mitigate post-crisis situations. The question is, how might CE relate to citizen science in applications post-disaster or conflict?

*Results/Conclusions*

CE practices emerge through the actions of people wanting to manage a local resource, and integrate both learning through small-scale experimentation and observations (adaptive management) and collaborative or participatory processes (co-management). They can be considered as an emergent form of adaptive co-management (Ruitenbeek and Cartier 2001; Armitage, Plummer et al. 2009). The local knowledge of individuals who initiate the practices is critical, although often linkages are made with scientists from universities, government, and non-profit organizations, so multiple forms of knowledge are incorporated into the stewardship activities. This learning shortens feedback times between management actions, such as participatory approaches for planting trees, and seeing the impact of tree planting on local ecological and social systems. CE practices embody attributes that may foster resilience both prior to and post-crisis, including multiple forms of knowledge and governance, self-organization, adaptive learning, shorter feedbacks, and ecosystem services (Folke, S. Carpenter et al. 2002; Walker and Salt 2006). We demonstrate that similar to CE, citizen science could build capacity to mitigate disaster and conflict through shortening feedbacks and through making available multiple forms of knowledge and data collection. Further, given the need for asset-based and participatory interventions post-crisis, and the paucity of existing mechanisms that address this need (Weinstein and Tidball 2007), we examine citizen science and its potential to become part of a tool kit of participatory responses that engage citizens in meaningful activity post-conflict

Named data networking for efficient IoT-based disaster management in a smart campus

Disasters are uncertain occasions that can impose a drastic impact on human life and building infrastructures. Information and Communication Technology (ICT) plays a vital role in coping with such situations by enabling and integrating multiple technological resources to develop Disaster Management Systems (DMSs). In this context, a majority of the existing DMSs use networking architectures based upon the Internet Protocol (IP) focusing on location-dependent communications. However, IP-based communications face the limitations of inefficient bandwidth utilization, high processing, data security, and excessive memory intake. To address these issues, Named Data Networking (NDN) has emerged as a promising communication paradigm, which is based on the Information-Centric Networking (ICN) architecture. An NDN is among the self-organizing communication networks that reduces the complexity of networking systems in addition to provide content security. Given this, many NDN-based DMSs have been proposed. The problem with the existing NDN-based DMS is that they use a PULL-based mechanism that ultimately results in higher delay and more energy consumption. In order to cater for time-critical scenarios, emergence-driven network engineering communication and computation models are required. In this paper, a novel DMS is proposed, i.e., Named Data Networking Disaster Management (NDN-DM), where a producer forwards a fire alert message to neighbouring consumers. This makes the nodes converge according to the disaster situation in a more efficient and secure way. Furthermore, we consider a fire scenario in a university campus and mobile nodes in the campus collaborate with each other to manage the fire situation. The proposed framework has been mathematically modeled and formally proved using timed automata-based transition systems and a real-time model checker, respectively. Additionally, the evaluation of the proposed NDM-DM has been performed using NS2. The results prove that the proposed scheme has reduced the end-to-end delay up from 2% to 10% and minimized up to 20% energy consumption, as energy improved from 3% to 20% compared with a state-of-the-art NDN-based DMS

Incremental reconstruction of moving object trajectory

This article presents a model and a prototype implementation of a technical application programming interface (API) for incremental reconstruction of the moving objects trajectories captured by closed-circuit television (CCTV) and High-definition television (HDTV) cameras. This paper proposes a unique, much simpler model-driven approach which is more efficient than other approaches for dynamic tracking such as Microsoft Kinect. The research reported here is part of a research program of the Cybersecurity Research Group of London Metropolitan University for real-time video analytics with applicability to surveillance in security, disaster recovery and safety management, and customer insight

Exploring good practice knowledge transfer related to post tsunami housing re-construction in Sri Lanka

Sri Lanka was badly affected by the tsunami that occurred on 26th December 2004. The tsunami destroyed about two-thirds of the Sri Lankan coastline and affected more than 1,000,000 people. It does not only affected the lives of the community, but also had a devastating effect on their housing and livelihoods. The overall loss of 100,000 or more houses due to the tsunami proved to be a major challenge to the emergency response teams and disaster planners. Although several major disasters of varying magnitudes have occurred in the world, the body of knowledge related to post-disaster housing reconstruction and rehabilitation appears fragmented and poorly integrated. This paper attempts to fill this theoretical gap by focusing on the extent to which good practice knowledge transfer helps in overcoming this problem for more effective and efficient delivery of post-tsunami housing in Sri Lanka. The paper applied knowledge transfer principles within the context of the two housing reconstruction strategies employed in post-tsunami housing reconstruction in Sri Lanka; namely donor-driven housing and owner driven housing. The results of this study reveal that the knowledge transfer within this context cannot be simply copied and inserted from one context without any localisation. Therefore, the paper proposes a high-level abstraction of the core principles of community engagement through participatory techniques associated with appropriate capacity and capability building techniques that will enable the various stakeholders to create a new application to suit the appropriate context of the transfer destination (post-tsunami context in Sri Lanka)

Improving the resilience of post-disaster water distribution systems using a dynamic optimization framework

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Improving the resilience of water distribution systems (WDSs) to handle natural disasters (e.g., earthquakes) is a critical step towards sustainable urban water management. This requires the water utility to be able to respond quickly to such disaster events and in an organized manner, to prioritize the use of available resources to restore service rapidly whilst minimizing the negative impacts. Many methods have been developed to evaluate the WDS resilience, but few efforts are made so far to improve resilience of a post-disaster WDS through identifying optimal sequencing of recovery actions. To address this gap, a new dynamic optimization framework is proposed here where the resilience of a post-disaster WDS is evaluated using six different metrics. A tailored Genetic Algorithm is developed to solve the complex optimization problem driven by these metrics. The proposed framework is demonstrated using a real-world WDS with 6,064 pipes. Results obtained show that the proposed framework successfully identifies near-optimal sequencing of recovery actions for this complex WDS. The gained insights, conditional on the specific attributes of the case study, include: (i) the near-optimal sequencing of recovery strategy heavily depends on the damage properties of the WDS, (ii) replacements of damaged elements tend to be scheduled at the intermediate-late stages of the recovery process due to their long operation time, and (iii) interventions to damaged pipe elements near critical facilities (e.g., hospitals) should not be necessarily the first priority to recover due to complex hydraulic interactions within the WDS

Climate change and variability, energy and disaster management: produced risks without produced solutions: rethinking the approach

Accelerated climate change and increasing climate variability is the single largest threat to the international goals of sustainable development, the Millennium Development Goals (MDGs) and disaster risk reduction. Global discourses recognise the need for effective and sustainable responses tso produced climate risks. The risk types likely to occur are known, but only in broad terms - their scale, severity, longevity and frequency are not known. The challenge for policymakers is developing an effective framework within which sustainable responses can be formulated. To address the problems of produced risks a comprehensive approach to risk management is necessary. The mechanisms within the climate change, sustainable development and disaster risk reduction discourses are not sufficiently effective or integrated to respond to this challenge. Fundamental reform to current modes of risk reduction is needed, but this can only be achieved through a shift in the dominant perspective on formulating sustainable responses. This requires a shift to an enabling policy framework that encourages bottom-up resilient responses. Resilience is argued as a tool for policy development that can enhance adaptive capacity to current climate risks and shape energy policy to respond to mitigate future climate risks