Information Technology in Disaster Risk Reduction

From our experience the Great East Japan Earthquake in March 2011 to help out the people in the affected area in terms of IT support such as internetworking and providing PCs, we came across an interesting issue concerning collaboration with people including supporters as well as the victims. We call this problem disaster communications. We also came to know the needs for disaster information processing as there was no such systems to manage shelters, goods distribution and volunteers. On the other hand such systems have been researched in the United States of America and Europe in terms of information processing for emergency management to a great extent. While we have had many natural disasters in Japan, only a very few of the researchers in computer science and information systems have been working on this issue. From this perspective, we try to identify the information required at disaster in this research. In particular, we explored the needs and seeds for disaster information processing in Iwate, Japan. We interviewed some supporters at Iwate in March 2011 such as local government officials, doctors and university administrators and found the situation awareness was required desperately in the beginning of the disaster. This paper reports our project of interviewing people who worked on disaster relief during the emergency response as well as our trial of a system for situation awareness based on the results from our interviews.

Nowadays, ICT has been broadly applied to all trades and professions, because of instant end-to-end connectivity and at-hand convenience. For sake of better enhancing disaster resilience, scientists, engineers and practitioners are make the most use of information and communication technology to all phases of disaster risk management- reduction, preparedness, response and recovery. Especially at the IOT age, the powerful tools provide both macro- and micro- viewpoints in both physical and social vulnerabilities that could help to make decisions on disaster risk reduction or emergency response. How to massage all informative and multiple inputs to meet demands of different users that requires several elements to succeed: (1) To identify fields to apply ICT for; (2) To design information intelligence for action; (3) To disseminate information through various channels; (4) To build up public-private partnership in information sharing; (5) To carefully utilize social media. During last decade, though team work between emergency responders and scientists, Taiwan has developed a systematic approach to integrate scientific outputs with emergency operation amid times of typhoons. The results do prove well-organized information shared by ICT both increase efficacy of emergency operation and public awareness.

As more sensor networks, the Internet of Things (IoT) and smart devices are applied for data collection, including physical parameters or social responses, it is a growing trend that big data is dominating quality of disaster risk reduction, emergency preparedness and emergency operation. How to appropriately use big data depends on quality, transmission, exchange, storage, display and dissemination during the whole process data life cycle. “Data life cycle” means approaches to improve knowledge to use big data. Moreover, to solve issues related to disaster risk management is required to integrate diverse data sets based on the characteristics of individual requests. For example, an execution of early eviction before a typhoon makes landfall, demographic structure, weather forecast, real-time rainfall monitoring, threshold values to trigger flood or landslide and supporting resources are the essential elements for a successful operation. However, lots of digital preparedness need comprehensive coordination and arrangements in advance. In order to further make the most use of data for enhancing public awareness and decision formation, producing open data is also important to reach targeted groups of users through understating key information intelligence to take right reactions. Since embracing policy of open data, it needs enablers to set up a well-regulated environment among original data producers, data aggregator, app or system developers, transmission channel providers and final message receivers. An developing example tells the recent developments on big data and open data for disaster risk management.

Disasters leave a trail of destruction, casualties and ruined human lives. They can directly cause loss of life and injury, destroy cities, buildings, living and public spaces, and damage vital infrastructures necessary for everyday functions. The aims of this essay are to present the research tool, in its on-going and yet undefined configuration, and at the same time for involving the many time ICT aspects and challenges of coping with disaster risk reduction and relief, definitely necessary in the operational and disseminating phases beyond the tool itself. Within the paper, along with the exposition of our idea in its actual form – which considers the possibility of further variations – we will present the reasons of the whys and reach to descript how we do believe the tool should be, passing through the other major issues like the who and the what. The tool is intended to be structured as the outcome of an applied research project, for creating a decision supporting instrument which will enable a broad range of relevant stakeholders to choose the most suitable sheltering solution, dwelling unit or machinery needed. The DiMaS Tool research project aims to present itself as a possibility for sorting and mapping already existing ready-to-use solutions, by specific parameters and characteristics, creating a taxonomy and a related system and expressing it in a universal and understandable language, through the ICT skills, in order to help choose the most adequate answer, managing the implementation and responsive process quickly and effectively.

The usage of the mHGN as a pattern recognizer cannot necessarily be used to recognize tornados. Two important issues that need to be solved first are related to data handlings of not-accurately recorded data, and to those of complex weather data. The not-so-appropriate data handlings will produce high false positive and true negative rate of the recognition results. Yet, the latest development of those data handlings has been carried out, and has shown positive and promising results. Such a new approach of data handlings can, therefore, be used to improve the quality and the accuracy of forecasting a tornado. The results taken from a simulated circumstances of a multidimensional pattern recognition have shown, that the tornado can be recognized around 9 h earlier with 90% of accuracy. However, several improvements related to the data representation within the mHGN architecture need to be implemented. The deployment of mHGN in several risky areas of tornados can then be expected as an alternative way of reducing damages, losses, and costs.

The concept of a regional information-analytical system for emergency situations is presented. The three-level architecture of such a system and the functions of its main components are described. A generalized model for assessing plans for eliminating the consequences of emergencies is described. The goals and peculiarities of the structural modules for the regional information and analytical system for the prevention and elimination of emergencies are detailed; some examples of the implementation of local subsystems for Ukraine are considered.

The article presents a manner of formulating the problem of designing safety systems in terms of decision-making problems solved with the use of the models of the so-called games with nature. The models of this type are very frequently used to make decisions under conditions of uncertainty. The situation also occurs in the process of designing safety systems. For the purposes of solving the problem, the appropriate understanding of the basic components of the models of games with nature, i.e. the game strategy and the state of nature, was assumed. In this context, a definition of a system and a safety system was provided, along with an interpretation of the relationships between safety system elements (risk reduction measures) and domain elements (hazard factors/sources, hazards), on account of which these systems are designed. The specificity of the functioning of safety systems also required a modification of the decision rules applied within the models used. The modification was illustrated with the example of Wald’s rule. A general concept of formulating the problem of designing safety systems as a decision-making problem was presented, along with the general algorithm of selecting risk reduction measures for safety systems with the use of the modified rules of the models of games with nature. Next, a mathematical model of the research problem was provided, including: creation of the risk reduction measure efficacy matrix, creation of the hazard source – hazard relationship matrix, determination of the payoff matrix, and the modification of decision rules. Usually, there is a need to select more than one risk reduction measure. An already developed original concept of sequential selection of these measures was used. The application of the rule adaptation proposed here was illustrated with an example of a fire protection system for railway vehicles. Hazard sources were identified and hazards related to electrical systems in railway vehicles were formulated. A list of examples of risk reduction measures which may form a safety system was presented.

Disaster information sharing tools are an important aspect of disaster resilience, and it is of utmost importance that these tools are accessible and usable for as many potential users as possible. In this paper, we evaluate the accessibility of a selection of tools for crowdsourcing disaster situation information. As our evaluation shows that the selected tools are not fully accessible, we provide recommendations for mitigation, as well as highlight the importance of further research in this area.

Earthquake is a type of disaster that occurs suddenly in different magnitudes. When magnitude of an earthquake increases it is expected that the effects are much more. Earthquakes in varying magnitude between 4 Mw and 5 Mw cause uneasiness among the public even if they do not cause heavy damage. The aim of this study is to estimate the probability of an earthquake between 4.0 and 5.0 by using artificial neural network model. Monthly real data between 2006 and 2015 is used for the model. Data is analyzed in MATLAB neural network tool, then estimated output value obtained via analysis and output of test value is compared with regression equation. Besides, seasonal effects on magnitude of earthquake are examined. Results show that 90.51% of the earthquake probability between 4.0 and 5.0 can be estimated by using artificial neural network model.

Large Corporates or global brands benefit from economic globalization and continues to grow in terms of comparative advantages across borders with synergy from integrated supply chain. When the large-scale disasters and catastrophes strike the Asia-Pacific Economic Cooperation (APEC) region - such as the 2004 Indian Ocean Tsunami or 2011 Great East Japan Earthquakes and Tsunamis, the impact on global value chain highlight the needs to promote business continuity planning/management (BCP/BCM). Disasters bring along the threats with opportunities in the market place. For mitigating the impact, most of the world leading corporates urge to allocate resources to further strengthen the disaster resilient capability and secure business environment. In APEC, each economy is unique in its geopolitical conditions, but common in its goal to be BCP/BCM capable. With missionary vision on promoting BCP/BCM. APEC deployed strategies in stages of preparatory work to managing risk and impact of large-scale natural disasters. APEC, as a pioneer, seeks to achieve the goal of sustainable quality growth and serve as learning points for interested economies who are in the midst of their BCP/BCM implementation. With review of the global and regional lessons learned from the large-scale disasters, this paper shared the regional efforts on disaster resilience, describe the strategic approaches and operational concept for emergency preparedness through technology and collaboration for enhancing global supply chain resilience across border.

The article is aimed at presenting the proof-of-concept system for automated direct disaster losses, developed within a scientific project of University of National and World Economy, Sofia. The idea behind the project was to create a system that can be used by customers without expert knowledge on physical or economic modeling of disaster effects. Thus alleviating the initial phases of disaster planning in administration, providing raw picture of disaster threats. The article describes in general conceptual and physical schemes of the system and gives main requirements for data and GIS applications that can be used. The process of developing such system shows that it is a complicated, but possible task. The system is not production ready and it is implemented with one physical model for floods. Nevertheless, the possibility to use and reuse the physical model by automation of main model estimation phases gives opportunity for creation and assessment of different alternatives for disaster prevention and relief.

Research in the field of disaster management is done by utilizing information and communication technology. Where disaster management is discussed is about evacuation planning issues. The evacuation stage is a very crucial stage in the disaster evacuation process. There have been many methods and algorithms submitted for the evacuation planning process, but no one has directly addressed evacuation planning on dynamic issues concerning time-varying and volume-dependent. This research will use the Relaxation-Based Algorithm combined with the Route Choice Model to produce evacuation models that can be applied to dynamic issues related to time-varying and volume-dependent because some types of disaster will result in damage as time and evacuation paths are volume-dependent so as to adjust to the change in the number of people evacuated. Disaster data that will be used in this research is sourced from Disaster Information Management System sourced from DesInventar. The results of this study are expected to produce an evacuation planning model that can be applied to dynamic problems that take into account the time-varying and volume-dependent aspects.

Accurate and reliable data processing is of primary importance for drought assessment. It helps decision makers to lay out mitigation measures within the context of drought preparedness planning and water resources management. In order to understand meteorological and hydrological drought, we need to identify drought characteristics (duration, severity and spatial extent). Drought indices are essential tools quantifying drought severity and identifying its frequency and duration. For the calculation of drought indices, availability of long time series of undisturbed, good-quality observational data is essential. The studied area cover a Bulgarian part of the catchment of Struma River which is one of the largest Bulgarian rivers. The general aim of this research is to evaluate the occurrence of hydrological and meteorological droughts in Struma River basin and to show utilization of various indices for comparative analysis of meteorological and hydrological drought. Drought events are identified using the following indices—Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and Streamflow Drought Index (SDI) for time scales 6 and 12 months. Additionally to these indices, we use also Rainfall Anomaly Index (RAI) and introduce Streamflow Anomaly Index (SAI). The main investigated period is 1962–2016.

Due to the increasing complexity of railway signalling systems, the design of those systems is more difficult and the demonstration of their safety can be extremely tedious. In this article, the verification and validation of railway signalling systems is investigated. We explain how railway signalling functions are designed, we show how they can be mathematically modelled using formal methods and we discuss some ways to use formal methods mechanisms to design, verify signalling systems and to prove the validity of their safety properties.

Previous research into the role of social media in crisis communication has tended to overlook how critical infrastructure (CI) operators might benefit from sites such as Facebook and Twitter, focusing instead on how emergency managers and the general public use such platforms. This paper sets out to address this gap by empirically exploring the expectations of French citizens in relation to the crisis communication strategies deployed by CI operators during major incidents. It does so by reviewing the literature on crisis communication, presenting the results of an online questionnaire, and comparing these results to the current practices of the A31 Highway in France, which were examined via a semi-structured interview. Results indicate that members of the public expect CI operators to communicate via traditional and social media. Therefore, the paper proposes that A31 Highway operators should expand their current practices to include social media.

The soil erosion is considered as one of the most serious environmental problem in a global scale. The development of the process could have negative impact on water, vegetation and ecosystem as a hole, as well as to influence on the quality of life. If the process is not mitigated in long term it could change the topographic surface and to trigger geomorphological hazards. The researches on soil erosion require analyses of large volume of information about soil properties, topographic surface, precipitation and land use. In the current research GIS technology is used for building the data base, spatial analyses and visualization of the results. The Universal Soil Loss Equation (USLE) is applied in Map Algebra and spatial distribution of soil loss is presented. The results are considered in relation to land use, particularly arable lands and vineyards. The application of computer technology provide opportunities for easy processing of data and updating the model by adding new data which can be used by territorial planning experts, local authorities and farmers in the planning process, monitoring and mitigating the soil erosion.