4,864 research outputs found

    A Review on the Application of Natural Computing in Environmental Informatics

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    Natural computing offers new opportunities to understand, model and analyze the complexity of the physical and human-created environment. This paper examines the application of natural computing in environmental informatics, by investigating related work in this research field. Various nature-inspired techniques are presented, which have been employed to solve different relevant problems. Advantages and disadvantages of these techniques are discussed, together with analysis of how natural computing is generally used in environmental research.Comment: Proc. of EnviroInfo 201

    Landslide susceptibility mapping using multi-criteria evaluation techniques in Chittagong Metropolitan Area, Bangladesh

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    Landslides are a common hazard in the highly urbanized hilly areas in Chittagong Metropolitan Area (CMA), Bangladesh. The main cause of the landslides is torrential rain in short period of time. This area experiences several landslides each year, resulting in casualties, property damage, and economic loss. Therefore, the primary objective of this research is to produce the Landslide Susceptibility Maps for CMA so that appropriate landslide disaster risk reduction strategies can be developed. In this research, three different Geographic Information System-based Multi-Criteria Decision Analysis methods—the Artificial Hierarchy Process (AHP), Weighted Linear Combination (WLC), and Ordered Weighted Average (OWA)—were applied to scientifically assess the landslide susceptible areas in CMA. Nine different thematic layers or landslide causative factors were considered. Then, seven different landslide susceptible scenarios were generated based on the three weighted overlay techniques. Later, the performances of the methods were validated using the area under the relative operating characteristic curves. The accuracies of the landslide susceptibility maps produced by the AHP, WLC_1, WLC_2, WLC_3, OWA_1, OWA_2, and OWA_3 methods were found as 89.80, 83.90, 91.10, 88.50, 90.40, 95.10, and 87.10 %, respectively. The verification results showed satisfactory agreement between the susceptibility maps produced and the existing data on the 20 historical landslide locations

    A collaborative approach for disaster risk reduction: mapping social learning with Mistawasis NĂȘhiyawak

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    Social learning and its relation to disaster risk reduction (DRR) have been increasingly highlighted in the literature. Yet, limited empirical research has hampered practical DRR applications. This thesis demonstrated social learning loops and their outcomes by reflecting on the case of 2011 flooding in Mistawasis NĂȘhiyawak. Using a mixed-methods research design, I explored the role of participatory processes, including communication of scientific knowledge to lay-experts, in social learning. First, I created flood extent maps for the community using spatial data and modeling techniques. In the second phase, I presented the maps in a workshop held at the community center to understand their value in regard to what people learn from them. This included deliberating not only about physical parameters of the flood but also exploring the social (and human) parameters. Hence, I used fuzzy cognitive mapping (FCM) as a novel method to represent the human perception of flood risk and to measure social learning. In the workshop, FCM was complemented by focus group discussions and participatory mapping. From the results, it was found that i) social learning can be measured using social sciences tools, ii) sharing experiences and stories from past events augmented learning, and iii) awareness on the role of emergency planning in DRR was found to be a significant outcome of social learning. In the growing urgency of climate uncertainties, social learning theory will be critical in helping design practical and ethical research approaches to DRR that emphasize knowledge sharing, two-way communication, and reflexivity. These will ultimately have enhanced emphasis on behavioral responses to disasters that are complementary to the investments in structural responses

    Research on navigation safety evaluation of Jiaxing Port

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    Remote Sensing of Natural Hazards

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    Each year, natural hazards such as earthquakes, cyclones, flooding, landslides, wildfires, avalanches, volcanic eruption, extreme temperatures, storm surges, drought, etc., result in widespread loss of life, livelihood, and critical infrastructure globally. With the unprecedented growth of the human population, largescale development activities, and changes to the natural environment, the frequency and intensity of extreme natural events and consequent impacts are expected to increase in the future.Technological interventions provide essential provisions for the prevention and mitigation of natural hazards. The data obtained through remote sensing systems with varied spatial, spectral, and temporal resolutions particularly provide prospects for furthering knowledge on spatiotemporal patterns and forecasting of natural hazards. The collection of data using earth observation systems has been valuable for alleviating the adverse effects of natural hazards, especially with their near real-time capabilities for tracking extreme natural events. Remote sensing systems from different platforms also serve as an important decision-support tool for devising response strategies, coordinating rescue operations, and making damage and loss estimations.With these in mind, this book seeks original contributions to the advanced applications of remote sensing and geographic information systems (GIS) techniques in understanding various dimensions of natural hazards through new theory, data products, and robust approaches

    Flood zoning and developing strategies to increase resilience against floods with a crisis management approach

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    Assessment and planning of crisis management with the approach to natural flood disasters include many factors. In this regard, one of the basic principles of crisis management is based on the resilience of urban infrastructure against floods. This study developed strategies to increase resilience by flood zoning and crisis management. The investigation of the current situation shows that despite the efforts being made, the climatic and environmental conditions of the rivers, the settlements of the infiltration basin, the constructions, and the location inaccuracy of the following structures indicate many challenges in managing the current situation in various components of crisis management. In this regard, the main direction of this article is to evaluate the urban resilience of the Khuzestan region against floods based on a crisis management approach and technique for order preference by similarity to ideal solution (TOPSIS) and Fuzzy weighting methods using geographic information system (GIS)

    Hydro-meteorological risk assessment methods and management by nature-based solutions

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    Hydro-meteorological risk (HMR) management involves a range of methods, such as monitoring of uncertain climate, planning and prevention by technical countermeasures, risk assessment, preparedness for risk by early-warnings, spreading knowledge and awareness, response and recovery. To execute HMR management by risk assessment, many models and tools, ranging from conceptual to sophisticated/numerical methods are currently in use. However, there is still a gap in systematically classifying and documenting them in the field of disaster risk management. This paper discusses various methods used for HMR assessment and its management via potential nature-based solutions (NBS), which are actually lessons learnt from nature. We focused on three hydro-meteorological hazards (HMHs), floods, droughts and heatwaves, and their management by relevant NBS. Different methodologies related to the chosen HMHs are considered with respect to exposure, vulnerability and adaptation interaction of the elements at risk. Two widely used methods for flood risk assessment are fuzzy logic (e.g. fuzzy analytic hierarchy process) and probabilistic methodology (e.g. univariate and multivariate probability distributions). Different kinds of indices have been described in the literature to define drought risk, depending upon the type of drought and the purpose of evaluation. For heatwave risk estimation, mapping of the vulnerable property and population-based on geographical information system is a widely used methodology in addition to a number of computational, mathematical and statistical methods, such as principal component analysis, extreme value theorem, functional data analysis, the Ornstein–Uhlenbeck process and meta-analysis. NBS (blue, green and hybrid infrastructures) are promoted for HMR management. For example, marshes and wetlands in place of dams for flood and drought risk reduction, and green infrastructure for urban cooling and combating heatwaves, are potential NBS. More research is needed into risk assessment and management through NBS, to enhance its wider significance for sustainable living, building adaptations and resilience
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