Anastasia Moumtzidou, Marios Bakratsas, Stelios Andreadis, Anastasios Karakostas, Ilias Gialampoukidis, Stefanos Vrochidis, et al. (2020). Flood detection with Sentinel-2 satellite images in crisis management systems. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 1049–1059). Blacksburg, VA (USA): Virginia Tech.
Abstract: The increasing amount of falling rain may cause several problems especially in urban areas, which drainage system can often not handle this large amount in a short time. Confirming a flooded scene in a timely manner can help the authorities to take further actions to counter the crisis event or to get prepared for future relevant incidents. This paper studies the detection of flood events comparing two successive in time Sentinel-2 images, a method that can be extended for detecting floods in a time-series. For the flood detection, fine-tuned pre-trained Deep Convolutional Neural Networks are used, testing as input different sets of three water sensitive satellite bands. The proposed approach is evaluated against different change detection baseline methods, based on remote sensing. Experiments showed that the proposed method with the augmentation technique applied, improved significantly the performance of the neural network, resulting to an F-Score of 62% compared to 22% of the traditional remote sensing techniques. The proposed method supports the crisis management authority to better estimate and evaluate the flood impact.
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Sérgio Freire, Daniele Ehrlich, & Stefano Ferri. (2014). Assessing temporal changes in global population exposure and impacts from earthquakes. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 324–328). University Park, PA: The Pennsylvania State University.
Abstract: It is frequently conveyed, especially in the media, an idea of “increasing impact of natural hazards” typically attributed to their rising frequency and/or growing vulnerability of populations. However, for certain hazard types, this may be mostly a result of increasing population exposure due to phenomenal global population growth, especially in the most hazardous areas. We investigate temporal changes in potential global population exposure and impacts from earthquakes in the XXth century. Spatial analysis is used to combine historical population distributions with a seismic intensity map. Changes in number of victims were also analyzed, while controlling for the progress in frequency and magnitude of hazard events. There is also a focus on mega-cities and implications of fast urbanization for exposure and risk. Results illustrate the relevance of population growth and exposure for risk assessment and disaster outcome, and underline the need for conducting detailed global mapping of settlements and population distribution.
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Dennis J. King. (2006). VISTA-a visualization analysis tool for humanitarian situational awareness. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 11–16). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: The US Department of State's Humanitarian Information Unit (HIU) is developing a new product and web-based visualization analysis tool, known as VISTA (Visualized Information & Synthesized Temporal Analysis). VISTA displays geo-spatial, temporal, numerical/graphic data and textual information, all in one product or via a web interface. VISTA is primarily intended for use by decision-makers, analysts, desk/project officers, and others to provide up-to-date common operating picture ie a vista about an emergency, issue or project.
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Babajide Osatuyi, & Michael J. Chumer. (2010). An empirical investigation of alert notifications: A temporal analysis approach. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: As the deployment of situational awareness mechanisms such as geothermal sensors, use of social network sites, and information and communication technologies (e.g., cell phones) become increasingly widespread to emergency responders, the problem of alert analysis has become very important. Broadcast of large amounts of alerts sent back to command centers for processing may impair the ability of analysts to connect dots that may otherwise adequately enable them to make informed decisions in a timely fashion. This paper investigates trends and patterns embedded in alert notifications generated over a given period of time in order to uncover correlations that may exist in the data. Data for this study are obtained from the National Center for Crisis and Continuity Coordination (NC4). We employ classical time series analysis to understand, explain and predict trends and patterns in the data. This work presents results obtained thus far in the quest for the effect of passage of time on alert patterns. Implications of this work in practice and research are discussed.
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Sérgio Freire, Aneta Florczyk, & Martino Pesaresi. (2016). New Multi-temporal Global Population Grids ? Application to Volcanism. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Better and finer global analyses of human exposure and risk of natural disasters require improved geoinformation on population distribution and densities, in particular concerning temporal and spatial resolution and capacity for change assessment. This paper presents the development of new multi-temporal global population grids and illustrates their value in the context of risk analysis by estimating the worldwide distribution of population in relation to recent volcanism. Results indicate that almost 6% of the world?s 2015 population lived within 100 km of a volcano with at least one significant eruption, and more than 12% within 100 km of a Holocene volcano, with human concentrations in this zone increasing since 1990 above the global population change rate. The novel 250-m resolution population grids constitute the new state-of-the-art in terms of global geospatial population data, with the potential to advance modeling and analyses at all stages of the emergency management cycle.
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