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Christoph Aubrecht, Klaus Steinnocher, & Hermann Huber. (2014). DynaPop – Population distribution dynamics as basis for social impact evaluation in crisis management. 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. 314–318). University Park, PA: The Pennsylvania State University.
Abstract: In this paper ongoing developments regarding the conceptual setup and subsequent implementation logic of a seamless spatio-temporal population dynamics model are presented. The DynaPop model aims at serving as basic input for social impact evaluation in crisis management. In addition to providing the starting point for assessing population exposure dynamics, i.e. the location and number of affected people at different stages during an event, knowledge of spatio-temporal population distribution patterns is also considered crucial for a set of other related aspects in disaster risk and crisis management including evacuation planning and casualty assessment. DynaPop is implemented via a gridded spatial disaggregation approach and integrates previous efforts on spatio-temporal modeling that account for various aspects of population dynamics such as human mobility and activity patterns that are particularly relevant in picturing the highly dynamic daytime situation.
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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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Sérgio Freire, & Christoph Aubrecht. (2011). Assessing spatio-temporal population exposure to tsunami hazard in the Lisbon Metropolitan Area. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The coastal region of Lisbon, Portugal, is potentially subject to tsunami hazard. Mapping and assessing tsunami risk requires giving adequate consideration to the population exposure. In the present work we model and map the spatio-temporal distribution of population in the daily cycle and analyze it with a tsunami hazard map to better assess tsunami risk in the Lisbon Metropolitan Area. New high-resolution daytime and nighttime population distribution surfaces are developed using 'intelligent dasymetric mapping' to combine best-available census data and statistics with land use and land cover data. Mobility statistics are considered for mapping daytime distribution. Finally, the population distribution maps are combined with the Tsunami Inundation Susceptibility map to assess potential human exposure to tsunami in daytime and nighttime periods. Results show that a significant amount of population is potentially at risk, and its numbers increase from nighttime to daytime, especially in the zones of high susceptibility.
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Sérgio Freire, Christoph Aubrecht, & Stephanie Wegscheider. (2012). When the tsunami comes to town – Improving evacuation modeling by integrating high-resolution population exposure. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Tsunamis are a major risk for Lisbon (Portugal) coastal areas whose impacts can be extremely high, as confirmed by the past occurrence of major events. For correct risk assessment and awareness and for implementing mitigation measures, detailed simulation of exposure and evacuation is essential. This work uses a spatial modeling approach for estimating residential population distribution and exposure to tsunami flooding by individual building, and for simulating their evacuation travel time considering horizontal and vertical displacement. Results include finer evaluation of exposure to, and evacuation from, a potential tsunami, considering the specific inundation depth and building's height. This more detailed and accurate modeling of exposure to and evacuation from a potential tsunami can benefit risk assessment and contribute to more efficient Crisis Response and Management. © 2012 ISCRAM.
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Sérgio Freire, Aneta Florczyk, & Stefano Ferri. (2015). Modeling Day- and Nighttime Population Exposure at High Resolution: Application to Volcanic Risk Assessment in Campi Flegrei. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: Improving analyses of population exposure to potential natural hazards, especially sudden ones, requires more detailed geodemographic data. Availability of such information for large areas is limited by specific database requirements and their cost.
This paper introduces and tests a new approach for refining spatio-temporal population distribution at high resolution by combining diverse geoinformation layers. Its value is demonstrated in the context of disaster risk analysis and emergency management by using the data in a real volcanic risk scenario in Campi Flegrei, located within the metropolitan area of Naples, Italy. Results show that there is significant variation in exposure from nighttime to daytime in the study area.
The proposed modeling approach can be applied and customized for other metropolitan areas, ultimately benefiting disaster risk assessment and mitigation.
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