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Timothy Clark, & Rich Curran. (2013). Geospatial site suitability modeling for US department of defense humanitarian assistance projects. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 463–467). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The purpose of this paper is to outline the requirement for data-driven methods for determining optimal geographic locations of United States Department of Defense (DOD) Humanitarian Assistance (HA) resources, including disaster mitigation and preparedness projects. HA project managers and tactical implementers charged with cost-efficient deployment of HA resources are challenged to produce measurable effects, in addition to contributing to broader Joint and Interagency-informed security assistance strategies. To address these issues, our ongoing research advocates geospatial multi-criteria site suitability decision support capabilities that leverage 1) existing geospatial resource location-allocation methodology as applied in government, retail, and commercial sectors; 2) user-generated criteria and objective preferences applied in widely-used decision frameworks; 3) assessments of the feasibility of obtaining data at a geographic scale where DOD tactical/operational level users can benefit from the model outputs; and 4) social science theory related to the HA domain criteria that form the foundation of potential decision models.
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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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Marius J. Paulikas, Andrew Curtis, & Thomas Veldman. (2014). Spatial video street-scale damage assessment of the Washington, Illinois Tornado of 2013. 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. 329–333). University Park, PA: The Pennsylvania State University.
Abstract: This paper advances a growing body of mobile mapping work which captures building scale tornado damage in order to reveal vulnerabilities, or protections, within an otherwise apparently homogenous damage path. The hope is to find how micro geography, or built environment structure patterning might lead to policy advances with regards to rebuilding of critical infrastructure in tornado prone areas. This paper will use spatially encoded video to record damage patterns for the Washington, Illinois tornado of November 17, 2013. What makes this event notable is the location and time of year which can be considered outside the norm. Individual building damage data are coded using the Tornado Injury Scale (TIS) and then analyzed using two forms of local area spatial analysis – a Getis-Ord (Gi) z-score analysis to identify hotspots of damage, and a Local Moran's I to identify building outliers within hotspots.
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