Carolin Klonner, Melanie Eckle, Tomás Usón, & Bernhard Höfle. (2017). Quality Improvement of Remotely Volunteered Geographic Information via Country-Specific Mapping Instructions. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 939–947). Albi, France: Iscram.
Abstract: Volunteered geographic information can be seen as valuable data for various applications such as within disaster management. OpenStreetMap data, for example, are mainly contributed by remote mappers based on satellite imagery and have increasingly been implemented in response actions to various disasters. Yet, the quality often depends on the local and country-specific knowledge of the mappers, which is required for performing the mapping task. Hence, the question is raised whether there is a possibility to train remote mappers with country-specific mapping instructions in order to improve the quality of OpenStreetMap data. An experiment is conducted with Geography students to evaluate the effect of additional material that is provided in wiki format. Furthermore, a questionnaire is applied to collect participants' socio-demographic information, mapping experience and feedback about the material. This pre-study gives hints for future designs of country-specific mapping instructions as well as the experiment design itself.
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Josiane Rodrigues Eugênio, Lutiane Queiroz de Almeida, & Vinnícius Vale Dionízio França. (2016). Disaster risk indicators in Brazil: a case study in Rio Grande do Norte State. 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: The following paper provides a tool to help evaluate, visualize and communicate different levels of exposure, vulnerability and risk at a regional level in BrazilKeywords. The indices show that social vulnerability is a determining factor for high disaster risk values.
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