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Abstract: Effective management of infrastructural networks in the case of a crisis requires a prior analysis of the vulnerability of spatial networks and identification of critical locations where an interdiction would cause most damage and disruption. This paper presents a preliminary study into how a graph theoretic structural analysis could be used for this purpose. Centrality measures are combined with a dual graph modelling approach in order to identify critical locations in a spatial network. The results of a case study on a street network of a small area in the city of Helsinki indicate that 'betweenness' is the most promising centrality measure for this purpose. Other measures and properties of graphs are under consideration for eventually developing a risk model not only for one but for a group of co-located spatial networks.

Abstract: “Over the last couple of years, the growing OpenStreetMap (OSM) data base repeatedly proved its potential for various use cases, including disaster management. Disaster mapping activations show increasing contributions, but oftentimes raise questions related to the quality of the provided \emph{Volunteered Geographic Information} (VGI). In order to better monitor and understand OSM mapping and data quality, we developed a software platform that applies big data technology to OSM full history data. OSM full history data monitoring allows detailed analyses of the OSM data evolution and the detection of remarkable patterns over time. This paper illustrates the specific potential of the platform for disaster activations by means of two case studies. Initial results demonstrate that our flexible and scalable platform structure enables fast and easy information extraction and supports mapping processes and data quality assurance.”

Keywords: OpenStreetMap, OpenStreetMap History, Disaster management, Humanitarian OpenStreetMap Team, Street network analyses

Track: Geospatial Technologies and Geographic Information Science for Crisis Management (GIS)

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	Ur?ka Demsar, Olga Patenková, & Kirsi Virrantaus. (2007). Centrality measures and vulnerability of spatial networks. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 201–209). Delft: Information Systems for Crisis Response and Management, ISCRAM. Abstract: Effective management of infrastructural networks in the case of a crisis requires a prior analysis of the vulnerability of spatial networks and identification of critical locations where an interdiction would cause most damage and disruption. This paper presents a preliminary study into how a graph theoretic structural analysis could be used for this purpose. Centrality measures are combined with a dual graph modelling approach in order to identify critical locations in a spatial network. The results of a case study on a street network of a small area in the city of Helsinki indicate that 'betweenness' is the most promising centrality measure for this purpose. Other measures and properties of graphs are under consideration for eventually developing a risk model not only for one but for a group of co-located spatial networks. Keywords: Damage detection; Electric network analysis; Risk assessment; Betweenness; Centrality measures; Critical location; Dual graphs; Effective management; Graph-theoretic; Spatial network; Street network; Graph theory Track: GISC Share to FB \| Save citation: RTF PDF LaTeX \| Export record: Atom XML MODS XML OAI_DC XML ODF XML SRW_DC XML SRW_MODS XML
	Michael Auer, Melanie Eckle, Sascha Fendrich, Luisa Griesbaum, Fabian Kowatsch, Sabrina Marx, et al. (2018). Towards Using the Potential of OpenStreetMap History for Disaster Activation Monitoring. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 317–325). Rochester, NY (USA): Rochester Institute of Technology. Abstract: “Over the last couple of years, the growing OpenStreetMap (OSM) data base repeatedly proved its potential for various use cases, including disaster management. Disaster mapping activations show increasing contributions, but oftentimes raise questions related to the quality of the provided \emph{Volunteered Geographic Information} (VGI). In order to better monitor and understand OSM mapping and data quality, we developed a software platform that applies big data technology to OSM full history data. OSM full history data monitoring allows detailed analyses of the OSM data evolution and the detection of remarkable patterns over time. This paper illustrates the specific potential of the platform for disaster activations by means of two case studies. Initial results demonstrate that our flexible and scalable platform structure enables fast and easy information extraction and supports mapping processes and data quality assurance.” Keywords: OpenStreetMap, OpenStreetMap History, Disaster management, Humanitarian OpenStreetMap Team, Street network analyses Track: Geospatial Technologies and Geographic Information Science for Crisis Management (GIS) Share to FB \| Save citation: RTF PDF LaTeX \| Export record: Atom XML MODS XML OAI_DC XML ODF XML SRW_DC XML SRW_MODS XML