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Towards using the potential of OpenStreetMap history for disaster activation monitoring

Over the last couple of years, the growing OpenStreetMap (OSM) database repeatedly proved its potential for various use cases, including disaster management. Disaster mapping activations show increasing numbers of contributions, but oftentimes raise questions related to the quality of the provided V...

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Bibliographic Details
Main Authors: Auer, Michael (Author) , Eckle, Melanie (Author) , Fendrich, Sascha (Author) , Griesbaum, Luisa (Author) , Kowatsch, Fabian (Author) , Marx, Sabrina (Author) , Raifer, Martin (Author) , Schott, Moritz (Author) , Troilo, Rafael (Author) , Zipf, Alexander (Author)
Format: Chapter/Article Conference Paper
Language:English
Published: 2018
In: 15th International Conference on Information Systems for Crisis Response and Management ISCRAM 2018, Rochester Institute of Technology, Rochester, NY, USA
Year: 2018, Pages: 1-9
Online Access:Verlag, kostenfrei, Volltext: https://idl.iscram.org/files/michaelauer/2018/2110_MichaelAuer_etal2018.pdf
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Author Notes:Michael Auer, Melanie Eckle, Sascha Fendrich, Luisa Griesbaum, Fabian Kowatsch, Sabrina Marx, Martin Raifer, Moritz Schott, Rafael Troilo, Alexander Zipf
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Summary:Over the last couple of years, the growing OpenStreetMap (OSM) database repeatedly proved its potential for various use cases, including disaster management. Disaster mapping activations show increasing numbers of contributions, but oftentimes raise questions related to the quality of the provided Volunteered Geographic Information. In order to better monitor and understand OSM mapping and data quality, we developed the ohsome 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 our 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.
Item Description:Gesehen am 19.02.2026
Physical Description:Online Resource
ISBN:9780692127605

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