Visual Analysis of Urban Traffic Data based on High-Resolution and High-Dimensional Environmental Sensor Data
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Urbanization is an increasing global trend resulting in a strong increase in public and individual transportation needs. Accordingly, a major challenge for traffic and urban planners is the design of sustainable mobility concepts to maintain and increase the long-term health of humans by reducing environmental pollution. Recent developments in sensor technology allow the precise tracking of vehicle sensor information, allowing a closer and more in-depth analysis of traffic data. We propose a visual analytics system for the exploration of environmental factors in these high-resolution and high-dimensional mobility sensor data. Additionally, we introduce an interactive visual logging approach to enable experts to cope with complex interactive analysis processes and the problem of the reproducibility of results. The usefulness of our approach is demonstrated via two expert studies with two domain experts from the field of environment-related projects and urban traffic planning.
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HÄUSSLER, Johannes, Manuel STEIN, Daniel SEEBACHER, Halldor JANETZKO, Tobias SCHRECK, Daniel A. KEIM, 2018. Visual Analysis of Urban Traffic Data based on High-Resolution and High-Dimensional Environmental Sensor Data. EnvirVis 2018 : Workshop on Visualisation in Environmental Sciences. Brno, Czech Republic, 4. Juni 2018. In: RINK, Karsten, ed. and others. EnvirVis 2018 : Workshop on Visualisation in Environmental Sciences. Goslar: The Eurographics Association, 2018. ISBN 978-3-03868-063-5. Available under: doi: 10.2312/envirvis.20181138BibTex
@inproceedings{Hauler2018Visua-42800, year={2018}, doi={10.2312/envirvis.20181138}, title={Visual Analysis of Urban Traffic Data based on High-Resolution and High-Dimensional Environmental Sensor Data}, isbn={978-3-03868-063-5}, publisher={The Eurographics Association}, address={Goslar}, booktitle={EnvirVis 2018 : Workshop on Visualisation in Environmental Sciences}, editor={Rink, Karsten}, author={Häußler, Johannes and Stein, Manuel and Seebacher, Daniel and Janetzko, Halldor and Schreck, Tobias and Keim, Daniel A.} }
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