Publikation: Visualising the Invisible : Exploring Approaches for Visual Analysis of Dynamic Airflow in Geographic Environments Using Sensor Data
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Measuring, modelling, and visualising dynamics of fluids, in particular air and water flow, are important in many applications, including engineering, biology, meteorology, and sports. While there are established models of airflow in controlled conditions, we are lacking an understanding of the distinct airflows in natural environments, whose characteristics are highly influential for all forms of aerial activities. There is little data available for fine-scale analysis and representation of airflow outside the lab without the help of sophisticated and laborious airflow measurements. Here, we explore ways to exploit movement data of flying agents for this purpose, propose an approach to model and visualise thermal dynamics as a discrete localised airflow, and demonstrate our approach using data collected from paraglider pilots.
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ZHANG, Ying, Hannah J. WILLIAMS, Falk SCHREIBER, Karsten KLEIN, 2024. Visualising the Invisible : Exploring Approaches for Visual Analysis of Dynamic Airflow in Geographic Environments Using Sensor Data. EuroVA2024 - 15th International Workshop on Visual Analytics. Dänemark, 27. Mai 2024. In: EL-ASSADY, Mennatallah, Hrsg., Hans-Jörg SCHULZ, Hrsg.. Proceedings of the EuroVis Workshop on Visual Analytics 2024. Eindhoven: The Eurographics Association, 2024, 20241117. EuroVis Workshop on Visual Analytics (EuroVA). ISBN 978-3-03868-253-0. Verfügbar unter: doi: 10.2312/eurova.20241117BibTex
@inproceedings{Zhang2024Visua-70028, year={2024}, doi={10.2312/eurova.20241117}, title={Visualising the Invisible : Exploring Approaches for Visual Analysis of Dynamic Airflow in Geographic Environments Using Sensor Data}, url={https://diglib.eg.org/handle/10.2312/eurova20241117}, isbn={978-3-03868-253-0}, publisher={The Eurographics Association}, address={Eindhoven}, series={EuroVis Workshop on Visual Analytics (EuroVA)}, booktitle={Proceedings of the EuroVis Workshop on Visual Analytics 2024}, editor={El-Assady, Mennatallah and Schulz, Hans-Jörg}, author={Zhang, Ying and Williams, Hannah J. and Schreiber, Falk and Klein, Karsten}, note={Article Number: 20241117} }
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