Visual Analysis of Spatio-Temporal Event Predictions : Investigating the Spread Dynamics of Invasive Species

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2017
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Symposium on Visualization in Data Science (VDS) at IEEE VIS 2017
Abstract
Invasive species are a major cause of ecological damage and commercial losses. A current problem spreading in North America and Europe is the vinegar fly Drosophila suzukii. Unlike other Drosophila, it infests non-rotting and healthy fruits and is therefore of concern to fruit growers, such as vintners. Consequently, large amounts of data about infestations have been collected in recent years. However, there is a lack of interactive methods to investigate this data. We employ ensemble-based classification to predict areas susceptible to infestation by D. suzukii and bring them into a spatio-temporal context using maps and glyph-based visualizations. Following the information-seeking mantra, we provide a visual analysis system Drosophigator for spatio-temporal event prediction, enabling the investigation of the spread dynamics of invasive species. We demonstrate the usefulness of this approach in two use cases.
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004 Computer Science
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2017 IEEE Visualization Conference (VIS), Oct 1, 2017 - Oct 6, 2017, Phoenix, Arizona, USA
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Cite This
ISO 690SEEBACHER, Daniel, Johannes HÄUSSLER, Michael HUNDT, Manuel STEIN, Hannes MÜLLER, Ulrich ENGELKE, Daniel A. KEIM, 2017. Visual Analysis of Spatio-Temporal Event Predictions : Investigating the Spread Dynamics of Invasive Species. 2017 IEEE Visualization Conference (VIS). Phoenix, Arizona, USA, Oct 1, 2017 - Oct 6, 2017. In: Symposium on Visualization in Data Science (VDS) at IEEE VIS 2017
BibTex
@inproceedings{Seebacher2017Visua-41756,
  year={2017},
  title={Visual Analysis of Spatio-Temporal Event Predictions : Investigating the Spread Dynamics of Invasive Species},
  booktitle={Symposium on Visualization in Data Science (VDS) at IEEE VIS 2017},
  author={Seebacher, Daniel and Häußler, Johannes and Hundt, Michael and Stein, Manuel and Müller, Hannes and Engelke, Ulrich and Keim, Daniel A.}
}
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