BigGIS Prädiktive und präskriptive Geoinformationssysteme basierend auf hochdimensionalen geo-temporalen Datenstrukturen

Institutions
  • FB Informatik und Informationswissenschaft
Publications
  Seebacher, Daniel; Häußler, Johannes; Hundt, Michael; Stein, Manuel; Müller, Hannes; Engelke, Ulrich; Keim, Daniel(2018): Visual Analysis of Spatio-Temporal Event Predictions : Investigating the Spread Dynamics of Invasive Species IEEE Transactions on Big Data ; 2018. - ISSN 2372-2096. - eISSN 2332-7790

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

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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 the occurrence of D. suzukii 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 the occurrence of 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 predictions, enabling the investigation of the spread dynamics of invasive species. We demonstrate the usefulness of our approach in three use cases and an evaluation with more than 30 domain experts.

Origin (projects)

Funding sources
NameProject no.DescriptionPeriod
Bundesministerium für Bildung und Forschung562/15no information
Further information
Period: 01.03.2015 – 31.03.2018