Visual Analysis of Spatio-Temporal Event Predictions: Investigating the Spread Dynamics of Invasive Species
This provides an interactive tool for fruit growers and ecologists to investigate invasive species spread, but it is incremental as it applies existing visualization methods to a new domain.
The paper tackles the problem of analyzing spatio-temporal data for invasive species like Drosophila suzukii, which damages fruits, by developing an interactive visual analysis system called Drosophigator that uses ensemble-based classification to predict susceptible areas and visualizes spread dynamics, demonstrating its usefulness in two use cases.
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.