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

TL;DR

This paper introduces Drosophigator, a visual analysis system that uses ensemble classification and glyph-based visualizations to explore and understand the spread dynamics of invasive species like Drosophila suzukii.

Contribution

The paper presents a novel interactive visual analysis system for investigating spatio-temporal data of invasive species infestations, integrating ensemble classification with glyph-based visualizations.

Findings

Effective visualization of infestation spread dynamics.

Successful application in two real-world use cases.

Enhanced understanding of invasive species spread patterns.

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.