Interactive Spatiotemporal Visualization for Understanding the Spread of Invasive Species

Abstract

Invasive species pose serious threats to ecosystems and economies, yet common Geographic Information Systems (GIS) struggle to show how invasions unfold through time and space. We present an interactive decision-support system that integrates first-detection chronology, local directional structure, and global linkages with contextual overlays. The design follows geovisual analytics principles and leverages cognitive-fit by matching tasks (chronology, direction, linkage) to encodings (heatmap, rays, arrows), complementing static maps and traditional GIS. The tool enables users to identify invasion centers, explore both local and global spread patterns, and overlay terrain and highway networks for contextual insight. We demonstrate the approach on four forest pests in the eastern United States using county-level first-detection records (1905–2020). A qualitative evaluation with three domain experts found the interface clear and useful for exploratory analysis; feedback informed planned improvements for interaction cues, accessibility, and edit transparency.