Extracting Movement-based Topics for Analysis of Space Use

Abstract

We present a novel approach to analyze spatio-temporal movement patterns using topic modeling. Our approach represents trajectories as sequences of place visits and moves, applies topic modeling separately to each collection of sequences, and synthesizes results. This supports the identification of dominant topics for both place visits and moves, the exploration of spatial and temporal patterns of movement, enabling understanding of space use. The approach is applied to two real-world data sets of car movements in Milan and UK road traffic, demonstrating the ability to uncover meaningful patterns and insights.