Spatiotemporal Visual Analysis in Parallel Coordinates Plots (STPCP): Field Trial Studies of Multidimensional Spatiotemporal Data

Visual analysis provides a powerful approach for exploring multidimensional spatiotemporal data, yet it faces significant challenges in simultaneously representing temporal and spatial attributes. A key limitation is the difficulty of visually encoding temporal sequences within geospatial graphics, which often leads to the separate treatment of spatial and temporal visualization methods. To address this issue, we propose an integrated approach that embeds map views into parallel coordinates plots, uses parallel axes to represent temporal sequences, and encodes multidimensional attributes through color channels. This design enables holistic visual analysis of multidimensional spatiotemporal datasets within a single visualization. We evaluated our method through user studies involving datasets from two distinct domains. Results demonstrate that the proposed approach exhibits strong generality and effectively mitigates the limitations associated with separated visualizations of spatial and temporal attributes.