Scalable Detection of Spatiotemporal Encounters in Historical Movement Data
Computer Graphics Forum
Evaluation of the visibility of vessel movement features in trajectory visualizations
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
Detecting movement patterns using Brownian bridges
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Visualizing interchange patterns in massive movement data
EuroVis '13 Proceedings of the 15th Eurographics Conference on Visualization
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We present a method to interactively explore multiple attributes in trajectory data using density maps, i.e., images that show an aggregate overview of massive amounts of data. So far, density maps have mainly been used to visualize single attributes. Density maps are created in a two-way procedure; first smoothed trajectories are aggregated in a density field, and then the density field is visualized. In our approach, the user can explore attributes along trajectories by calculating a density field for multiple subsets of the data. These density fields are then either combined into a new density field or first visualized and then combined. Using a widget, called a distribution map, the user can interactively define subsets in an effective and intuitive way, and, supported by high-end graphics hardware the user gets fast feedback for these computationally expensive density field calculations. We show the versatility of our method with use cases in the maritime domain: to distinguish between periods in the temporal aggregation, to find anomalously behaving vessels, to solve ambiguities in density maps via drill down in the data, and for risk assessments. Given the generic framework and the lack of domain-specific assumptions, we expect our concept to be applicable for trajectories in other domains as well.