Does animation in user interfaces improve decision making?
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
International Journal of Human-Computer Studies - Special issue: Interactive graphical communication
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IEEE Transactions on Visualization and Computer Graphics
Effectiveness of Animation in Trend Visualization
IEEE Transactions on Visualization and Computer Graphics
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An Evaluation of Space Time Cube Representation of Spatiotemporal Patterns
IEEE Transactions on Visualization and Computer Graphics
Activities, ringmaps and geovisualization of large human movement fields
Information Visualization
Towards a taxonomy of movement patterns
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Spatiotemporal Analysis of Sensor Logs using Growth Ring Maps
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IEEE Transactions on Visualization and Computer Graphics
Space-time density of trajectories: exploring spatio-temporal patterns in movement data
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An integrated approach for visual analysis of a multisource moving objects knowledge base
International Journal of Geographical Information Science - Geospatial Visual Analytics: Focus on Time Special Issue of the ICA Commission on GeoVisualization
Different levels of 3D: an evaluation of visualized discrete spatiotemporal data in space-time cubes
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2D and 3D representations for feature recognition in time geographical diary data
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Interactive visualization of multivariate trajectory data with density maps
PACIFICVIS '11 Proceedings of the 2011 IEEE Pacific Visualization Symposium
Generating color palettes using intuitive parameters
EuroVis'08 Proceedings of the 10th Joint Eurographics / IEEE - VGTC conference on Visualization
Visualisation of sensor data from animal movement
EuroVis'09 Proceedings of the 11th Eurographics / IEEE - VGTC conference on Visualization
Visualization of vessel movements
EuroVis'09 Proceedings of the 11th Eurographics / IEEE - VGTC conference on Visualization
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There are many visualizations that show the trajectory of a moving object to obtain insights in its behavior. In this user study, we test the performance of three of these visualizations with respect to three movement features that occur in vessel behavior. Our goal is to compare the recently presented vessel density by Willems et al. [WvdWvW09] with well-known trajectory visualizations such as an animation of moving dots and the space-time cube. We test these visualizations with common maritime analysis tasks by investigating the ability of users to find stopping objects, fast moving objects, and estimate the busiest routes in vessel trajectories. We test the robustness of the visualizations towards scalability and the influence of complex trajectories using small-scale synthetic data sets. The performance is measured in terms of correctness and response time. The user test shows that each visualization type excels for correctness for a specific movement feature. Vessel density performs best for finding stopping objects, but does not perform significantly less than the remaining visualizations for the other features. Therefore, vessel density is a nice extension in the toolkit for analyzing trajectories of moving objects, in particular for vessel movements, since stops can be visualized better, and the performance for comparing lanes and finding fast movers is at a similar level as established trajectory visualizations.