Visual analytics of movement: An overview of methods, tools and procedures

Natalia Andrienko, Gennady Andrienko
2012 Information Visualization  
Analysis of movement is currently a hot research topic in visual analytics. A wide variety of methods and tools for analysis of movement data have been developed in recent years. They allow analysts to look at the data from different perspectives and fulfil diverse analytical tasks. Visual displays and interactive techniques are often combined with computational processing, which, in particular, enables analysis of larger amounts of data than it would be possible with purely visual methods.
more » ... al analytics leverages methods and tools developed in other areas related to data analytics, particularly, statistics, machine learning, and geographic information science. We present an illustrated structured survey of the state of the art in visual analytics concerning the analysis of movement data. Besides reviewing the existing works, we demonstrate by examples how different visual analytics techniques can support understanding of various aspects of movement. LOOKING AT TRAJECTORIES In this section, we consider, first, the techniques for visual representation of trajectories and interaction with the representations, second, the use of clustering methods for comparative studies of multiple trajectories, and, third, the time transformations supporting exploration of temporal properties of trajectories and comparison of dynamic properties of multiple trajectories. Visualizing trajectories The most common types of display for the visualization of movements of discrete entities are static and animated maps [53] [11] and interactive space-time cubes [37][34][32] with linear symbols representing trajectories. These displays as well as some basic interaction techniques are illustrated in Fig. 1 . In Fig. 1A , there is a map with entire trajectories of ships represented by lines drawn with 10% opacity. Small hollow and filled squares mark respectively the start and end positions of
doi:10.1177/1473871612457601 fatcat:qe6fzkgnxbemndzpgryx4jjynm