Visual analytics of delays and interaction in movement data. Issue 2 (1st February 2017)

• Record Type: Journal Article
• Authors: Konzack, Maximilian; McKetterick, Thomas; Ophelders, Tim; Buchin, Maike; Giuggioli, Luca; Long, Jed; Nelson, Trisalyn; Westenberg, Michel A.; Buchin, Kevin
• Is Part Of: International journal of geographical information science. Volume 31:Issue 2(2017)
• Page Start: 320
• Page End: 345
• Publication Date: 2017-02-01
• Subjects: Trajectory analysis -- visual analytics -- similarity measures; Geography -- Data processing -- Periodicals; Information storage and retrieval systems -- Periodicals; Géomatique -- Périodiques; Systèmes d'information -- Périodiques; 910.285
• DOI: 10.1080/13658816.2016.1199806
• Languages: English
• ISSNs: 1365-8816

Abstract

ABSTRACT: The analysis of interaction between movement trajectories is of interest for various domains when movement of multiple objects is concerned. Interaction often includes a delayed response, making it difficult to detect interaction with current methods that compare movement at specific time intervals. We propose analyses and visualizations, on a local and global scale, of delayed movement responses, where an action is followed by a reaction over time, on trajectories recorded simultaneously. We developed a novel approach to compute the global delay in subquadratic time using a fast Fourier transform (FFT). Central to our local analysis of delays is the computation of a matching between the trajectories in a so-called delay space . It encodes the similarities between all pairs of points of the trajectories. In the visualization, the edges of the matching are bundled into patches, such that shape and color of a patch help to encode changes in an interaction pattern. To evaluate our approach experimentally, we have implemented it as a prototype visual analytics tool and have applied the tool on three bidimensional data sets. For this we used various measures to compute the delay space, including the directional distance, a new similarity measure, which captures more complex interactions by combining directional and spatial characteristics. We compare matchings of various methods computing similarity between trajectories. We also compare various procedures to compute the matching in the delay space, specifically the Fréchet distance, dynamic time warping (DTW), and edit distance (ED). Finally, we demonstrate how to validate the consistency of pairwise matchings by computing matchings between more than two trajectories.