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Journal of Visualization

Erschienen in:

05.01.2018 | Regular Paper

M3: visual exploration of spatial relationships between flight trajectories

verfasst von: Hutong Wu, Shicao Jia, Jinsong Wang, Jiawan Zhang

Erschienen in: Journal of Visualization | Ausgabe 3/2018

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Abstract

Outlier detection and clustering are important to analyze trajectory. While many algorithms have been developed to tackle these issues, they lack the combination with visualization to enable the involvement of human intelligence during the analyzing process. We propose a visual framework called M3, which combines data mining algorithms with visualization technique through three coordinated views: Map, MST, and FSDMatrix. Map view displays the spatial information of trajectories. MST is a minimum spanning tree, which presents the relationships between trajectories. In MST, each node represents a trajectory; edges between nodes denote the Fréchet distance between trajectories. FSDMatrix shows a matrix of pairwise Free Space Diagram to assist in detecting outliers and clustering trajectories. The three views are interacted with each other. Through case studies, we discuss the applicability of our framework and demonstrate the convenience brought by it.

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Vorheriger Artikel FeatureNet: automatic visual summarization of major features in multivariate volume data

Nächster Artikel VAUT: a visual analytics system of spatiotemporal urban topics in reviews

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Titel: M3: visual exploration of spatial relationships between flight trajectories
verfasst von: Hutong Wu
Shicao Jia
Jinsong Wang
Jiawan Zhang
Publikationsdatum: 05.01.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Journal of Visualization / Ausgabe 3/2018
Print ISSN: 1343-8875
Elektronische ISSN: 1875-8975
DOI: https://doi.org/10.1007/s12650-017-0471-1

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