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Attribute trajectory analysis : a framework to analyse attribute changes using trajectory analysis techniques

Long Zhang (UGent) and Nico Van de Weghe (UGent)
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Abstract
Trajectory analysis has attracted growing attention in the research field of geography. Beyond traditional moving object trajectories, another type of trajectory exists in which the coordinates are object attributes rather than geographical coordinates. In this paper, a framework to analyse these so-called attribute trajectories is proposed that uses four techniques typically employed in the analysis of moving object trajectories: the Reeb graph, the similarity matrix, the convoy and the mega-convoy. The Reeb graph provides the ability to visualise the temporal dynamics of attribute similarities. The similarity matrix is a supplement of the Reeb graph whose purpose is to visualise the pairwise similarities among the attributes. Moreover, the similarity matrix forms a basis for clustering. The convoy highlights objects whose attributes remain similar for a sufficiently long period. The mega-convoy reduces the number of convoys and reveals their evolutionary histories by merging overlapping convoys. A small real-world meteorological dataset is used as an example to illustrate the attribute trajectory analysis framework and the techniques. This paper aims to form a starting point for applying trajectory analysis techniques in many research fields.
Keywords
LAND-COVER-CHANGE, CHANGE-VECTOR ANALYSIS, MOVING POINT OBJECTS, CLUSTER-ANALYSIS, PATTERN-ANALYSIS, FLOCK PATTERNS, CLIMATE ZONES, SPACE, CHINA, Attribute trajectory, Reeb graph, similarity matrix, convoy, mega-convoy

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Please use this url to cite or link to this publication:

Chicago
Zhang, Long, and Nico Van de Weghe. 2018. “Attribute Trajectory Analysis : a Framework to Analyse Attribute Changes Using Trajectory Analysis Techniques.” International Journal of Geographical Information Science 32 (5): 1043–1059.
APA
Zhang, Long, & Van de Weghe, N. (2018). Attribute trajectory analysis : a framework to analyse attribute changes using trajectory analysis techniques. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 32(5), 1043–1059.
Vancouver
1.
Zhang L, Van de Weghe N. Attribute trajectory analysis : a framework to analyse attribute changes using trajectory analysis techniques. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE. 2018;32(5):1043–59.
MLA
Zhang, Long, and Nico Van de Weghe. “Attribute Trajectory Analysis : a Framework to Analyse Attribute Changes Using Trajectory Analysis Techniques.” INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE 32.5 (2018): 1043–1059. Print.
@article{8561383,
  abstract     = {Trajectory analysis has attracted growing attention in the research field of geography. Beyond traditional moving object trajectories, another type of trajectory exists in which the coordinates are object attributes rather than geographical coordinates. In this paper, a framework to analyse these so-called attribute trajectories is proposed that uses four techniques typically employed in the analysis of moving object trajectories: the Reeb graph, the similarity matrix, the convoy and the mega-convoy. The Reeb graph provides the ability to visualise the temporal dynamics of attribute similarities. The similarity matrix is a supplement of the Reeb graph whose purpose is to visualise the pairwise similarities among the attributes. Moreover, the similarity matrix forms a basis for clustering. The convoy highlights objects whose attributes remain similar for a sufficiently long period. The mega-convoy reduces the number of convoys and reveals their evolutionary histories by merging overlapping convoys. A small real-world meteorological dataset is used as an example to illustrate the attribute trajectory analysis framework and the techniques. This paper aims to form a starting point for applying trajectory analysis techniques in many research fields.},
  author       = {Zhang, Long and Van de Weghe, Nico},
  issn         = {1365-8816},
  journal      = {INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE},
  language     = {eng},
  number       = {5},
  pages        = {1043--1059},
  title        = {Attribute trajectory analysis : a framework to analyse attribute changes using trajectory analysis techniques},
  url          = {http://dx.doi.org/10.1080/13658816.2018.1435885},
  volume       = {32},
  year         = {2018},
}

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