Abstract
Widespread availability of location aware devices (such as GPS receivers) promotes capture of detailed movement trajectories of people, animals, vehicles and other moving objects, opening new options for a better understanding of the processes involved. In this paper we investigate spatio-temporal movement patterns in large tracking data sets. We present a natural definition of the pattern ‘one object is leading others’, which is based on behavioural patterns discussed in the behavioural ecology literature. Such leadership patterns can be characterised by a minimum time length for which they have to exist and by a minimum number of entities involved in the pattern. Furthermore, we distinguish two models (discrete and continuous) of the time axis for which patterns can start and end. For all variants of these leadership patterns, we describe algorithms for their detection, given the trajectories of a group of moving entities. A theoretical analysis as well as experiments show that these algorithms efficiently report leadership patterns.
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Notes
Java was chosen because this increases the platform independence and it makes it easier to integrate the code into an existing larger framework.
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Acknowledgements
Patrick Laube was partially supported by ARC Discovery grant DPDP0662906. National ICT Australia is funded through the Australian Government’s Backing Australia’s Ability initiative, in part through the Australian Research Council. The authors wish to thank Karin Schütz, AgResearch Ruakura, Hamilton, New Zealand for valuable comments on animal movement patterns, Bojan Djordjevic for implementing the algorithms and the anonymous reviewers of this and earlier versions of this article.
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Andersson, M., Gudmundsson, J., Laube, P. et al. Reporting Leaders and Followers among Trajectories of Moving Point Objects. Geoinformatica 12, 497–528 (2008). https://doi.org/10.1007/s10707-007-0037-9
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DOI: https://doi.org/10.1007/s10707-007-0037-9