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Grand Challenges in Computational Movement Analysis

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Abstract

This final chapter addresses the prospect of Computational Movement Analysis (CMA) as a relatively young research field. The first decade of CMA was shaped by significant technological developments resulting in much increased availability of fine-grained movement data, an innocent and somewhat naïve enthusiasm over moving points resulting in a wide but fragmented variety of methods for movement analysis, and finally due to this lack of a unifying theory of CMA only moderate success in overcoming GIS’ and GIScience’ legacy of static cartography. The final chapter concludes this book by proposing a set of grand challenges of CMA.

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Notes

  1. 1.

    Dagstuhl Seminars #08451 (2008), #10491 (2010) #12512 (2012), on Representation, Analysis and Visualization of Moving Objects; First Workshop on Movement Pattern Analysis (MPA’10), 09/2010, Zurich, Switzerland; Workshop on Analysis and Visualization of Moving Objects, Lorentz Centre, 06/2011, Leiden, NL; Workshop on Progress in Movement Analysis—Experiences with Real Data, 09/2012, University of Zurich, Switzerland.

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Correspondence to Patrick Laube .

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Laube, P. (2014). Grand Challenges in Computational Movement Analysis. In: Computational Movement Analysis. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-10268-9_5

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  • DOI: https://doi.org/10.1007/978-3-319-10268-9_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10267-2

  • Online ISBN: 978-3-319-10268-9

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