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The Annual International Conference on Geographic Information Science

GIScience 2016: Geographic Information Science pp 34–47Cite as

Hierarchical Prism Trees for Scalable Time Geographic Analysis

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9927))

Abstract

As location-aware applications and location-based services continue to increase in popularity, data sources describing a range of dynamic processes occurring in near real-time over multiple spatial and temporal scales are becoming the norm. At the same time, existing frameworks useful for understanding these dynamic spatio-temporal data, such as time geography, are unable to scale to the high volume, velocity, and variety of these emerging data sources. In this paper, we introduce a computational framework that turns time geography into a scalable analysis tool that can handle large and rapidly changing datasets. The Hierarchical Prism Tree (HPT) is a dynamic data structure for fast queries on spatio-temporal objects based on time geographic principles and theories, which takes advantage of recent advances in moving object databases and computer graphics. We demonstrate the utility of our proposed HPT using two common time geography tasks (finding similar trajectories and mapping potential space-time interactions), taking advantage of open data on space-time vehicle emissions from the EnviroCar platform.

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Notes

  1. 1.

    Although some parallel versions of kd-trees [35] do show promise.

  2. 2.

    See for example, http://www.realtimerendering.com/intersections.html.

  3. 3.

    https://www.envirocar.org.

  4. 4.

    http://www.obdii.com/background.html.

  5. 5.

    ICARUS analyzes the migratory behavior of animals such as birds and bats:

    http://icarusinitiative.org.

  6. 6.

    Argos is a global, satellite-based platform widely used in animal tracking:

    http://www.argos-system.org/.

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Author information

Authors and Affiliations

  1. Geography Department, University of Colorado at Boulder, Boulder, CO, USA

    Carson J. Q. Farmer

  2. Department of Development and Planning, Aalborg University Copenhagen, Copenhagen, Denmark

    Carsten Keßler

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  1. Carson J. Q. Farmer
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Correspondence to Carson J. Q. Farmer .

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Editors and Affiliations

  1. University of Texas at Austin , Austin, Texas, USA

    Jennifer A. Miller

  2. University of California at Berkeley , Berkeley, California, USA

    David O'Sullivan

  3. University of Wisconsin-Madison , Madison, Wisconsin, USA

    Nancy Wiegand

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Farmer, C.J.Q., Keßler, C. (2016). Hierarchical Prism Trees for Scalable Time Geographic Analysis. In: Miller, J., O'Sullivan, D., Wiegand, N. (eds) Geographic Information Science. GIScience 2016. Lecture Notes in Computer Science(), vol 9927. Springer, Cham. https://doi.org/10.1007/978-3-319-45738-3_3

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  • DOI: https://doi.org/10.1007/978-3-319-45738-3_3

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