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International Conference on Geographic Information Science

GIScience 2010: Geographic Information Science pp 16–26Cite as

Time-Geographic Density Estimation for Moving Point Objects

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6292))

Abstract

This research presents a time-geographic method of density estimation for moving point objects. The approach integrates traditional kernel density estimation (KDE) with techniques of time geography to generate a continuous intensity surface that characterises the spatial distribution of a moving object over a fixed time frame. This task is accomplished by computing density estimates as a function of a geo-ellipse generated for each consecutive pair of control points in the object’s space-time path and summing those values at each location in a manner similar to KDE. The main advantages of this approach are: (1) that positive intensities are only assigned to locations within a moving object’s potential path area and (2) that it avoids arbitrary parameter selection as the amount of smoothing is controlled by the object’s maximum potential velocity. The time-geographic density estimation technique is illustrated with a sample dataset, and a discussion of limitations and future work is provided.

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Author information

Authors and Affiliations

  1. Department of Geography, University of South Florida, Tampa, FL, USA

    Joni A. Downs

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  1. Joni A. Downs
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Editor information

Editors and Affiliations

  1. University of Zurich, 8057, Zurich, Switzerland

    Sara Irina Fabrikant  & Tumasch Reichenbacher  & 

  2. Utrecht University, 3508, Utrecht, The Netherlands

    Marc van Kreveld

  3. University of Bamberg, 96047, Bamberg, Germany

    Christoph Schlieder

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© 2010 Springer-Verlag Berlin Heidelberg

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Downs, J.A. (2010). Time-Geographic Density Estimation for Moving Point Objects. In: Fabrikant, S.I., Reichenbacher, T., van Kreveld, M., Schlieder, C. (eds) Geographic Information Science. GIScience 2010. Lecture Notes in Computer Science, vol 6292. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15300-6_2

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  • DOI: https://doi.org/10.1007/978-3-642-15300-6_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15299-3

  • Online ISBN: 978-3-642-15300-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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