Time-Geographic Density Estimation for Moving Point Objects

  • Joni A. Downs
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6292)


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.


time geography moving objects density estimation point pattern analysis 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Joni A. Downs
    • 1
  1. 1.Department of GeographyUniversity of South FloridaTampaUSA

Personalised recommendations