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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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
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