Efficient summarization of spatiotemporal events

Authors:
Peggy Agouris;Anthony Stefanidis
Affiliations:
University of Maine, Orono;University of Maine, Orono
Venue:
Communications of the ACM
Year:
2003

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Abstract

Raster datasets at discrete temporal instances capture a variety of spatiotemporal phenomena. These phenomena and the respective datasets that capture them may span various spatial and temporal scales, like a car's trajectory as it is captured by various cameras at video rates, or the long-term erosion of a river's edge captured by an annual series of aerial imagery.