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Discovering shared segments on the migration route of the bar-headed goose by time-based plane-sweeping trajectory clustering
Journal of Information and Computational Science
By: Ze Luo, Yan Baoping, John Y. Takekawa, and Diann J. Prosser
We propose a new method to help ornithologists and ecologists discover shared segments on the migratory pathway of the bar-headed geese by time-based plane-sweeping trajectory clustering. We present a density-based time parameterized line segment clustering algorithm, which extends traditional comparable clustering algorithms from temporal and spatial dimensions. We present a time-based plane-sweeping trajectory clustering algorithm to reveal the dynamic evolution of spatial-temporal object clusters and discover common motion patterns of bar-headed geese in the process of migration. Experiments are performed on GPS-based satellite telemetry data from bar-headed geese and results demonstrate our algorithms can correctly discover shared segments of the bar-headed geese migratory pathway. We also present findings on the migratory behavior of bar-headed geese determined from this new analytical approach.
Suggested Citation
Luo, Z., Baoping, Y., Takekawa, J.Y., Prosser, D.J., 2012, Discovering shared segments on the migration route of the bar-headed goose by time-based plane-sweeping trajectory clustering: Journal of Information and Computational Science, v. 9, no. 16, p. 5093-5100.
Publication type
Article
Publication Subtype
Journal Article
Title
Discovering shared segments on the migration route of the bar-headed goose by time-based plane-sweeping trajectory clustering