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: , and 

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Abstract

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.

Additional publication details

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
Series title Journal of Information and Computational Science
Volume 9
Issue 16
Year Published 2012
Language English
Publisher Binary Information Press Limited
Contributing office(s) Western Ecological Research Center
Description 8 p.
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Journal of Information and Computational Science
First page 5093
Last page 5100
Country United States