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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

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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