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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.
| 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 |
| Google Analytic Metrics | Metrics page |