Discovery of Migration Habitats and Routes of Wild Bird Species by Clustering and Association Analysis

Abstract

Knowledge about the wetland use of migratory bird species during the annual life circle is very interesting to biologists, as it is critically important for conservation site construction and avian influenza control. The raw data of the habitat areas and the migration routes can be determined by high-tech GPS satellite telemetry, that usually are large scale with high complexity. In this paper, we convert these biological problems into computational studies, and introduce efficient algorithms for the data analysis. Our key idea is the concept of hierarchical clustering for migration habitat localization, and the notion of association rules for the discovery of migration routes. One of our clustering results is the Spatial-Tree, an illusive map which depicts the home range of bar-headed geese. A related result to this observation is an association pattern that reveals a high possibility of bar-headed geese’s potential migration routes. Both of them are of biological novelty and meaning.KeywordsClusteringSequence miningBird MigrationHabitatRouteScientific dataQinghai Lake