GPS location history data mining and anomalous detection: the scenario of bar-headed geese migration
Chapter 44 in Proceedings of the 2012 International Conference on Information Technology and Software Engineering, volume 211 in the Lecture Notes in Electrical Engineering series
By:
Ze Luo
,
Yan Xiong
,
Baoping Yan
,
Diann J. Prosser
,
and John Y. Takekawa
It is important to discover common movement sequences and uncommon behaviors during the migration of wild birds. In this paper, we propose a new approach to analyze the GPS location history data of migratory birds. The stopover sites are first extracted from the location history data of birds, and their movement sequences are generated automatically. Then, a consistency calculation method is introduced for calculating the movement sequence consistency degrees among the birds. The common movement sequences and uncommon behaviors can be recognized on the basis of consistency. We conducted experiments on the data collected from bar-headed geese captured in the Qinghai Lake region. The experiment results indicate the correctness of our approach.
Additional publication details
Publication type:
Book chapter
Publication Subtype:
Book Chapter
Title:
GPS location history data mining and anomalous detection: the scenario of bar-headed geese migration
Volume:
211
Year Published:
2013
Language:
English
Publisher:
Springer
Publisher location:
Amsterdam, Netherlands
Contributing office(s):
Patuxent Wildlife Research Center
Description:
Chapter 44: 8 p.
Larger Work Type:
Book
Larger Work Subtype:
Other Government Series
Larger Work Title:
Proceedings of the 2012 International Conference on Information Technology and Software Engineering
,
and John Y. Takekawa