GPS Location History Data Mining and Anomalous Detection: The Scenario of Bar-Headed Geese Migration

  • Yan Xiong
  • Ze Luo
  • Baoping Yan
  • Diann J. Prosser
  • John Y. Takekawa
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 211)


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.


Location history mining Anomalous detection Bar-headed goose 


  1. 1.
    Cooke SJ, Hinch SG, Wikelski M (2004) Biotelemetry: a mechanistic approach to ecology. Trends Ecol Evol 19:334–343CrossRefGoogle Scholar
  2. 2.
    Tomkiewicz SM, Fuller MR et al (2010) Global positioning system and associated technologies in animal behavior and ecological research. Phil Trans R Soc B 365:2163–2176. doi:10.1098/rstb.2010.0090
  3. 3.
    Smouse PE, Focardi S, Moorcroft PR (2010) Stochastic modeling of animal movement. Phil Trans R Soc B 365:2201–2211CrossRefGoogle Scholar
  4. 4.
    Li Q, Zheng Y et al (2008) Mining user similarity based on location history. In: GIS ‘08 Proceedings of the 16th ACM SIGSPATIAL international conference on advances in geographic information systems. doi: 10.1145/1463434.1463477
  5. 5.
    Zheng Y, Zhang L et al (2011) Recommending friends and locations based on individual location history. ACM Trans Web 5(1), Article 5Google Scholar
  6. 6.
    Tang M, Zhou Y et al (2011) Exploring the wild birds’ migration data for the disease spread study of H5N1: A clustering and association approach. Knowl Inf Syst 27:227–251Google Scholar
  7. 7.
    Carneiro C, Alp A et al (2008) Advanced data mining method for discovering regions and trajectories of moving objects: “Ciconiaciconia”Scenario. In: Proceedings of AGILE, pp 201–224Google Scholar
  8. 8.
    Cui P, Luo Z et al (2011) Bird migration and risk for H5N1 transmission into Qinghai Lake, China. Vector-Borne Zoonotic Dis 11(2):567–576Google Scholar
  9. 9.
    Sabir B et al (2008) Seasonal movements and migration of Palla’s Gulls La-rusIchthyaetus from Qinghai Lake, China. Forktail 24:100–107Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yan Xiong
    • 1
  • Ze Luo
    • 1
  • Baoping Yan
    • 1
  • Diann J. Prosser
    • 2
  • John Y. Takekawa
    • 3
  1. 1.Computer Network Information CenterChinese Academy of SciencesBeijingChina
  2. 2.U.S. Geological SurveyPatuxent Wildlife Research CenterBeltsvilleUSA
  3. 3.U.S. Geological SurveyWestern Ecological Research CenterVallejoUSA

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