title: A new method for discovering behavior patterns among animal movements.
abstract: Advanced satellite tracking technologies enable biologists to track animal movements at fine spatial and temporal scales. The resultant data present opportunities and challenges for understanding animal behavioral mechanisms. In this paper, we develop a new method to elucidate animal movement patterns from tracking data. Here, we propose the notion of continuous behavior patterns as a concise representation of popular migration routes and underlying sequential behaviors during migration. Each stage in the pattern is characterized in terms of space (i.e., the places traversed during movements) and time (i.e. the time spent in those places); that is, the behavioral state corresponding to a stage is inferred according to the spatiotemporal and sequential context. Hence, the pattern may be interpreted predictably. We develop a candidate generation and refinement framework to derive all continuous behavior patterns from raw trajectories. In the framework, we first define the representative spots to denote the underlying potential behavioral states that are extracted from individual trajectories according to the similarity of relaxed continuous locations in certain distinct time intervals. We determine the common behaviors of multiple individuals according to the spatiotemporal proximity of representative spots and apply a projection-based extension approach to generate candidate sequential behavior sequences as candidate patterns. Finally, the candidate generation procedure is combined with a refinement procedure to derive continuous behavior patterns. We apply an ordered processing strategy to accelerate candidate refinement. The proposed patterns and discovery framework are evaluated through conceptual experiments on both real GPS-tracking and large synthetic datasets.
authors.affiliation: University of Chinese Academy of Sciences, Beijing, China; Computer Network Information Center, Chinese Academy of Sciences, Beijing, China.
authors.forename: Yuwei
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Computer Network Information Center, Chinese Academy of Sciences, Beijing, China.
authors.forename: Ze
authors.initials: Z
authors.lastname: Luo
authors.affiliation: Western Ecological Research Center, US Geological Survey, Vallejo, CA, USA; Science Division, National Audubon Society, San Francisco, CA, USA.
authors.forename: John
authors.initials: J
authors.lastname: Takekawa
authors.affiliation: Patuxent Wildlife Research Center, US Geological Survey, Beltsville, MD, USA.
authors.forename: Diann
authors.initials: D
authors.lastname: Prosser
authors.affiliation: Computer Network Information Center, Chinese Academy of Sciences, Beijing, China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Xiong
authors.affiliation: EMPRES Wildlife Health and Ecology Unit, Animal Production and Health Division, Food and Agriculture Organization of the United Nations, Rome, Italy.
authors.forename: Scott
authors.initials: S
authors.lastname: Newman
authors.affiliation: Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, Oklahoma, USA.
authors.forename: Xiangming
authors.initials: X
authors.lastname: Xiao
authors.affiliation: Wildlife Science and Conservation Center, Ulaanbaatar, Mongolia.
authors.forename: Nyambayar
authors.initials: N
authors.lastname: Batbayar
authors.affiliation: Western Ecological Research Center, US Geological Survey, Vallejo, CA, USA.
authors.forename: Kyle
authors.initials: K
authors.lastname: Spragens
authors.affiliation: Bombay Natural History Society, Hornbill House, Mumbai, India.
authors.forename: Sivananinthaperumal
authors.initials: S
authors.lastname: Balachandran
authors.affiliation: Computer Network Information Center, Chinese Academy of Sciences, Beijing, China.
authors.forename: Baoping
authors.initials: B
authors.lastname: Yan
keywords: Spatiotemporal data mining; animal movements; continuous behavior patterns