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A new method for discovering behavior patterns among animal movements

Overview of attention for article published in International Journal of Geographical Information Science, September 2015
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Title
A new method for discovering behavior patterns among animal movements
Published in
International Journal of Geographical Information Science, September 2015
DOI 10.1080/13658816.2015.1091462
Pubmed ID
Authors

Yuwei Wang, Ze Luo, John Takekawa, Diann Prosser, Yan Xiong, Scott Newman, Xiangming Xiao, Nyambayar Batbayar, Kyle Spragens, Sivananinthaperumal Balachandran, Baoping Yan

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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Netherlands 1 2%
South Africa 1 2%
United Kingdom 1 2%
Denmark 1 2%
United States 1 2%
Unknown 43 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 24%
Researcher 11 22%
Student > Master 6 12%
Lecturer 2 4%
Student > Postgraduate 2 4%
Other 5 10%
Unknown 11 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 33%
Computer Science 10 20%
Earth and Planetary Sciences 5 10%
Environmental Science 3 6%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 4 8%
Unknown 10 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 May 2016.
All research outputs
#16,636,403
of 25,452,734 outputs
Outputs from International Journal of Geographical Information Science
#1
of 1 outputs
Outputs of similar age
#160,195
of 286,379 outputs
Outputs of similar age from International Journal of Geographical Information Science
#1
of 1 outputs
Altmetric has tracked 25,452,734 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1 research outputs from this source. They receive a mean Attention Score of 0.0. This one scored the same or higher as 0 of them.
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