Deep Learning Resolves Representative Movement Patterns in a Marine Predator Species

• Published in: Applied Sciences
• Main Authors: Peng, Chengbin, Duarte, Carlos, Costa, Daniel, Guinet, Christophe, Harcourt, Robert, Hindell, Mark, Mcmahon, Clive, Muelbert, Monica, Thums, Michele, Wong, Ka-Chun, Zhang, Xiangliang
• Other Authors: Universidade de Lisboa (ULISBOA), State University of Feira de Santana, Centre d'Études Biologiques de Chizé - UMR 7372 (CEBC), Université de La Rochelle (ULR)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Department of Biological Sciences, Macquarie University, Macquarie University, Department of Biological Sciences, Antartic Wildlife Research Unit, School of Zoology, University of Tasmania, Institute for Marine and Antarctic Studies Horbat (IMAS), University of Tasmania Hobart, Australia (UTAS), Universidade Federal do Rio Grande, Australian Institute of Marine Science Perth (AIMS Perth), Australian Institute of Marine Science (AIMS), King Abdullah University of Science and Technology (KAUST)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2019
• Subjects: marine animal movement analysis; recurrent neural networks; representative patterns; [SDE]Environmental Sciences; Elephant Seal; Southern Elephant Seal
• Online Access: https://hal.archives-ouvertes.fr/hal-02746653; https://doi.org/10.3390/app9142935

International audience The analysis of animal movement from telemetry data provides insights into how and why animals move. While traditional approaches to such analysis mostly focus on predicting animal states during movement, we describe an approach that allows us to identify representative movement patterns of different animal groups. To do this, we propose a carefully designed recurrent neural network and combine it with telemetry data for automatic feature extraction and identification of non-predefined representative patterns. In the experiment, we consider a particular marine predator species, the southern elephant seal, as an example. With our approach, we identify that the male seals in our data set share similar movement patterns when they are close to land. We identify this pattern recurring in a number of distant locations, consistent with alternative approaches from previous research.