Classification of animal dive tracks via automatic landmarking, principal components analysis and clustering
Abstract
The behaviour of animals and their interactions with the environment can be inferred by tracking their movement. For this reason, biologgers are an important source of ecological data, but analysing the shape of the tracks they record is difficult. In this paper we present a technique for automatically determining landmarks that can be used to analyse the shape of animal tracks. The approach uses a parametric version of the SALSA algorithm to fit regression splines to 1‐dimensional curves in N dimensions (in practice N = 2 or 3). The knots of these splines are used as landmarks in a subsequent Principal Components Analysis, and the dives classified via agglomerative clustering. We demonstrate the efficacy of this algorithm on simulated 2‐dimensional dive data, and apply our method to real 3‐dimensional whale dive data from the Behavioral Response Study (BRS) in the Bahamas. The BRS is a series of experiments to quantify shifts in behavior due to SONAR. Our analysis of 3‐dimensional track data supports an alteration in the dive behavior post‐ensonification.
Citation
Walker , C , MacKenzie , M L , Donovan , C R , Hastie , G D , Quick , N J & Kidney , D 2011 , ' Classification of animal dive tracks via automatic landmarking, principal components analysis and clustering ' , Ecosphere , vol. 2 , no. 8 , pp. 1-13 . https://doi.org/10.1890/ES11-00034.1
Publication
Ecosphere
Status
Peer reviewed
ISSN
2150-8925Type
Journal article
Rights
Copyright: © 2011 Walker et al. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Description
The BRS study was financially supported by the United States (U.S.) Office of Naval Research (www.onr.navy.mil) Grants N00014‐07‐10988, N00014‐07‐11023, N00014‐08‐10990; the U.S. Strategic Environmental Research and Development Program (www.serdp.org) Grant SI‐1539, the Environmental Readiness Division of the U.S. Navy (http://www.navy.mil/local/n45/), the U.S. Chief of Naval Operations Submarine Warfare Division (Undersea Surveillance), the U.S. National Oceanic and Atmospheric Administration (National Marine Fisheries Service, Office of Science and Technology) (http://www.st.nmfs.noaa.gov/), U.S. National Oceanic and Atmospheric Administration Ocean Acoustics Program (http://www.nmfs.noaa.gov/pr/acoustics/), and the Joint Industry Program on Sound and Marine Life of the International Association of Oil and Gas Producers (www.soundandmarinelife.org).Collections
Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.