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Classification of animal dive tracks via automatic landmarking, principal components analysis and clustering
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dc.contributor.author | Walker, Cameron | |
dc.contributor.author | MacKenzie, Monique Lea | |
dc.contributor.author | Donovan, Carl Robert | |
dc.contributor.author | Hastie, Gordon Drummond | |
dc.contributor.author | Quick, Nicola Jane | |
dc.contributor.author | Kidney, Darren | |
dc.date.accessioned | 2019-01-14T17:30:12Z | |
dc.date.available | 2019-01-14T17:30:12Z | |
dc.date.issued | 2011-08-19 | |
dc.identifier.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 | en |
dc.identifier.issn | 2150-8925 | |
dc.identifier.other | PURE: 5347536 | |
dc.identifier.other | PURE UUID: dc0749ae-228c-4fd1-be8e-aeb5093a82a5 | |
dc.identifier.other | ORCID: /0000-0002-9773-2755/work/54819186 | |
dc.identifier.other | ORCID: /0000-0002-1465-5193/work/68647696 | |
dc.identifier.other | ORCID: /0000-0002-8505-6585/work/74509959 | |
dc.identifier.uri | https://hdl.handle.net/10023/16861 | |
dc.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). | en |
dc.description.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. | |
dc.language.iso | eng | |
dc.relation.ispartof | Ecosphere | en |
dc.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. | en |
dc.subject | Automatic landmark generation | en |
dc.subject | Principal components analysis | en |
dc.subject | Regression spline | en |
dc.subject | Whale ensonification | en |
dc.subject | QH301 Biology | en |
dc.subject.lcc | QH301 | en |
dc.title | Classification of animal dive tracks via automatic landmarking, principal components analysis and clustering | en |
dc.type | Journal article | en |
dc.description.version | Publisher PDF | en |
dc.contributor.institution | University of St Andrews. Office of the Principal | en |
dc.contributor.institution | University of St Andrews. Statistics | en |
dc.contributor.institution | University of St Andrews. Scottish Oceans Institute | en |
dc.contributor.institution | University of St Andrews. Centre for Research into Ecological & Environmental Modelling | en |
dc.contributor.institution | University of St Andrews. School of Mathematics and Statistics | en |
dc.contributor.institution | University of St Andrews. Sea Mammal Research Unit | en |
dc.contributor.institution | University of St Andrews. School of Biology | en |
dc.identifier.doi | https://doi.org/10.1890/ES11-00034.1 | |
dc.description.status | Peer reviewed | en |
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