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Assessing Performance of Bayesian State-Space Models Fit to Argos Satellite Telemetry Locations Processed with Kalman Filtering

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Listed:
  • Mónica A Silva
  • Ian Jonsen
  • Deborah J F Russell
  • Rui Prieto
  • Dave Thompson
  • Mark F Baumgartner

Abstract

Argos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF). The KF algorithm is reported to increase the number and accuracy of estimated positions over the traditional Least Squares (LS) algorithm, with potential advantages to the application of state-space methods to model animal movement data. We tested the performance of two Bayesian state-space models (SSMs) fitted to satellite tracking data processed with KF algorithm. Tracks from 7 harbour seals (Phoca vitulina) tagged with ARGOS satellite transmitters equipped with Fastloc GPS loggers were used to calculate the error of locations estimated from SSMs fitted to KF and LS data, by comparing those to “true” GPS locations. Data on 6 fin whales (Balaenoptera physalus) were used to investigate consistency in movement parameters, location and behavioural states estimated by switching state-space models (SSSM) fitted to data derived from KF and LS methods. The model fit to KF locations improved the accuracy of seal trips by 27% over the LS model. 82% of locations predicted from the KF model and 73% of locations from the LS model were

Suggested Citation

  • Mónica A Silva & Ian Jonsen & Deborah J F Russell & Rui Prieto & Dave Thompson & Mark F Baumgartner, 2014. "Assessing Performance of Bayesian State-Space Models Fit to Argos Satellite Telemetry Locations Processed with Kalman Filtering," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-13, March.
    • Handle: RePEc:plo:pone00:0092277
    DOI: 10.1371/journal.pone.0092277
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    References listed on IDEAS

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    4. Breed, Greg A. & Costa, Daniel P. & Jonsen, Ian D. & Robinson, Patrick W. & Mills-Flemming, Joanna, 2012. "State-space methods for more completely capturing behavioral dynamics from animal tracks," Ecological Modelling, Elsevier, vol. 235, pages 49-58.
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    1. Andrew D Lowther & Christian Lydersen & Mike A Fedak & Phil Lovell & Kit M Kovacs, 2015. "The Argos-CLS Kalman Filter: Error Structures and State-Space Modelling Relative to Fastloc GPS Data," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-16, April.

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