A mechanistic model of GPS collar location data: Implications for analysis and bias mitigation

Ben C. Augustine, Philip H. Crowley, John J. Cox

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


Global positioning system (GPS) collars have revolutionized the collection of animal location data; however, it is well-recognized that considerable bias can be present in these data due to habitat or behavior-induced obstruction of satellite signals resulting in inaccurate or missing locations. To date, no explicit theoretical framework of GPS fix acquisition specific to animal telemetry has been presented, and studies make differing assumptions regarding factors influencing GPS fix acquisition and how these data should be analyzed. Inappropriate statistical models have been used, interaction effects have been misunderstood, and the implementation of bias mitigation techniques has been problematic. Herein we outline current conceptual and analytical problems in the GPS animal telemetry literature, and subsequently present a theoretical model-based framework for GPS fix acquisition that clarifies the single and interactive effects of habitat and behavioral obstruction, fix interval, and collar model on GPS collar performance. By recognizing that GPS fix acquisition is a Bernoulli process, it becomes apparent that all forms of obstruction inherently interact with each other, making generalizations across study areas, study species, and collar models problematic. Stationary collar tests to determine the probability of fix acquisition (PFA), location accuracy, and the response to sources of obstruction are thus of limited applicability to animal-deployed collars. Bias mitigation techniques that extrapolate PFA models across samples, especially those using stationary collar tests to correct animal-deployed collars, are theoretically unsound. It is also demonstrated that nonlinearities in the relationships between sources of obstruction and PFA complicate PFA modeling with limited data and that even slight model misspecification can lead to considerable errors in correction factors, especially when using inverse weighting to mitigate bias. By emphasizing the importance of GPS collar sensitivity and ephemeris retention, the theoretical framework predicts that newer, more sensitive GPS collars will be less severely biased by sources of obstruction than reported for the older, less sensitive collars that have been used in the majority of GPS performance studies to date and we expect this trend to continue. This heuristic modeling exercise should be of value to researchers planning and analyzing studies using GPS collars and it also establishes a starting point for future theoretical investigations into GPS collar performance and bias mitigation.

Original languageEnglish
Pages (from-to)3616-3625
Number of pages10
JournalEcological Modelling
Issue number19
StatePublished - Oct 10 2011

Bibliographical note

Funding Information:
We would like to thank Dr. David Maehr for the opportunity to study black bears with GPS telemetry, which initiated our interest in the issue of bias in GPS telemetry. We would also like to thank Kentucky Department of Fish and Wildlife Resources and the USDA Cooperative State Research Education and Extension Service Precision Resource Management Grand for funding and the Crowley lab group, Songlin Fei, Yanbing Zheng, anonymous reviewers for useful comments that substantially improved this manuscript.


  • Global positioning system (GPS)
  • Resource selection
  • Telemetry
  • Topographic obstruction
  • Vegetative obstruction
  • Wildlife

ASJC Scopus subject areas

  • Ecological Modeling


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