A method for estimating colony sizes of Adélie penguins using remote sensing imagery

M. A. LaRue, H. J. Lynch, P. O B Lyver, K. Barton, D. G. Ainley, A. Pollard, W. R. Fraser, G. Ballard

Research output: Contribution to journalArticlepeer-review

58 Scopus citations


Adélie penguins (Pygoscelis adeliae) are important predators of krill (Euphausia spp.) and Antarctic silverfish (Pleuragramma antarctica) during summer, are a key indicator of the status of the Southern Ocean ecosystem, and are therefore a focal species for the Committee for the Conservation of Antarctic Marine Living Resources (CCAMLR) Ecosystem Monitoring Program. The ability to monitor the population size of species potentially affected by Southern Ocean fisheries, i.e., the Adélie penguin, is critical for effective management of those resources. However, for several reasons, direct estimates of population size are not possible in many locations around Antarctica. In this study, we combine high-resolution (0.6 m) satellite imagery with spectral analysis in a supervised classification to estimate the sizes of Adélie penguin breeding colonies along Victoria Land in the Ross Sea and on the Antarctic Peninsula. Using satellite images paired with concurrent ground counts, we fit a generalized linear mixed model with Poisson errors to predict the abundance of breeding pairs as a function of the area of current-year guano staining identified in the satellite imagery. Guano-covered area proved to be an effective proxy for the number of penguins residing within. Our model provides a robust, quantitative mechanism for estimating the breeding population size of colonies captured in imagery and identifies terrain slope as a significant component influencing apparent nesting density. While our high-resolution satellite imagery technique was developed for the Adélie penguin, these principles are directly transferrable to other colonially nesting seabirds and other species that aggregate in fixed localities.

Original languageEnglish (US)
Pages (from-to)507-517
Number of pages11
JournalPolar Biology
Issue number4
StatePublished - Apr 2014


  • Adélie penguin
  • Antarctica
  • GIS
  • Generalized linear mixed models
  • High-resolution imagery
  • Population estimation
  • Supervised classification


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