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Polar Bears from Space: Assessing Satellite Imagery as a Tool to Track Arctic Wildlife

Overview of attention for article published in PLOS ONE, July 2014
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Title
Polar Bears from Space: Assessing Satellite Imagery as a Tool to Track Arctic Wildlife
Published in
PLOS ONE, July 2014
DOI 10.1371/journal.pone.0101513
Pubmed ID
Authors

Seth Stapleton, Michelle LaRue, Nicolas Lecomte, Stephen Atkinson, David Garshelis, Claire Porter, Todd Atwood

Abstract

Development of efficient techniques for monitoring wildlife is a priority in the Arctic, where the impacts of climate change are acute and remoteness and logistical constraints hinder access. We evaluated high resolution satellite imagery as a tool to track the distribution and abundance of polar bears. We examined satellite images of a small island in Foxe Basin, Canada, occupied by a high density of bears during the summer ice-free season. Bears were distinguished from other light-colored spots by comparing images collected on different dates. A sample of ground-truthed points demonstrated that we accurately classified bears. Independent observers reviewed images and a population estimate was obtained using mark-recapture models. This estimate (N: 94; 95% Confidence Interval: 92-105) was remarkably similar to an abundance estimate derived from a line transect aerial survey conducted a few days earlier (N: 102; 95% CI: 69-152). Our findings suggest that satellite imagery is a promising tool for monitoring polar bears on land, with implications for use with other Arctic wildlife. Large scale applications may require development of automated detection processes to expedite review and analysis. Future research should assess the utility of multi-spectral imagery and examine sites with different environmental characteristics.

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Geographical breakdown

Country Count As %
United States 2 1%
Germany 1 <1%
United Kingdom 1 <1%
France 1 <1%
Mexico 1 <1%
Canada 1 <1%
Unknown 143 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 26 17%
Student > Master 24 16%
Student > Ph. D. Student 23 15%
Student > Bachelor 16 11%
Other 6 4%
Other 16 11%
Unknown 39 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 49 33%
Environmental Science 32 21%
Biochemistry, Genetics and Molecular Biology 7 5%
Computer Science 7 5%
Earth and Planetary Sciences 3 2%
Other 14 9%
Unknown 38 25%