Image analysis of color aerial photography to estimate penguin population size
Trathan, Philip N. ORCID: https://orcid.org/0000-0001-6673-9930. 2004 Image analysis of color aerial photography to estimate penguin population size. Wildlife Society Bulletin, 32 (2). 332-343. https://doi.org/10.2193/0091-7648(2004)32[332:IAOCAP]2.0.CO;2
Full text not available from this repository. (Request a copy)Abstract/Summary
Penguin populations are potentially sensitive indicators of ecological change in Antarctic and sub-Antarctic marine ecosystems. Aerial photographic surveys provide the most robust method for estimating breeding population size, particularly for large colonies. Obtaining population estimates from aerial photographs is laborious and usually carried out by manually counting individual birds on highly magnified prints. I derived population estimates using computer-based image analysis of digitally scanned color aerial photographs of macaroni penguin (Eudyptes chrysolophus) colonies at Bird Island, South Georgia. I compared automated image analysis with manual counts from the photographic prints and conventional ground counts, highlighting assumptions that contributed to differences in population estimates. The automated image-analysis routines produced estimates that were highly correlated with ground counts, indicating that the technique could be reliably used for large-scale macaroni penguin population surveys.
Item Type: | Publication - Article |
---|---|
Digital Object Identifier (DOI): | https://doi.org/10.2193/0091-7648(2004)32[332:IAOCAP]2.0.CO;2 |
Programmes: | BAS Programmes > Antarctic Science in the Global Context (2000-2005) > Dynamics and Management of Ocean Ecosystems |
ISSN: | 0091-7648 |
Additional Keywords: | aerial photography, image analysis, penguin population estimate, South Georgia |
NORA Subject Terms: | Zoology Ecology and Environment |
Date made live: | 15 Mar 2012 11:09 +0 (UTC) |
URI: | https://nora.nerc.ac.uk/id/eprint/12479 |
Actions (login required)
View Item |
Document Downloads
Downloads for past 30 days
Downloads per month over past year