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Data from: Measuring agreement among experts in classifying camera images of similar species Gooliaff, TJ; Hodges, Karen E.
Description
Abstract
Camera trapping and solicitation of wildlife images through citizen science have become common tools in ecological research. Such studies collect many wildlife images for which correct species classification is crucial; even low misclassification rates can result in erroneous estimation of the geographic range or habitat use of a species, potentially hindering conservation or management efforts. However, some species are difficult to tell apart, making species classification challenging - but the literature on classification agreement rates among experts remains sparse. Here, we measure agreement among experts in distinguishing between images of two similar congeneric species, bobcats (Lynx rufus) and Canada lynx (L. canadensis). We asked experts to classify the species in selected images to test whether the season, background habitat, time of day, and the visible features of each animal (e.g., face, legs, tail) affected agreement among experts about the species in each image. Overall, experts had moderate agreement (Fleiss’ kappa = 0.64), but experts had varying levels of agreement depending on these image characteristics. Most images (71%) had ≥1 expert classification of ‘unknown’, and many images (39%) had some experts classify the image as ‘bobcat’ while others classified it as ‘lynx’. Further, experts were inconsistent even with themselves, changing their classifications of numerous images when they were asked to reclassify the same images months later. These results suggest that classification of images by a single expert is unreliable for similar-looking species. Most of the images did obtain a clear majority classification from the experts, although we emphasize that even majority classifications may be incorrect. We recommend that researchers using wildlife images consult multiple species experts to increase confidence in their image classifications of similar sympatric species. Still, when the presence of a species with similar sympatrics must be conclusive, physical or genetic evidence should be required.
Usage notes
Image classifications
Item Metadata
| Title |
Data from: Measuring agreement among experts in classifying camera images of similar species
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| Creator | |
| Date Issued |
2021-05-19
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| Description |
Abstract
Camera trapping and solicitation of wildlife images through citizen science have become common tools in ecological research. Such studies collect many wildlife images for which correct species classification is crucial; even low misclassification rates can result in erroneous estimation of the geographic range or habitat use of a species, potentially hindering conservation or management efforts. However, some species are difficult to tell apart, making species classification challenging - but the literature on classification agreement rates among experts remains sparse. Here, we measure agreement among experts in distinguishing between images of two similar congeneric species, bobcats (Lynx rufus) and Canada lynx (L. canadensis). We asked experts to classify the species in selected images to test whether the season, background habitat, time of day, and the visible features of each animal (e.g., face, legs, tail) affected agreement among experts about the species in each image. Overall, experts had moderate agreement (Fleiss’ kappa = 0.64), but experts had varying levels of agreement depending on these image characteristics. Most images (71%) had ≥1 expert classification of ‘unknown’, and many images (39%) had some experts classify the image as ‘bobcat’ while others classified it as ‘lynx’. Further, experts were inconsistent even with themselves, changing their classifications of numerous images when they were asked to reclassify the same images months later. These results suggest that classification of images by a single expert is unreliable for similar-looking species. Most of the images did obtain a clear majority classification from the experts, although we emphasize that even majority classifications may be incorrect. We recommend that researchers using wildlife images consult multiple species experts to increase confidence in their image classifications of similar sympatric species. Still, when the presence of a species with similar sympatrics must be conclusive, physical or genetic evidence should be required.; Usage notes Image classifications |
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| Type | |
| Notes |
Dryad version number: 1 Version status: submitted Dryad curation status: Published Sharing link: https://datadryad.org/stash/share/Pgq2zuXS5JmrO9Oks-iTFj6waEL1Y6sSbXdVfR03Hps</p> Storage size: 160134 Visibility: public |
| Date Available |
2020-06-24
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| Provider |
University of British Columbia Library
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| License |
CC0 1.0
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| DOI |
10.14288/1.0398011
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| URI | |
| Publisher DOI | |
| Rights URI | |
| Aggregated Source Repository |
Dataverse
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Item Media
Item Citations and Data
License
CC0 1.0