Journal article
Snapshot Serengeti, high-frequency annotated camera trap images of 40 mammalian species in an African savanna
- Abstract:
- Camera traps can be used to address large-scale questions in community ecology by providing systematic data on an array of wide-ranging species. We deployed 225 camera traps across 1,125 km(2) in Serengeti National Park, Tanzania, to evaluate spatial and temporal inter-species dynamics. The cameras have operated continuously since 2010 and had accumulated 99,241 camera-trap days and produced 1.2 million sets of pictures by 2013. Members of the general public classified the images via the citizen-science website www.snapshotserengeti.org. Multiple users viewed each image and recorded the species, number of individuals, associated behaviours, and presence of young. Over 28,000 registered users contributed 10.8 million classifications. We applied a simple algorithm to aggregate these individual classifications into a final 'consensus' dataset, yielding a final classification for each image and a measure of agreement among individual answers. The consensus classifications and raw imagery provide an unparalleled opportunity to investigate multi-species dynamics in an intact ecosystem and a valuable resource for machine-learning and computer-vision research.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 3.0MB, Terms of use)
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- Publisher copy:
- 10.1038/sdata.2015.26
Authors
- Publisher:
- Nature Publishing Group
- Journal:
- Scientific Data More from this journal
- Volume:
- 2
- Pages:
- 150026
- Publication date:
- 2015-06-09
- Acceptance date:
- 2015-04-29
- DOI:
- EISSN:
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2052-4463
- Language:
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English
- Keywords:
- Pubs id:
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pubs:528379
- UUID:
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uuid:c3d6de6c-8e94-423e-b8a5-e55ce6971bc0
- Local pid:
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pubs:528379
- Source identifiers:
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528379
- Deposit date:
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2016-05-10
Terms of use
- Copyright holder:
- Alexandra Swanson et al
- Copyright date:
- 2015
- Notes:
- This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0. Metadata associated with this Data Descriptor is available at http://www.nature.com/sdata/ and is released under the CC0 waiver to maximize reuse.
- Licence:
- CC Attribution (CC BY)
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