Data
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.14264/uql.2019.930&rft.title=Seaview Survey Photo-quadrat and Image Classification Dataset&rft.identifier=10.14264/uql.2019.930&rft.publisher=The University of Queensland&rft.description=The primary scientific dataset arising from the XL Catlin Seaview Survey project is the “Seaview Survey Photo-quadrat and Image Classification Dataset”, consisting of: (1) over one million standardised, downward-facing “photo-quadrat” images covering approximately 1m2 of the sea floor; (2) human-classified annotations that can be used to train and validate image classifiers; (3) benthic cover data arising from the application of machine learning classifiers to the photo-quadrats; and (4) the triplets of raw images (covering 360o) from which the photo-quadrats were derived.Photo-quadrats were collected between 2012 and 2018 at 860 transect locations around the world, including: the Caribbean and Bermuda, the Indian Ocean (Maldives, Chagos Archipelago), the Coral Triangle (Indonesia, Philippines, Timor-Leste, Solomon Islands), the Great Barrier Reef, Taiwan and Hawaii.For additional information regarding methodology, data structure, organization and size, please see attached document “Dataset documentation”.&rft.creator=Dr Emma Kennedy&rft.creator=Dr Erwin Alberto Rodriguez-Ramirez&rft.creator=Dr Kristen Brown&rft.creator=Dr Sophie Dove&rft.creator=Dr Veronica Radice&rft.creator=Ms Catherine Kim&rft.creator=Professor Ove Hoegh-Guldberg&rft.date=2019&rft.relation=https://espace.library.uq.edu.au/view/UQ:347827&rft.relation=https://espace.library.uq.edu.au/view/UQ:380143&rft.relation=https://espace.library.uq.edu.au/view/UQ:697455&rft.relation=https://espace.library.uq.edu.au/view/UQ:dbdaddd&rft.relation=https://espace.library.uq.edu.au/view/UQ:9495bb2&rft.relation=https://espace.library.uq.edu.au/view/UQ:ac556ed&rft.relation=https://espace.library.uq.edu.au/view/UQ:367749&rft.relation=https://espace.library.uq.edu.au/view/UQ:385523&rft.relation=https://espace.library.uq.edu.au/view/UQ:b53f10b&rft.relation=https://espace.library.uq.edu.au/view/UQ:f5ee4ee&rft.relation=https://espace.library.uq.edu.au/view/UQ:f931842&rft.relation=https://espace.library.uq.edu.au/view/UQ:47679a9&rft_subject=coral reef&rft_subject=benthic community&rft_subject=monitoring&rft_subject=seascape surveys&rft_subject=photographic surveys&rft_subject=survey&rft_subject=machine learning&rft_subject=image classification&rft.type=dataset&rft.language=English Access the data

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The primary scientific dataset arising from the XL Catlin Seaview Survey project is the “Seaview Survey Photo-quadrat and Image Classification Dataset”, consisting of: (1) over one million standardised, downward-facing “photo-quadrat” images covering approximately 1m2 of the sea floor; (2) human-classified annotations that can be used to train and validate image classifiers; (3) benthic cover data arising from the application of machine learning classifiers to the photo-quadrats; and (4) the triplets of raw images (covering 360o) from which the photo-quadrats were derived.Photo-quadrats were collected between 2012 and 2018 at 860 transect locations around the world, including: the Caribbean and Bermuda, the Indian Ocean (Maldives, Chagos Archipelago), the Coral Triangle (Indonesia, Philippines, Timor-Leste, Solomon Islands), the Great Barrier Reef, Taiwan and Hawaii.For additional information regarding methodology, data structure, organization and size, please see attached document “Dataset documentation”.

Issued: 2019

Data time period: 16 09 2012 to 05 05 2018

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