Benthic megafaunal specimen counts from seabed photographs at a site in the Central North Sea (STEMM-CCS Project)

DOI

The data are counts of megafaunal specimens in seabed photographs captured with a Teledyne Gavia autonomous underwater vehicle deployed from the RRS James Cook in May 2019 at a site in UK sector of the Central North Sea (Connelly, 2019), as part of the Strategies for Environmental Monitoring of Marine Carbon Capture and Storage (STEMM-CCS) project. The seabed photographs were captured using a GRAS-14S5M-C camera with a Tamron TAM 23FM08-L lens mounted to the Gavia autonomous underwater vehicle. The camera captured photographs at a temporal frequency of 1.875 frames per second, a resolution of 1280 x 960 pixels, and at a target altitude of 2 m above the seafloor. Overlapping photos were removed. Megafaunal specimens (>1 cm) in the non-overlapping images were detected using the MAIA machine learning algorithm in BIIGLE. The potential specimens detected using this method were reviewed to remove false positives and classified into morphotypes manually. Counts by morphotype, latitude and longitude (in degrees), camera altitude (m above seafloor) and seabed area (m2) are provided for each photo. The following additional unchecked raw data are also provided: date, time, AUV mission number, and AUV heading, pitch, and roll. Acknowledgements We thank the crew and operators of the RRS James Cook and the Gavia autonomous underwater vehicle. The project was funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 654462.

Identifier
DOI https://doi.org/10.1594/PANGAEA.912668
Related Identifier http://eprints.soton.ac.uk/id/eprint/437264
Metadata Access https://ws.pangaea.de/oai/provider?verb=GetRecord&metadataPrefix=datacite4&identifier=oai:pangaea.de:doi:10.1594/PANGAEA.912668
Provenance
Creator Hosking, Brett; Horton, Tammy; Durden, Jennifer M; Jones, Daniel O B; Ruhl, Henry A
Publisher PANGAEA - Data Publisher for Earth & Environmental Science
Publication Year 2020
Funding Reference Horizon 2020, 654462
Rights Creative Commons Attribution 4.0 International; https://creativecommons.org/licenses/by/4.0/
OpenAccess true
Representation
Language English
Resource Type Dataset
Format text/tab-separated-values
Size 80342 data points
Discipline Fine Arts, Music, Theatre and Media Studies; Humanities; Photography
Spatial Coverage (-0.394W, 57.978S, -0.372E, 57.996N); North Sea
Temporal Coverage Begin 2019-05-20T09:48:46Z
Temporal Coverage End 2019-05-27T13:56:50Z