fd971fc7-a730-4c68-9a02-76022e56ddab eng utf8 dataset dataset NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom polardatacentre@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information pointOfContact 2022-03-29 ISO 19115 Geographic Information - Metadata ISO 19115:2003(E) European Petroleum Survey Group (EPSG) Geodetic Parameter Registry 2008-11-12 publication European Petroleum Survey Group EPSGadministrator@iogp.org https://www.epsg-registry.org/ EPSG Geodetic Parameter Dataset The EPSG Geodetic Parameter Dataset is a structured dataset of Coordinate Reference Systems and Coordinate Transformations, accessible through this online registry. information publisher urn:ogc:def:crs:EPSG::3031 6.18.3 Data for Synthetic Shelf Sediment Maps for the Greenland Sea and Barents Sea 2022-03-29 creation 2022-03-29 revision 2022-03-29 publication 2022-03-29 released 1.0 https://doi.org/10.5285/fd971fc7-a730-4c68-9a02-76022e56ddab doi GB/NERC/BAS/PDC/01629 https://data.bas.ac.uk/ NE/R012571/1 award Please cite this item as: Laverick, J. (2022). Data for Synthetic Shelf Sediment Maps for the Greenland Sea and Barents Sea (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/fd971fc7-a730-4c68-9a02-76022e56ddab This dataset represents the sediment properties and physical environment of the seabed for the Greenland Sea and Barents Sea shelf area. The data were produced at a spatial resolution of 0.01 by 0.01 degrees. Available variables include: whole sediment mean grain size, mud, sand and gravel percentages, rock cover, porosity and permeability, carbon and nitrogen content of sediments, depth, slope, roughness, terrain ruggedness index, topographic position index. The dataset also includes a seasonal cycle of monthly natural disturbance and bed shear stress. This dataset was produced by the MiMeMo project (NE/R012571/1), part of the Changing Arctic Ocean programme, jointly funded by the UKRI Natural Environment Research Council (NERC) and the German Federal Ministry of Education and Research (BMBF). No credit. completed Laverick, Jack H. University of Strathclyde Researcher author NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom PDCServiceDesk@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information pointOfContact asNeeded completed EARTH SCIENCE > Oceans > Marine Sediments > Geotechnical Properties EARTH SCIENCE > Oceans > Marine Environment Monitoring theme Global Change Master Directory (GCMD) Science Keywords 2026-01-27 publication 23 Global Change Data Center, Science and Exploration Directorate, Goddard Space Flight Center (GSFC) National Aeronautics and Space Administration (NASA) Greenbelt MD United States of America https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords Global Change Master Directory (GCMD) Keywords The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords. information publisher Arctic Barents Sea Greenland Sea Sediment maps Sediment properties theme Barents Sea Arctic Greenland Sea Arctic place Oceanographic geographical features theme GEMET - INSPIRE themes, version 1.0 2021-01-06 revision otherRestrictions no limitations to public access otherRestrictions no limitations license Open Government Licence v3.0 otherRestrictions Data released under Open Government Licence V3.0: otherRestrictions None. url url largerWorkCitation url url dependency url url crossReference url url dependency textTable eng utf8 environment oceans -43.995 70.305 60.00083 82.89083 2021-01-01 2021-12-31 It is recommended that careful attention be paid to the contents of any data, and that the author be contacted with any questions regarding appropriate use. If you find any errors or omissions, please report them to polardatacentre@bas.ac.uk. NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom PDCServiceDesk@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information distributor text/plain text/csv application/octet-stream application/netcdf bytes 9234179686 https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=fd971fc7-a730-4c68-9a02-76022e56ddab WWW:LINK-1.0-http--link Get Data Download data download bytes 9234179686 https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=fd971fc7-a730-4c68-9a02-76022e56ddab WWW:LINK-1.0-http--link Get Data Download data download bytes 9234179686 https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=fd971fc7-a730-4c68-9a02-76022e56ddab WWW:LINK-1.0-http--link Get Data Download data download bytes 9234179686 https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=fd971fc7-a730-4c68-9a02-76022e56ddab WWW:LINK-1.0-http--link Get Data Download data download dataset Methodology: This dataset was produced by a random forest model trained on bathymetric properties and bed shear stress to predict sediment classes as defined by the Norwegian geological survey (NGU). Sediment classes were predicted for a larger area in the Barents Sea than covered by NGU, and also for the Greenland Sea. The discrete sediment classes were then decomposed into continuous variables before exploiting relationships with sediment grain size to produce fields of additional sediment properties. Data collection: The model was implemented in the R programming environment (v.4.0.2) using H2O (v3.32.0.1). Data quality: Average model accuracy was always > 92% in recreating Sediment classes. For more detailed assessment of model accuracy see the associated manuscript. asNeeded completed