CEFAS742b396b-e638-4501-8d43-9818510d13fd English dataset Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS) Cefas Lowestoft Laboratory Pakefield Road Lowestoft Suffolk NR33 0HT UK data.manager@cefas.co.uk pointOfContact 2024-07-12T10:27:31 EPSG Geodetic Parameter Registry 2022-01-07 revision WGS 84 EPSG Geodetic Parameter Registry 2022-01-07 revision ETRS89 UK shelf and North Sea quantitative sediment composition predictions 2018-01-31 publication 2024-07-12 revision 2015-04-01 creation CEFAS3313 https://data.cefas.co.uk Spatial predictions of substrate composition for the UK shelf and North Sea. Compositional fractions of mud, sand and gravel were modelled for an area of the UK and North Sea using a statistical regression model. This dataset consists of percentage composition predictions for the mud, sand and gravel components as raster tifs. In addition the proportion of each of these sediment components were combined to predict the likely sediment classification as both a EUNIS habitat class and Folk class. These are also available as raster tif files with an associated ArcGIS layer file indicating the appropriate class for each raster value. A shape file of the Folk classification is also available. Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS) Cefas Lowestoft Laboratory Pakefield Road Lowestoft Suffolk NR33 0HT UK data.manager@cefas.co.uk originator Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS) Cefas Lowestoft Laboratory Pakefield Road Lowestoft Suffolk NR33 0HT UK data.manager@cefas.co.uk custodian Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS) Cefas Lowestoft Laboratory Pakefield Road Lowestoft Suffolk NR33 0HT UK data.manager@cefas.co.uk distributor Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS) data.manager@cefas.co.uk owner Department for Environment, Food and Rural Affairs (DEFRA) defra.helpline@defra.gov.uk owner European Commission info@publications.europa.eu owner notPlanned Sediment grain size parameters SeaDataNet P02 parameter discovery vocabulary 2011-03-25 revision Desk study Model Sediment GEMET, version 1.0 2008-06-01 publication Habitats and biotopes GEMET - INSPIRE themes, version 1.0 2008-06-01 publication Littoral Infralittoral Circalittoral Deep Circalittoral Sediment SeaVoX Vertical Co-ordinate Coverages 2010-05-18 revision Marine Environmental Data and Information Network MEDIN metadata record availability 2012-01-11 publication data.gov.uk MEDIN metadata record availability 2012-01-11 publication otherRestrictions noLimitations otherRestrictions Public data - no limitations to reuse 500 English environment -11.00 10.00 48.00 59.50 2015-04-01 2015-04-01 Binary Delimited Geographic Information System Unknown https://data.cefas.co.uk/view/3313 Cefas Data Portal download The Cefas Data Portal contains metadata records and data sets available to download and connect to in support of our commitment to open science. Data is available in the following formats: Binary download, CSV, ESRI Shapefile. The data can also be accessed via the WFS and WMS protocols. dataset INSPIRE Data Specification on Habitats and Biotopes – Technical Guidelines 2013-12-10 publication false See the referenced specification Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 publication true See the referenced specification For a full description of the methodology used to generate these data see: `http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0142502`_ In short, the analysis combined outputs from hydrodynamic models as well as optical remote sensing data from satellite platforms and bathymetric variables, which were mainly derived from acoustic remote sensing. A statistical regression model was built to make quantitative predictions of sediment composition (fractions of mud, sand and gravel) using the random forest algorithm. The compositional data was analysed on the additive log-ratio scale and then transformed back into percentages of the individual sediment components. From these percentage components a EUNIS substrate model was also generated. .. _`http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0142502`: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0142502 MEDIN 3.1.1