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From 1 - 10 / 1430
  • Region: Nordland county Number of field observations: 4331 Field sampling years: 2011, 2012 Prevalence: 13% Presence / absences: 503 / 3828 Method: BRT run in R with the R-package Dismo. (GAMs were also tested and gave similar distribution.) Number of predictor variables: 9 Information about the predictor variables: curvature at coarse and medium detailed spatial resolution with a 1025 and 525 m moving calculating window respectively, based on a 25 m resolution DEM; DEM, slope, and wave exposure (all at 25 m resolution, the predictor variables are described in Rinde et al. 2006); mean salinity, mean current speed, maximum temperature and mean temperature, all with a 800 m resolution, but resampled to 25 m. AUC internal: 0.99.

  • Multibeam echosounder data and seabed sampling data acquired during the INSS and INFOMAR national seabed mapping programmes were the primary sources of data used in the generation of this marine habitat map. The original classes assigned to the data were translated to the EUNIS habitat classification system as part of the MESH Atlantic project.

  • Multibeam echosounder data and seabed sampling data acquired during the INFOMAR national seabed mapping programme were the primary sources of data used in the generation of this marine habitat map. The original classes assigned to the data were translated to the EUNIS habitat classification system as part of the MESH Atlantic project.

  • Multibeam echosounder data and seabed sampling data acquired during the INSS and INFOMAR national seabed mapping programmes were the primary sources of data used in the generation of this habitat map. The original sediment classes assigned to the data were translated to the EUNIS habitat classification system as part of the MESH Atlantic project.

  • Classification of Roaringwater Bay into marine habitats. The original classes assigned to the data were translated to the EUNIS habitat classification system as part of the MESH Atlantic project.

  • Multibeam echosounder data and seabed sampling data acquired during the INFOMAR national seabed mapping programme were the primary sources of data used in the generation of this marine habitat map. The original classes assigned to the data were translated to the EUNIS habitat classification system as part of the MESH Atlantic project.

  • Region: The counties Aust-Agder and Telemark Number of field observations: 1848 Field sampling years: 1992 and 2008 Prevalence: 13.6% Presence / absences: 252/1596 Method: BRT run in R with the R-package Dismo. (The model predicts carbonate sand on peaks and in sheltered areas where it is unlikely to find carbonate sand. Such areas have been identified through rules set up in collaboration with geologists at Geological Survey of Norway (NGU; curvature index values >|1|, and the wave exposure index less than 10 000, cf Rinde et al. 2006) and removed from the shape layers for predicted presence of carbonate sand created from the grid layer. Number of predictor variables: 10 Information about the predictor variables: curvature at coarse, medium and detailed resolution with a 1025, 525 and 125 m moving calculating window respectively, based on a 25 m resolution DEM; DEM, slope at two resolutions (12.5 and 25 m); wave exposure, longitude, and an optimal radiation index, all with 25 m resolution; and aspect based on a 12.5 resolution DEM. AUC internal: 0.96.

  • This classification was produced using approach similar to the used by BGS in creation of seabed sediments maps. The interpretation used data from surface grab samples and surface sub-samples from vibro core samples. Each sample was colour coded following detailed particle size analysis based on Folk classification. This data was incorporated within GIS and interpreted together with multibeam backscatter and shaded relief. This exercise allowed interpolation between areas where sample data was absent. Moreover, this interpretation was supported with video dive data. Thus, this study produced seabed sediment type facies interpretation for selected study areas that added more detail to the existing BGS maps. The original classes assigned to the data were translated to the EUNIS habitat classification system as part of the MESH Atlantic project.

  • A survey of habitats with particular reference to maerl around the Summer Isles, Ross and Chromate, Scotland was undertaken by the Benthic Mapping and assessment project (BMAP), at the University of Newcastle, in collaboration with Scottish Natural Heritage. Careful integration of acoustic data with biological data forms the basis of biological resource maps.

  • Confidence in kinetic energy due to currents at the seabed in the Mediterranean. Values are on a range from 1 (Low confidence) to 3 (High confidence). The confidence assessment considered factors such as: • Quality of training data and methods used to construct the model. • Temporal resolution. • Spatial resolution Detailed information on the confidence assessment in Populus J. et al 2017. EUSeaMap, a European broad-scale seabed habitat map. Ifremer. http://doi.org/10.13155/49975