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  • Broadscale habitat (EUNIS level 3) for Land's End (Runnels Stone) recommended Marine Conservation Zone (rMCZ) Updated habitat map resulting from an intergrated analysis of the acoustic and ground-truth survey data from 2013 (onboard the Coastal Survey Vessel (CSV) Water Guardian on cruise wgdn0112). Sediment types at each groundtruthing station were used to inform a semi-automated process of map production using object-based image analysis (OBIA).

  • Broadscale habitat (EUNIS level 3) for the Goodwin Sands recommended Marine Conservation Zone (rMCZ).Seabed texture polygons mapped using semi automated ISO cluster unsupervised classification and expert interpretation of acoustic data (MBES bathymetry and backscatter) and groundtruthing data from PSA analysis and image (stills and video) classification.

  • JNCC requested that BGS carry out geostatistical analysis of sediment sample data from the CEND 8/12 survey of Swallow Sand MCZ and CEND 6/13 survey of South-west Deeps (West) MCZ in order to produce maps of sediment distribution in the sites. For each of the MCZ a geostatistical analysis of the data is reported leading to the selection of a robust linear model of corregionalization for the composition of the sediment, based on the additive log-ratio transformation of data on mud, sand and gravel content. This model is then used for spatial prediction on a 250-m grid. At each grid node a prediction distribution is obtained, conditional on neighbouring data and the selected model. By sampling from this distribution, and back-transforming onto the original compositional simplex of the data, we obtain a conditional expectation for the proportions of sand, gravel and mud at each location, a 95% confidence interval for the value at each node, and the probability that each of the four sediment texture classes that underly the EUNIS habitat classification is found at the node.

  • Broadscale habitat (EUNIS level 3) for Hythe Bay (rMCZ) recommended Marine Conservation Zone (rMCZ) Updated habitat map resulting from an intergrated analysis of the acoustic and ground-truth survey data from 2012. The ground-truthing survey was carried out by the Environment Agency (EA) on the 26th March 2012 using the MV Sea Vigil. The site is predominantly characterised as A5.3 Subtidal mud.

  • A geostatistical analysis of the data is reported leading to the selection of a linear model of corregionalization for the composition of the sediment, based on the additive log-ratio transformation of data on mud, sand and gravel content. This model is then used for spatial prediction on a 250-m grid. At each grid node a prediction distribution is obtained, conditional on neighbouring data and the selected model. By sampling from this distribution, and backtransforming onto the original compositional simplex of the data, we obtain a conditional expectation for the proportions of sand, gravel and mud at each location, a 95% confidence interval for the value at each node, and the probability that each of the four sediment texture classes that underlie the EUNIS habitat classification is found at the node.

  • Updated habitat map resulting from an integrated analysis of the 2013 dedicated survey data (collected on cruise CEND0613) for South West Deeps (West) recommended Marine Conservation Zone (rMCZ). A new habitat map for the site was produced by analysing and interpreting the available acoustic data and the ground-truth data collected by the dedicated surveys of South West Deeps West rMCZ. The process is a combination of two approaches, auto-classification (image analysis) and expert interpretation. The routine for auto-classification is flexible and dependent on site-specific data, allowing for application of a bespoke routine to maximise the acoustic data available. ArcGIS was used to perform an initial unsupervised classification on the supplied backscatter image. The single band backscatter mosaic was filtered and smoothed prior to the application of an Iso cluster/maximum likelihood classification routine. For further information, refer to the South-West Deeps (West) rMCZ Post-survey Site Report.

  • This it the updated broadscale habitat (BSH) map for the Whitsand and Looe Bay MCZ. Several BSH were identified as part of this map creation including: Infralittoral rock, moderate energy circalittoral rock, subtidal sand, subtidal mixed sediments, subtidal coarse sediment

  • Broadscale habitat (EUNIS level 3) for the Dover to Deal recommended Marine Conservation Zone (rMCZ).Seabed texture polygons mapped using expert interpretation of acoustic data (MBES bathymetry and backscatter) and groundtruthing data from PSA analysis and image (stills and video).

  • Updated habitat map resulting from an intergrated analysis of the acoustic and groundtruthsurvey data in 2014 (onboard the RV Cefas Endeavour). Sediment types at each groundtruthing station were used to inform a semi-automated process of map production using object-based image analysis (OBIA). The majority of the seabed was classified as 'A5.2 Subtidal sand', with patches of 'A5.1 Subtidal coarse sediment' and 'A5.4 Subtidal mixed sediments'.

  • Updated habitat map resulting from an integrated analysis of the dedicated 2012 survey data (CEND3/12b) for South East of Falmouth rMCZ. A new habitat map for the site was produced by analysing and interpreting the available acoustic data and the groundtruth data collected by the dedicated survey of this site. The process is a combination of two approaches, auto-classification (image analysis) and expert interpretation, as described below. The routine for auto-classification is flexible and dependent on site-specific data, allowing for application of a bespoke routine to maximise the acoustic data available. ArcGIS was used to perform an initial unsupervised classification on the supplied backscatter image. The single band backscatter mosaic was filtered and smoothed prior to the application of an Iso cluster/maximum likelihood classification routine. For further information, refer to the South-East Falmouth rMCZ Post-survey Site Report vs. 8 (Green, S. & Cooper, R., 2015).