Classification of the seabed in the Atlantic Ocean into broad-scale benthic habitats employing a non-hierarchical top-down clustering approach aimed at informing Marine Spatial Planning. This work was performed at the University of Plymouth in 2021 with data provided by a wide group of partners representing the nations surrounding the Atlantic Ocean. It classifies continuous environmental data into discrete classes that can be compared to observed biogeographical patterns at various scales. It has 3 levels of classification. The numbers in the raster layer correspond to individual classes. Description of these classes is given in McQuaid, K.A. et al. (2023).

Species distribution models (GAM, Maxent and Random Forest ensemble) predicting the distribution of Syringammina fragilissima fields assemblage in the North East Atlantic. This community is considered ecologically coherent according to the cluster analysis conducted by Parry et al. (2015) on image sample. Modelling its distribution complements existing work on their definition and offers a representation of the extent of the areas of the North East Atlantic where they can occur based on the best available knowledge. This work was performed at the University of Plymouth in 2021.

Species distribution models (GAM, Maxent and Random Forest ensemble) predicting the distribution of discrete Lophelia pertusa - Desmophylum pertusum colonies assemblage in the Celtic Sea. This community is considered ecologically coherent according to the cluster analysis conducted by Parry et al. (2015) on image samples. Modelling its distribution complements existing work on their definition and offers a representation of the extent of the areas of the North East Atlantic where they can occur based on the best available knowledge. This work was performed at the University of Plymouth in 2021.

This data product selects sample areas of digital bathymetry, chosen for their relevance to marine activities and data sources alternative to GEBCO. The approach for building the digital map of water depth is to use GEBCO as a baseline and look at a set of sample areas where GEBCO could be improved upon. Sample areas have also been selected to be representative of each continent bordering the Atlantic and expected future requirements. Data sources include GEBCO, EMODNET, USGS and CHS.

This data was obtained through a partnership with IMF, as part of IMF's World Seaborne Trade Monitoring System (Cerdeiro, Komaromi, Liu and Saeed, 2020). The data analysis was supported by the World Bank’s ESMAP and PROBLUE programs. The dataset contains 6 density layers, with vessel types aggregated to suit the needs of the WBG Offshore Wind Development Program: 1) Commercial ships 2) Fishing ships 3) Oil & Gas [note: this is just platforms, rigs, and FPSOs] 4) Passenger ships 5) Leisure vessels 6) GLOBAL ship density layers of all ship categories combined

This product is a map of the uncertainty of available digital bathymetry measurements for the North Atlantic Ocean. This is done for a spatial resolution feasible for this large area (25km x 25km). It is designed to assess the quality of the bathymetry readings with a view to supporting assessments of future need. The product is formulated through a number of characteristics of the data including age of measurement and slope.

This dataset is the coastal zone land surface region from Europe, derived from the coastline towards inland, as a series of 10 consecutive buffers of 1km width each. The coastline is defined by the extent of the Corine Land Cover 2018 (raster 100m) version 20 accounting layer. In this version all Corine Land Cover pixels with a value of 523, corresponding to sea and oceans, were considered as non-land surface and thus were excluded from the buffer zone.

Coastal zones are presented as a series of 10 consecutive buffers of 1km width each (towards inland). For this dataset, were treated as sea data all areas with class values of 52x (521: coastal lagoons, 522: estuaries, 523: sea and ocean) in Corine Land Cover (details in lineage).