The raster dataset represents fishing intensity (kilowatt per fishing hour) by pelagic towed gears in the European seas. The dataset has been derived from Automatic Identification System (AIS) based pelagic fishing intensity data received from the European Commission’s Joint Research Centre - Independent experts of the Scientific, Technical and Economic Committee for Fisheries (JRC STECF), as well as from Vessel Monitoring System (VMS) and logbook based pelagic fishing effort data from HELCOM Commission. The temporal extent varies between the data sources (between 2013 and 2015). The dataset has been transformed to a logarithmic scale (ln1). This dataset has been prepared for the calculation of the combined effect index, produced for the ETC/ICM Report 4/2019 "Multiple pressures and their combined effects in Europe's seas" available on: https://www.eionet.europa.eu/etcs/etc-icm/etc-icm-report-4-2019-multiple-pressures-and-their-combined-effects-in-europes-seas-1.

Classification of the Atlantic Ocean seabed into broad-scale benthic habitats employing a 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. For ease of use, a layer is provided for each level. Level 1 has 4 classes. Level 2 has 15 classes nested within level 1. Layers indices are 2 digits (1[level1 class index]1[level 2 class index]). Level 3 has 157 classes nested within level 2 and class names have 4 digits (1digit[level1 class index]1[level 2 class index]2[level 3 class index]). Note that the classification was performed for the whole world and thus it has more classes than in the presented layer.

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 a class value of 523 (sea and ocean) in Corine Land Cover (details in lineage).

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).

The raster dataset represents the risk of collision of whales with vessels in Europe Seas. The most vulnerable species from ship strikes are cetaceans and turtles, since they go to the surface to breathe. On the other hand, their migration routes can overlap with shipping lanes. The collisions can produce the death or injury of the animals, and are an important threat for the conservation of these species. The dataset has been prepared in the context of the development of the first European Maritime Transport Environmental Report (EMSA-EEA report, 2021: https://www.eea.europa.eu/publications/maritime-transport).

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).

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.