Litto3D® marine part is a unique and continuous land-sea database which can provide 3D models of the shape and location of french coastal terrain. Surveys are carried out by airborne lidar bathymetry over the sea side and airborne lidar topography over the land side up to 400m inland. Litto3D® marine part digital models are available in two formats: a set of 3D points and a qualified terrain mesh. The partial product "Litto3D® marine part - Nouvelle-Aquitaine 2020-2022" covers the geographical area from the Sèvre Niortaise to the Ile d'Oléron and from the Gironde estuary to the Spanish border. It will be updated as treatment progresses. Eventually, the entire Nouvelle-Aquitaine coastline will be covered.

The EMODnet Bathymetry World Base Layer (EBWB) service is a gridded representation of worldwide bathymetric and topographic coverage adapted for a better representation of seabed morphological features. Based on modern WMTS schema, it allows a fluid and powerful rendering. For the global oceans EBWB1 is composed of the 2018 EMODnet Bathymetric grid around Europe (approx. 100m resolution) and uses the GEBCO 2019 grid (approx. 500m resolution) elsewhere in the marine environment. Land coverage is based on a combination of 30 arc second ASTER GDEM, SRTM3, EU-DEM, and Global 1 second world-wide water body map for the topographic part. This compilation of publicly available data sources have been merged and pre-tiled for rendering, at 10 levels of zoom starting from 1/24th of an arcminute (approx. 75m resolution). The EBWB1 service is available in non-projected system (Lat, Long, WGS84: EPSG:4086), Web Mercator (EPSG:3857), Inspire compliant ETRS-EALA projection (EPSG:3035) and projections adapted to both poles (ESPG 3031 and 3996) Service URL: https://tiles.emodnet-bathymetry.eu/wmts/1.0.0/WMTSCapabilities.xml

Source data for the EMODNet DTM for the Belgium Coastal Waters is compiled by the Vlaamse Hydrografie (http://www.afdelingkust.be/en/bathymetric-database) at a resolution of 1/512 arc minute. The data set covers dry coast and dunes along the Belgian coast.

Source data for the EMODNet DTM for the Belgium Coastal Waters is compiled by the Vlaamse Hydrografie (http://www.afdelingkust.be/en/bathymetric-database) at a resolution of 1/512 arc minute. The data set covers the waters along the Belgian coast.

Source data for the EMODNet DTM for the Belgium Coastal Waters is compiled by the Vlaamse Hydrografie (http://www.afdelingkust.be/en/bathymetric-database) at a resolution of 1/64 arc minute. The data set covers the waters along the Belgian coast.

Source data for the EMODNet DTM for the Belgium Continental Shelf (BCP) is compiled by the Vlaamse Hydrografie (https://www.agentschapmdk.be/en/hydrografische-data) at a resolution of 1/64'. The data set covers the Belgium Continental shelf area.

Source data for the EMODNet DTM for the Belgium Continental Shelf (BCP) is compiled by the Vlaamse Hydrografie (http://www.afdelingkust.be/en/bathymetric-database) at a resolution of 1/64". The data set covers the Belgium Continental shelf area.

Source data for the EMODNet DTM for the Belgium Continental Shelf (BCP) is compiled by the Vlaamse Hydrografie (http://www.afdelingkust.be/en/bathymetric-database) at a resolution of 1/64'. The data set covers the Belgium Continental shelf area.

The GEBCO_2019 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The grid uses as a base Version 1 of the SRTM15_plus data set (Sandwell et al). This data set is a fusion of land topography with measured and estimated seafloor topography. It is largely based on version 11 of SRTM30_plus (5). Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project, and from a number of international and national data repositories and regional mapping initiatives. The GEBCO_2019 Grid represents all data within the 2019 compilation. The compilation of the GEBCO_2019 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. The majority of the compilation was done using the remove-restore procedure (Smith and Sandwell, 1997; Becker, Sandwell and Smith, 2009 and Hell and Jakobsson, 2011). This is a two stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2019 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA).

Distribution of three bathymetric terrain variables (depth, slope and Bathymetric Position Index) on the North Atlantic (18°N to 76°N and 36°E to 98°W). This dataset originated from three source layers (3km * 3km resolution) computed within the work package 3 of EU ATLAS project, and based on the EMODnet Digital Bathymetry portal and the General Bathymetric Chart of the Oceans (GEBCO). From these source layers, the mean depth (m), slope (degree) and BPI (no unit) were calculated for each 25km * 25km gridsquare. This dataset was built to feed a basin-wide spatial conservation planning exercise, targeting the deep sea of the North Atlantic. The goal of this approach was to identify conservation priority areas for Vulnerable Marine Ecosystems (VMEs) and deep fish species, based on the distribution of species and habitats, human activities and current spatial management.