Litto3D provides 3D, continuous sea-land description of French coastal areas. Data is acquired by airborne topo-bathymetric LiDARs. Litto3D products come in 3D point clouds and digital terrain models formats. The product "Litto3D - Nouvelle-Aquitaine 2020-2022" covers the geographical area from the Charente-Maritime to the Spanish border. For the maritime part, the data produced by Shom extend offshore down to signal extinction, approximatively 20 depth when environmental conditions are optimal. On land, the data are truncated at a limit that ensures the product retain its coastal character.

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

The multispectral images of the study area were acquired by drone on 18 September 2025 using the DJI Mavic 3M RTK. The orthomosaic was generated from 5,128 images across five spectral bands (Green, Red, Red Edge, Near-Infrared (NIR), and Alpha), captured at an altitude of 100 meters (2025). The ground resolution achieved was 4.568 cm/pixel, covering a surveyed area of approximately 0.94 km². The Digital Surface Models (DSMs) were resampled to a resolution of 10 cm.

Digital Surface Models (DSMs) of the study area were generated by drones on 19 September 2024 and 18 September 2025. Each pixel represents the elevation value of the terrain at the time of the survey. These DSMs were generated from 895 (2024) and 1,282 images (2025), captured at an altitude of 120 (2024) and 100 meters (2025) using the DJI Mavic 3E RTK and Mavic 3M RTK drones, with ground resolutions of 3.19 (2024) and 2.63 cm/pixel (2025). The surveyed area covers approximately 1 km². The DSMs were resampled to a resolution of 20 cm. The vertical coordinate system used is NGF IGN69.

Digital Surface Models (DSMs) of the study area surveyed by drone between June 2024 and March 2025. Each pixel contains the elevation value corresponding to the terrain at the time of the mission. These DSMs were generated from around 1,300 images (depending of the survey) acquired using the DJI Mavic 3E RTK drone, with a resolution of 3.2 cm/pixel. The surveyed area covers around 2.1 km². The campaign was conducted on the highest tides of each month. The drone acquisitions were carried out by Nicolas Lachaussée from the LIENSs UMR Drone Platform. Photogrammetric processing was performed by Natacha Volto (LIENSs) using Agisoft Metashape software. The vertical coordinate system is NGF IGN69. The vertical accuracy (RMSD ~ 3 cm), calculated using around 100 control points, randomly distributed across the study area. It is derived from the vertical difference for each control point between the value measured with the DGPS SP80 and the value extracted from the photogrammetry-generated DSM. These drone surveys were carried out as part of the thesis of Loës Le Goff Le Gourrierec supervised by Xavier Bertin.

Bathymetric datasets are an extraction of surveys belonging to the Shom public database. For depth up to 50m, the vertical precision of soundings varies from 30cm to 1m and the horizontal precision varies from 1 to 20m. In deep ocean, the vertical precision is mainly around 1 or 2% of the bottom depth. It is sometimes more, it depends on the technology used. The data are referenced to ZH which is assimilated to LAT. Data are corrected for sound velocity variations. <br /> October 27 2025 version

Bathymetric datasets are an extraction of surveys belonging to the Shom public database. For depth up to 50m, the vertical precision of soundings varies from 30cm to 1m and the horizontal precision varies from 1 to 20m. In deep ocean, the vertical precision is mainly around 1 or 2% of the bottom depth. It is sometimes more, it depends on the technology used. The data are referenced to ZH which is assimilated to LAT. Data are corrected for sound velocity variations. <br /> October 27 2025 version

Bathymetric datasets are an extraction of surveys belonging to the Shom public database. For depth up to 50m, the vertical precision of soundings varies from 30cm to 1m and the horizontal precision varies from 1 to 20m. In deep ocean, the vertical precision is mainly around 1 or 2% of the bottom depth. It is sometimes more, it depends on the technology used. The data are referenced to ZH which is assimilated to LAT. Data are corrected for sound velocity variations. <br /> October 27 2025 version

Bathymetric datasets are an extraction of surveys belonging to the Shom public database. For depth up to 50m, the vertical precision of soundings varies from 30cm to 1m and the horizontal precision varies from 1 to 20m. In deep ocean, the vertical precision is mainly around 1 or 2% of the bottom depth. It is sometimes more, it depends on the technology used. The data are referenced to ZH which is assimilated to LAT. Data are corrected for sound velocity variations. <br /> October 27 2025 version

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.