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.

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.

This metadata corresponds to the EUNIS Littoral biogenic habitat (salt marshes) types, predicted distribution of habitat suitability dataset. Littoral habitats are those formed by animals such as worms and mussels or plants (salt marshes). The verified littoral biogenic habitat samples used are derived from the Braun-Blanquet database (http://www.sci.muni.cz/botany/vegsci/braun_blanquet.php?lang=en) which is a centralised database of vegetation plots and comprises copies of national and regional databases using a unified taxonomic reference database. The geographic extent of the distribution data are all European countries except Armenia and Azerbaijan. The modelled suitability for EUNIS saltmarsh habitat types is an indication of where conditions are favourable for the habitat type based on sample plot data (Braun-Blanquet database) and the Maxent software package. The modelled suitability map may be used as a proxy for the geographical distribution of the habitat type. However, note that it is not representing the actual distribution of the habitat type. As predictors for the suitabilty modelling not only Climate and Soil parameters have been taken into account, but also so-called RS-EVB's, Remote Sensing-enabled Essential Biodiversity Variables like Landuse, Vegetation height, Phenology, LAI(Leave Area Index) and Population density. Because the EBV's are restricted by the extent of the Remote Sensing data (EEA38 countries and the United Kingdom) the modelling result does also not go beyond this boundary. The dataset is provided both in Geodatabase and Geopackage formats. The Training map files show the modelled suitable distribution, omitting the 10% of occurrence records in the least suitable environment under the assumption that they are not representative of the overall suitable habitat distribution. The 10 percentile training presence is an arbitrary threshold which omits all regions with habitat suitability lower than the suitability values for the lowest 10% of occurrence records.

The dataset shows the percentage of cities' administrative area (core city based on the Urban Morphological Zones dataset) inundated by the sea level rise of 1 metre, without any coastal flooding defences present for a series of individual coastal European cities (included in Urban Audit). The dataset has been computed using the CReSIS (Centre for Remote Sensing of Ice Sheets) dataset for 2018.

This metadata corresponds to the EUNIS Littoral biogenic habitat types (salt marshes), distribution based on vegetation plot data dataset. Littoral biogenic habitats (commonly known as salt marshes) are formed by animals such as worms and mussels or plants. The verified saltmarsh habitat samples used are derived from the Braun-Blanquet database (http://www.sci.muni.cz/botany/vegsci/braun_blanquet.php?lang=en) which is a centralised database of vegetation plots and comprises copies of national and regional databases using a unified taxonomic reference database. The geographic extent of the distribution data are all European countries except Armenia and Azerbaijan. The dataset is provided both in Geodatabase and Geopackage formats.