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Link to download a zip file containing OSM spatial files, a QGIS project, styles, license file and documentation on how to get started.

Link to download a zip file containing OSM spatial files, a QGIS project, styles, license file and documentation on how to get started.

The Open Database License (ODbL) is a license agreement intended to
allow users to freely share, modify, and use this Database while
maintaining this same freedom for others. Many databases are covered by
copyright, and therefore this document licenses these rights. Some
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cover databases, and so the ODbL addresses these rights, too. Finally,
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act in certain ways in return for accessing this Database.

Link to download a zip file containing OSM spatial files, a QGIS project, styles, license file and documentation on how to get started.

Link to download a zip file containing OSM spatial files, a QGIS project, styles, license file and documentation on how to get started.

This is a link to the website to download the distribution of seagrass biome dataset.

This is a MaxEnt model map of the global distribution of the seagrass biome. Species occurrence records were extracted from the Global Biodiversity Information Facility (GBIF), United Nations Environment Programme-World Conservation Monitoring Centre (UNEP-WCMC) Ocean Data Viewer and Ocean biogeographic information system (OBIS). This map shows the suitable habitats for the seagrass distribution at global scale.

This is a link to the website to download the UNEP-WCMC global patterns of above-ground biomass of mangrove forests.

This is a link to the website to download the UNEP-WCMC distribution of corals dataset.

This is a link to the website to download the UNEP-WCMC distribution of cold-water corals dataset.

This dataset shows the global distribution of cold-water corals. Occurrence records are given for 86 Families under the subclass Octocorallia (octocorals; also known as Alcyonaria) and four Orders (in Class Anthozoa): Scleractinia (reef-forming corals), Antipatharia (black corals), Zoanthidae (encrusting or button polyps), and Pennatulacea (sea pens). Occurrence records are also available for the order sub-Order Filifera (lace corals) in Class Hydrozoa.

This dataset contains rasters and a metadata file for global mean monthly sea surface temperature (°C) from 2010-2019. Rasters are in WGS84 coordinate system (EPSG 4326). Sea surface temperature is the temperature of the top millimeter of the ocean's surface. Sea surface temperatures influence weather, including hurricanes, as well as plant and animal life in the ocean. Like Earth's land surface, sea surface temperatures are warmer near the equator and colder near the poles. Currents like giant rivers move warm and cold water around the world's oceans.

This dataset contains rasters and a metadata file for global mean monthly ocean chlorophyll concentration (mg/m3) from 2010-2019. Rasters are in WGS84 coordinate system (EPSG 4326) . Chlorophyll-a is the light-harvesting pigment found in all photosynthetic plants. Its concentration in the ocean is used as an index of phytoplankton biomass and, as such, is a key input to primary productivity models.

Zip file containing NetCDF files for both zonal and meridional current velocities (meters/second) for 5 day temporal resolution for the years 2000-2019 in the WGS84 coordinate system (EPSG:4326).

This is the report for the Reefs at Risk Revisited analysis. Reefs at Risk Revisited is a high-resolution update of the original global analysis, Reefs at Risk: A Map-Based Indicator of Threats to the World’s Coral Reefs. Reefs at Risk Revisited uses a global map of coral reefs at 500-m resolution, which is 64 times more detailed than the 4-km resolution map used in the 1998 analysis, and benefits from improvements in many global data sets used to evaluate threats to reefs (most threat data are at 1 km resolution, which is 16 times more detailed than those used in the 1998 analysis).

This dataset contains GIS data (raster and shapefiles) for the local threats to coral reefs: coastal development, integrated local, marine pollution, overfishing, and watershed pollution.

The Global Mangrove Watch (GMW) is a collaboration between Aberystwyth University (U.K.), solo Earth Observation (soloEO; Japan), Wetlands International the World Conservation Monitoring Centre (UNEP-WCMC) and the Japan Aerospace Exploration Agency (JAXA).

Conservation International, GRID-Arendal and Geoscience Australia recently collaborated to produce a map of the global distribution of seafloor geomorphic features. The global seafloor geomorphic features map represents an important contribution towards the understanding of the distribution of blue habitats. Certain geomorphic feature are known to be good surrogates for biodiversity. For example, seamounts support a different suite of species to abyssal plains.

GEBCO’s gridded bathymetric data set, the GEBCO_2020 grid, is a global terrain model for ocean and land at 15 arc-second intervals. It is accompanied by a Type Identifier (TID) Grid that gives information on the types of source data that the GEBCO_2020 Grid is based.

If the data sets are used in a presentation or publication then we ask that you acknowledge the source.This should be of the form: GEBCO Compilation Group (2020) GEBCO 2020 Grid (doi:10.5285/a29c5465-b138-234d-e053-6c86abc040b9)

Raster data representing the mean levels of chlorophyll in mg/m3 for the surface water layer. The data are available for global-scale applications at a spatial resolution of 5 arcmin (approximately 9.2 km at the equator).

Marine data layers for present conditions were produced with climate data describing monthly averages for the period 2000–2014, obtained from pre-processed global ocean re-analyses combining satellite and in situ observations at regular two- and three-dimensional spatial grids.

Raster data representing the mean levels of dissolved oxygen in µmol/m3 for the surface water layer. The data are available for global-scale applications at a spatial resolution of 5 arcmin (approximately 9.2 km at the equator).

Marine data layers for present conditions were produced with climate data describing monthly averages for the period 2000–2014, obtained from pre-processed global ocean re-analyses combining satellite and in situ observations at regular two- and three-dimensional spatial grids.