1378 results

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.

Raster data representing the mean levels of nitrate 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.

Raster data representing the mean levels of phosphate 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.

Raster data representing the mean levels of phytoplankton 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.

Raster data representing the mean levels of salinity in practical salinity scale (PSS) 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 silicate 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.

Raster data representing the mean levels of temperature in degrees Celsius (°C) 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.

The Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11 consists of estimates of human population density (number of persons per square kilometer) based on counts consistent with national censuses and population registers, for the years 2000. A proportional allocation gridding algorithm, utilizing approximately 13.5 million national and sub-national administrative units, was used to assign population counts to 30 arc-second grid cells.

The Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11 consists of estimates of human population density (number of persons per square kilometer) based on counts consistent with national censuses and population registers, for the year 2005. A proportional allocation gridding algorithm, utilizing approximately 13.5 million national and sub-national administrative units, was used to assign population counts to 30 arc-second grid cells.

The Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11 consists of estimates of human population density (number of persons per square kilometer) based on counts consistent with national censuses and population registers, for the year 2010. A proportional allocation gridding algorithm, utilizing approximately 13.5 million national and sub-national administrative units, was used to assign population counts to 30 arc-second grid cells.

The Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11 consists of estimates of human population density (number of persons per square kilometer) based on counts consistent with national censuses and population registers, for the year 2015. A proportional allocation gridding algorithm, utilizing approximately 13.5 million national and sub-national administrative units, was used to assign population counts to 30 arc-second grid cells.

 SPREP

In the 30th SPREP meeting held in September this year, the meeting supported the scaling up of environment data management in the Pacific and directed the Secretariat to initiate a process for developing a full-sized project proposal to support the scaling up environmental data management work in the region.

Later in October,  the Inform Project participating countries collectively agree on the need to scale up and extend the Inform Project services beyond 2022.

 SPREP

In the 30th SPREP meeting held in September this year, the meeting supported the scaling up of environment data management in the Pacific and directed the Secretariat to initiate a process for developing a full-sized project proposal to support the scaling up environmental data management work in the region.

Later in October,  the Inform Project participating countries collectively agree on the need to scale up and extend the Inform Project services beyond 2022.