Dataset includes various regional-scale spatial data layers in geojson format.
Protected areas of Palau. Data sourced from: IUCN and UNEP-WCMC (2018), The World Database on Protected Areas (WDPA) [On-line], [July 2018]. Cambridge, UK: UNEP-WCMC. Available at: www.protectedplanet.net.
Bio-ORACLE is a set of GIS rasters providing geophysical, biotic and environmental data for surface and benthic marine realms. The data are available for global-scale applications at a spatial resolution of 5 arcmin (approximately 9.2 km at the equator).
Linking biodiversity occurrence data to the physical and biotic environment provides a framework to formulate hypotheses about the ecological processes governing spatial and temporal patterns in biodiversity, which can be useful for marine ecosystem management and conservation.
Data submitted to the UN Ozone Secretariat highlighting the trend of ODS consumption (calculated as Production (if any) + imports - exports) in Palau. Ozone Depleting Substances calculated here are HCFCs and Methal Bromide.
Location and distribution of MPAs on the east side of Babeldaob. Data obtained from WDPA dataset
Regional framework to assess the regional monitoring indicators that measure the status of managed conservation areas set aside under the Micronesia Challenge. The tool allows you to see the monitoring progress and learn more about the monitoring data collected across the region.
The World Database on Protected Areas (WDPA) is the most comprehensive global database of marine and terrestrial protected areas, updated on a monthly basis, and is one of the key global biodiversity data sets being widely used by scientists, businesses, governments, International secretariats and others to inform planning, policy decisions and management.
This dataset provides direct internet links to Palau's data hosted on the GBIF website/ records.
Dataset that provides a direct internet link to Palau's climate change data portal.
Shape file polygons-geojson
This dataset contains mapped point locations for protected areas within Palau. This dataset should be viewed in combination with the World Database on Protected Areas polygon locations to get a comprehensive view of all protected areas within Palau.
This dataset contains mapped polygon locations for protected areas within Palau. This dataset should be viewed in combination with the World Database on Protected Areas point locations to get a comprehensive view of all protected areas within Palau.
the link directly leads to the Republic of Palau's data on the Micronesia Challenge website
Dataset that provides a direct internet link to Palau's climate change data portal.
Pacific islands region land area
GIS file (geojson format) displaying protected areas in Palau.
direct link to Palau's data on the GBIF website
Raster data representing the mean levels of calcite 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 current velocities in meters/second 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 iron 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.