35 results
 SPREP Environmental Monitoring and Governance (EMG)

Dataset includes various regional-scale spatial data layers in geojson format.

 Secretariat of the Pacific Regional Environment Programme

GEBCO's aim is to provide the most authoritative publicly-available bathymetry of the world's oceans. It operates under the joint auspices of the International Hydrographic Organization(IHO) and the Intergovernmental Oceanographic Commission (IOC) (of UNESCO).

GEBCO produces and makes available a range of bathymetric data sets and products. This includes a global bathymetric grid; gazetteer of undersea feature names, a Web Map Service and printable maps of ocean bathymetry.

 Secretariat of the Pacific Regional Environment Programme

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.

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 Secretariat of the Pacific Regional Environment Programme

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, 2005, 2010, 2015, and 2020. 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.

 Department of Environment, Climate Change & Emergency Management (DECEM), FSM

FSM Protected Areas (PA) data from the World Database on Protected Areas (WDPA), downloaded August 2019. This dataset includes both tables and spatial data.

 Department of Environment, Climate Change & Emergency Management (DECEM), FSM

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey.
The dataset is included the Digital Atlas of Micronesia, module Pohnpei, by Island Research & Education Initiative (iREi), in collaboration with Water and Environmental Research Institute of the Western Pacific (WERI) University of Guam and partial funding from United States Geological Survey (USGS), under WRRI 104-B Program, project # 2016GU302B.

 Department of Environment, Climate Change & Emergency Management (DECEM), FSM

This dataset the extent of coral reefs around Pohnpei. The data layer shown here is a subset of Pohnpei base layer. The original data, so-called Digital Line Graphs (DLSs), were created by U.S. Geological Survey (USGS) for the 1:25,000-scale topographic maps (2001). The shoreline was modified by by University of Guam (UOG) (2017) based on 2016 Worldview-3 satellite imagery from Digital Globe. The dataset was slightly shifted and also updated (mainly around Kolonia and its vicinity).

 Department of Environment, Climate Change & Emergency Management (DECEM), FSM

This dataset shows the extent and basic types of sea grass areas around Pohnpei. It classifies sea grass areas by one of the three main species (Cymodocea rotundata, Thalassia hemprichii, and Enhalus acaroides) and the level of coverage (describes as continuous, aggregated, and isolated). The data source is McKenzie, L.J. and Rasheed, M.J. (2006), Seagrasses: Pohnpei Island and And Atoll Marine Assessment, Technical report of survey conducted 26 October 3 November 2005, SeagrassWatch HQ, DPI&F, Cairns, 60pp.

 Department of Environment, Climate Change & Emergency Management (DECEM), FSM

This dataset shows the areas of biological significance (ABS) on Pohnpei. The original dataset was created by The Nature Conservancy. A subset to show only Pohnpei was created by the Island Research & Education Initiative (iREi). These data are intended to capture those areas that represent the wide range of biodiversity features in the marine and terrestial areas of FSM. They are used to guide conservation planning and projects in FSM, and ultimately to help establish conservation areas. Polygons capturing expert knowledge from FSM Blueprint project.

 The Nature Conservancy

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. The WDPA is a joint project between UN Environment and the International Union for Conservation of Nature (IUCN).

 Department of Environment, Climate Change & Emergency Management (DECEM), FSM

The population was compiled from available census reports and validated using other available datasets. For each country, population counts from the finest resolution was trended to 2010 using a country-specific annual growth rate assumptions. Underlying vector geometry comes from regional sources, primarily SPC.
Primary Data Source(s): PopGIS, Federated States of Micronesia Division of Statistics
Secondary Data Source(s): None
Geographical Resolutions Available (with count):
1. State (4)
2. Municipality (421)
3. Electoral District (373)

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.

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 2020. 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.

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 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 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.