GlobCover is an ESA initiative which began in 2005 in partnership with JRC, EEA, FAO, UNEP, GOFC-GOLD and IGBP. The aim of the project was to develop a service capable of delivering global composites and land cover maps using as input observations from the 300m MERIS sensor on board the ENVISAT satellite mission. ESA makes available the land cover maps, which cover 2 periods: December 2004 - June 2006 and January - December 2009. For maximum user benefit the thematic legend of GlobCover is compatible with the UN Land Cover Classification System (LCCS). The system is based on an automatic pre-processing and classification chain. Both of the two global land cover maps (2005/2006 and 2009) provided in the framework of GlobCover have been validated by an international group of land cover experts and the validation reports were made available to the user community. Except for the global land cover maps, a set of MERIS by-products were also made freely available through the main data distribution source, ESA Ionia Server.

The Shuttle Radar Topography Mission (SRTM) was flown aboard the space shuttle Endeavour February 11-22, 2000. The National Aeronautics and Space Administration (NASA) and the National Geospatial-Intelligence Agency (NGA) participated in an international project to acquire radar data which were used to create the first near-global set of land elevations. Endeavour orbited Earth 16 times each day during the 11-day mission, completing 176 orbits. SRTM successfully collected radar data over 80% of the Earth's land surface between 60° north and 56° south latitude with data points posted every 1 arc-second (approximately 30 meters). SRTM Void Filled elevation data (at 3") are the result of additional processing to address areas of missing data or voids in the SRTM Non-Void Filled collection. The voids occur in areas where the initial processing did not meet quality specifications. Since SRTM data are one of the most widely used elevation data sources, the NGA filled the voids using interpolation algorithms in conjunction with other sources of elevation data. The resolution for SRTM Void Filled data is 1 arc-second for the United States and 3 arc-seconds for global coverage.

2010 estimates of total number of people per grid square across Africa South America and Asia, with national totals adjusted to match UN population division estimates, 2012 revision (http://esa.un.org/wpp/)

Landsat tm7 sensor. RGB raster map using bands 5-3-1. Date 2012-01-18. Edited in Grass GIS 7.2.2. Editings: - gdal_fillnodata for the satellite images from 2003 to 2018. - i.landsat.toar for DN to kind of reflectance transformation in order to later perform supervised classification of the imageries. - RGB raster map from bands 5-3-1. Image downloaded from www.earthexplorer.usgs.gov.

The GHSL Landsat is a spatial raster dataset that is mapping human settlements globally based on the Landsat satellite data collection. The GHSL Landsat uses the Global Land Survey (GLS) collection of Landsat imagery, which is a carefully coordinated collection of high resolution imagery for global modelling and is produced by the Global Land Cover Facility (www.landcover.org). This allows the mapping of settlements back in time until the year 1975. In addition, Landsat GHSL uses recent Landsat-8 from 2013/2014 for the latest coverage. The aggregated set has the coordinate Reference System: Spherical Mercator (EPSG:3857) and the spatial resolution of 38 m. This data is provided as single GEOTIFF file.

World Roads provides a base map layer for the roads and ferries of the world. They are a subset of DeLorme World Base Map 2015 (DWBM).

The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) consists of estimates of human population for the years 1990, 1995, and 2000 by 30 arc-second (1km) grid cells and associated data sets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 1,000,000 national and sub-national geographic units, is used to assign population values (counts, in persons) to grid cells. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT).

The GHSL Landsat is a spatial raster dataset that is mapping human settlements globally based on the Landsat satellite data collection. The GHSL Landsat uses the Global Land Survey (GLS) collection of Landsat imagery, which is a carefully coordinated collection of high resolution imagery for global modelling and is produced by the Global Land Cover Facility (www.landcover.org). This allows the mapping of settlements back in time until the year 1975. In addition, Landsat GHSL uses recent Landsat-8 from 2013/2014 for the latest coverage. GHS BUILT-UP GRID These data contain a multitemporal information layer on built-up presence as derived from Landsat image collections (GLS1975, GLS1990, GLS2000, and ad-hoc Landsat 8 collection 2013/2014). The data have been produced by means of Global Human Settlement Layer methodology in 2015. 250m of resolution - World Mollweide (EPSG:54009)

World Urban Areas represents the major urban areas of the world as shaded polygons.

Results from time-series analysis of Landsat images characterizing forest extent and change. Trees are defined as vegetation taller than 5m in height and are expressed as a percentage per output grid cell as ‘2000 Percent Tree Cover’. ‘Forest Cover Loss’ is defined as a stand-replacement disturbance, or a change from a forest to non-forest state, during the period 2000–2014. ‘Forest Cover Gain’ is defined as the inverse of loss, or a non-forest to forest change entirely within the period 2000–2012. ‘Forest Loss Year’ is a disaggregation of total ‘Forest Loss’ to annual time scales. Reference 2000 and 2014 imagery are median observations from a set of quality assessment-passed growing season observations. detailed information at: http://science.sciencemag.org/content/342/6160/850 This global dataset is divided into 10x10 degree tiles, consisting of seven files per tile. All files contain unsigned 8-bit values and have a spatial resolution of 1 arc-second per pixel, or approximately 30 meters per pixel at the equator.