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.

The MODIS 500-m global map of urban extent was produced by Annemarie Schneider at the University of Wisconsin-Madison, in partnership with Mark Friedl at Boston Univeristy and the MODIS Land Group. A new dataset has been developed depicting global urban land c. 2001-2002 based on Moderate Resolution Imaging Spectroradiometer (MODIS) 500-m satellite data.Methods exploit temporal and spectral information in one year of MODIS observations, classified using an ensemble decision tree classification approach.

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).

Area of dense human habitation. Derived from 2002-2003 MODIS satellite data at 1 km resolution: Schneider, A., M. A. Friedl, D. K. McIver, and C. E. Woodcock (2003) Mapping urban areas by fusing multiple sources of coarse resolution remotely sensed data. Photogrammetric Engineering and Remote Sensing, volume 69, pages 1377-1386.

The developed approach outputs a global raster layer representing both the spatial distribution and density of built-up areas, for the year 2010. The information about the presence of built-up is expressed as the percentage of built-up area respect to the total surface of the cell. Values are expressed in the range [0 to 100]. The layer is made available as a grid having a spatial resolution of 30-arc seconds (approximately 1 km at the equator), in the WGS84 coordinate system. Being available as a quantitative, continuous raster dataset significantly increases its value by facilitating integration with other spatial datasets for analysis or modeling The method uses machine learning techniques to understand the best population thresholds translating population densities to built-up densities. In the proposed methodology the MODIS Urban Land Cover (ULC) 500 m (C5) made by satellite data of the year circa 2001-2002 is used as training set for classification of the LandScan 2010 Global Population Database (LS). Similar techniques are described in Pesaresi et al. (2013) and Gueguen (2014) for the purpose of finding best rescaling parameters translating remote sensing image-derived features to a high-level-abstraction semantic as “built-up areas”.

World Cities provides a base map layer of the cities for the world. The cities include national capitals, provincial capitals, major population centers, and landmark cities.

The objective of the “Global Urban Footprint” (GUF) project is the worldwide mapping of settlements with unprecedented spatial resolution of 0.4 arcsec (~12 m). A total of 180 000 TerraSAR-X and TanDEM-X scenes have been processed to create the GUF. The resulting map shows the Earth in three colors only: black for “urban areas”, white for “land surface” and grey for “water”. This reduction emphasizes the settlement patterns and allows for the analysis of urban structures, and hence the proportion of settled areas, the regional population distribution and the arrangement of rural and urban areas. The Release of public domain GUF with ~2.8’’ (84m) spatial resolution for any non-profit use is planned in 2016.

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)

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.