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 CCI-LC team has successfully produced and released its 3-epoch series of global land cover maps at 300m spatial resolution, where each epoch covers a 5-year period (2008-2012, 2003-2007, 1998-2002). These maps were produced using a multi-year and multi-sensor strategy in order to make use of all suitable data and maximize product consistency. The entire 2003-2012 MERIS Full and Reduced Resolution (FR and RR) archive was used as input to generate a 10-year 2003-2012 global land cover map. This 10-year product has then served as a baseline to derive the 2010, 2005 and 2000 maps using back- and up-dating techniques with MERIS and SPOT-Vegetation time series specific to each epoch.

The Global Land Cover-SHARE (GLC-SHARE) is a new land cover database at the global level created by FAO, Land and Water Division in partnership and with contribution from various partners and institutions. It provides a set of major thematic land cover layers resulting by a combination of “best available” high resolution national, regional and/or sub-national land cover databases with the weighted average land cover information derived from large-scale available datasets. The database is produced with a resolution of 30 arc second (1km). The approach implemented is based on the utilization of the Land Cover Classification System (LCCS) and SEEA (System of Environmental-Economic Accounting) legend systems for the harmonization of the various global, regional and national land cover legends. The major benefit of the GLC-SHARE product is its capacity to preserve the existing and available high resolution land cover information at the regional and country level obtained by spatial and multi-temporal source data, integrating them with the best synthesis of global datasets. Preliminary validation campaign was performed using 1000 random points statistically distributed over each land cover classes. The database is distributed in the following eleven layers, in raster format (GeoTIFF ), whose pixel values represent the percentage of density coverage in each pixel of the land cover type. The dominant layer, representing the value of the dominant land cover type, is also available along with a legend in LYR ESRI format. Finally, information on each layer's source is retrievable in sources layer, by joining the raster values with an Excel table.

The first 30 m resolution global land cover data set with 10 classes and for the year 2000 and 2010. Global Land Cover (GLC) information is fundamental for environmental change studies, land resource management, sustainable development, and many other societal benefits. Although GLC data exists at spatial resolutions of 300 m and 1000 m, a 30 m resolution mapping approach is now a feasible option for the next generation of GLC products. Since most significant human impacts on the land system can be captured at this scale, a number of researchers are focusing on such products. This paper reports the operational approach used in such a project, which aims to deliver reliable data products. Over 10,000 Landsat-like satellite images are required to cover the entire Earth at 30 m resolution. To derive a GLC map from such a large volume of data necessitates the development of effective, efficient, economic and operational approaches. Automated approaches usually provide higher efficiency and thus more economic solutions, yet existing automated classification has been deemed ineffective because of the low classification accuracy achievable (typically below 65%) at global scale at 30 m resolution. As a result, an approach based on the integration of pixel- and object-based methods with knowledge (POK-based) has been developed. Data citation: CHEN Jun et al.: 2015.Global land cover mapping at 30 m resolution: A POK-based operational approach. ISPRS Journal of Photogrammetry and Remote Sensing Volume 103, May 2015, Pages 7–27 http://dx.doi.org/10.1016/j.isprsjprs.2014.09.002 Available at: http://www.geodoi.ac.cn/WebEn/doi.aspx?Id=163

This data represents the 30 meters Digital Elevation Model (DEM) from Shuttle Radar Topography Mission (SRTM). This data-set was derived through mosaicking of individual SRTM tiles for a particular country and clipping the mosaicked tiles using the country boundary extent.