Comprises de location of fish species records within the Okavango Basin. Source: Africa Water Resources Database (FAO). This dataset is part of the GIS Database for the Environment Protection and Sustainable Management of the Okavango River Basin project (EPSMO). Detailed information on the database can be found in the “GIS Database for the EPSMO Project” document produced by Luis Veríssimo (FAO consultant) in July 2009, and here available for download.

A set of 2 features depicting the distribution of two important fish species (Clarias gariepinus and Pseudocrenilabrtus philander) within the Okavango Basin. Source: Africa Water Resources Database (FAO). This dataset is part of the GIS Database for the Environment Protection and Sustainable Management of the Okavango River Basin project (EPSMO). Detailed information on the database can be found in the “GIS Database for the EPSMO Project” document produced by Luis Veríssimo (FAO consultant) in July 2009, and here available for download.

Populated places including urbanized areas and villages within the Okavango Basin. Source: Digital Chart of the World (DCW). This dataset is part of the GIS Database for the Environment Protection and Sustainable Management of the Okavango River Basin project (EPSMO). Detailed information on the database can be found in the “GIS Database for the EPSMO Project” document produced by Luis Veríssimo (FAO consultant) in July 2009, and here available for download.

This dataset divides the South Sudan according to its hydrological characteristics: major hydrological basins and their sub-basins It identifies eighteen sub-basins as follows: Akoba, Bahr al arab, Buhayrat abyad, Gelha, Khawr biban, Khawr tunbak, Khawr_marchar, Kidepo, Kwahr as sidrah, Kwahr m’ boloko, Lake turkana, Lotagipi swamp, Sopo, Sue, White nile 3, White nile 4, White nile 5 and White nile 6. The dataset provides information on: numerical code and name of the major basin (MAJ_BAS and MAJ_NAME); - area of the major basin in square km (MAJ_AREA); and numerical code and name of the sub-basin (SUB_BAS and SUB_NAME). The dataset comes from the HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales) of the US Geological Survey. The USGS HydroSHEDS is based on high-resolution elevation data obtained during a Space Shuttle flight of NASA’s Shuttle Radar Topography Mission (SRTM). Around twenty-three sub-basins fall in the South Sudan area, including five sub-basins of which only a small portion is comprised. They are part of two main hydrological basins: the biggest part of the study area belongs to the Nile basin, while the eastern part of the area belongs to the Rift Valley basin. The delineation of the hydrological basins can be considered as the starting point in the analysis of the hydrological cycle to study surface water resources systems.

Global Map (resolution 30 arcsec) of SubSoil Organic Carbon Stock (30 - 100 cm depth). This dataset has been created by spatializing the information of over 17.000 soil samples from many databases (WISE3, USDA-NRCS- SOTER. ISRIC, University of Tuscia, SPADE, Russia, FAO et al.). Land Cover information comes from FAO GLC-SHARE Land Cover Database and the Harmonized Soil World Database (ver 1.21 - http://webarchive.iiasa.ac.at/Research/LUC/External-World-soil-database/HTML/). Soil Organic Carbon (SOC) stock in the map is represented as a continuous value and expressed in Mg/ha.

Global Map (resolution 30 arcsec) of TopSoil Organic Carbon Stock (0 - 30 cm depth). This dataset has been created by spatializing the information of over 23.500 soil samples from many databases (WISE3, USDA-NRCS- SOTER. ISRIC, University of Tuscia, SPADE, Russia, FAO et al.). Land Cover information comes from FAO GLC-SHARE Land Cover Database and the Harmonized Soil World Database (ver 1.21 - http://webarchive.iiasa.ac.at/Research/LUC/External-World-soil-database/HTML/). Soil Organic Carbon (SOC) stock in the map is represented as a continuous value and expressed in Mg/ha.

High-resolution, multi-purpose land cover products are available for a few countries only worldwide. The Africover Eastern Africa module (AFRICOVER) of the Global Land Cover Network (GLCN) initiative (www.glcn.org) produced detailed land cover maps for ten countries in Eastern Africa. The land cover database was created based on the visual on-screen interpretation of Landsat imagery in combination with in-situ validation data and expert knowledge. The land cover database includes the following ten countries: Burundi, Democratic Republic of Congo, Egypt, Eritrea, Kenya, Rwanda, Somalia, Sudan, United Republic of Tanzania and Uganda (FAO 1998). The Landsat images used for mapping were acquired between 1995 and 2001 and have been interpreted at a scale of 1:200,000 or 1:100,000 respectively for large or small countries. The legend used in AFRICOVER products is based on the Land Cover Classification System (LCCS). The full-resolution versions of the 10 datasets were used as input to derive circa 1-km grids of crop percentages. Land cover classes were first analysed at the level of polygon by using LCCS definitions, thereby deriving the minimum, maximum and mean crop percentage for each polygon. A ‘best estimate’ of crop percentage, normally but not always corresponding to the mean, was also established. Results were subsequently rasterized to an intermediate 100m-resolution product and finally aggregated to 1km resolution map. All types of crops are considered, including herbaceous, shrub and tree crops. A comparable product has been generated from the 2005 land cover of Senegal (GLCN, 2005)(Cropland extent in Senegal).