Based on: A. Verhegghen, P. Defourny, "A new 300 m vegetation map for Central Africa based on multi-sensor times series", Third Recent Advance in Quantitative Remote Sensing, J.A. Sobrino (Ed.), Publicaciones de la Universitat de Valencia,Valencia, Spain, 2010.608 Vegetation types of 8 countries in Central Africa have been mapped thanks to a semi-automatic processing method based on temporal and spectral information from 19 months of ENVISAT MERIS FRS observation and 8 years of SPOT VEGETATION time series. The approach is based on a previous 1-km mapping effort for the Democratic Republic of Congo and on the lessons learnt from the ESA-GlobCover project. A land cover map with 20 vegetation classes was produced in five major steps: data compositing, seasonal stratification of the study zone, unsupervised classifications, automatic labelling and manual editing. The floristic composition and physiognomy of each vegetation type are described using the Land Cover Classification System developed by the FAO. This mapping exercise will be a reference document to deliver area estimates of the different forest types in a consistent way for DRCongo, Gabon, Cameroon, Equatorial Guinea, Central African Republic, Congo, Rwanda and Burundi. For the display of the NFMS portal, the original data has been reprojected to "latlong" projection, cropped, and masked for the area of the DRC.

This land cover dataset provides information on the land cover distribution by administrative divisions. The dataset was created using the FAO/GLCN methodology and tools. The land cover mapping was carried out with the interpretation of an integrated coverage of GLS Landsat satellite images (2000 and circa 2005-2007) acquired for the whole extent of South Sudan, and improved with updated higher resolution SPOT images (2006-2008) covering the agricultural areas. This approach was adopted to emphasize the land cover features in the agricultural production areas which were derived from the existing Africover Sudan data base dated circa 2002. The legend was prepared using the Land Cover Classification System (LCCS*). The country land cover dataset is split in administrative divisions which include the following states: Central Equatoria, Eastern Equatoria, Jonglei, Lakes Northern Bahr el Ghazal, Unity, Upper Nile, Warrap, Western Bahr el Ghazal, Western Equatoria. *LCCS is a comprehensive, standardized a priori classification system, designed to meet specific user requirements and created for mapping exercises, independent of the scale or means used to map. The classification uses a set of independent diagnostic criteria that allows the correlation with existing classifications and legends.

The dataset is based on the "Atlas of forest cover and change 2000-2010 in the Democratic Republic of the Congo”, produced as a part of the OSFAC initiative “Monitoring the forests of Central Africa using remotely sensed data sets” (FACET in French). The FACET forest classification provides a thematic simple map of relatively few forest cover types. Mapping the occurrence and type of forest cover change is the first step in identifying and analyzing the drivers of deforestation such as agriculture, logging and charcoal production. Citation information for the data Prepared by: Observatoire satellital des forêts d’Afrique centrale (OSFAC), South Dakota State University (SDSU), University of Maryland (UMD), © OSFAC, 2010.

This dataset of sub-basins comes from the USGS HydroSHEDS layers and identifies the following eighteen sub-basins: 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 HydroSHEDS are hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales of the US Geological Survey. The USGS HydroSHEDS layer 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.

This land cover dataset provides information on the land cover distribution by sub-basin divisions. The dataset was created using the FAO/GLCN methodology and tools. The land cover mapping was carried out with the interpretation of an integrated coverage of GLS Landsat satellite images (2000 and circa 2005-2007) acquired for the whole extent of South Sudan, and improved with updated higher resolution SPOT images (2006-2008) covering the agricultural areas. This approach was adopted to emphasize the land cover features in the agricultural production areas which were derived from the existing Africover Sudan data base dated circa 2002. The legend was prepared using the Land Cover Classification System (LCCS*). The sub-basins division of the land cover comes from the South Sudan hydrological basins layer (USGS HydroSHEDS) which identifies the following nineteen sub-basins: Akoba, Bahr al arab, Baro Wenz, 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 LCCS is a comprehensive, standardized a priori classification system, designed to meet specific user requirements and created for mapping exercises, independent of the scale or means used to map. The classification uses a set of independent diagnostic criteria that allows the correlation with existing classifications and legends.

This dataset divides the Australian continent in major hydrological basins and their sub-basins according to its hydrological characteristics. It was obtained by delineating drainage basin boundaries from hydrologically corrected elevation data (WWF HydroSHEDS and Hydro1K). The dataset consists of the following information:- numerical code and name of the major basin (MAJ_BAS and MAJ_NAME); - area of the major basin in square km (MAJ_AREA); - numerical code and name of the sub-basin (SUB_BAS and SUB_NAME); - area of the sub-basin in square km (SUB_AREA); - numerical code of the sub-basin towards which the sub-basin flows (TO_SUBBAS) (the codes -888 and -999 have been assigned respectively to internal sub-basins and to sub-basins draining into the sea)

Version 1.1 of a thematic grid of Land Use Systems (LUS) and its attributes for East Asia and Pacific with a spatial resolution of 5 arc minutes or 0.083333 decimal degrees. This dataset is developed in the framework of the LADA project (Land degradation Assessment in Drylands) by the Land Tenure and Management Unit of the Food and Agriculture Organization of the United Nations and is copyright of FAO/UNEP GEF. The LUS map implementation is based on a innovative methodology combining more than 10 global datasets. Due to the map generation method, the quality of the map can never be uniform. The overall quality of the map depends heavily on the individual quality of the data for the different countries.

Version 1.1 of a thematic grid of Land Use Systems (LUS) and its attributes for Sub-Saharan Africa with a spatial resolution of 5 arc minutes or 0.083333 decimal degrees. This dataset is developed in the framework of the LADA project (Land degradation Assessment in Drylands) by the Land Tenure and Management Unit of the Food and Agriculture Organization of the United Nations and is copyright of FAO/UNEP GEF. The LUS map implementation is based on a innovative methodology combining more than 10 global datasets. Due to the map generation method, the quality of the map can never be uniform. The overall quality of the map depends heavily on the individual quality of the data for the different countries.

Version 1.1 of a thematic grid of Land Use Systems (LUS) and its attributes with a spatial resolution of 5 arc minutes or 0.083333 decimal degrees. This dataset is developed in the framework of the LADA project (Land degradation Assessment in Drylands) by the Land Tenure and Management Unit of the Food and Agriculture Organization of the United Nations and is copyright of FAO/UNEP GEF. The LUS map implementation is based on a innovative methodology combining more than 10 global datasets. Due to the map generation method, the quality of the map can never be uniform. The overall quality of the map depends heavily on the individual quality of the data for the different countries.

Total number of fire occurrences, calculated using data from the MODIS satellite (products MOD14A2 and MYD14A2, "Thermal Anomalies and Fire", https://lpdaac.usgs.gov/products/modis_products_table/myd14a2). In each pixel of the derived map (1-kilometer resolution), the total is based time-series based on 8-daily tiles, one for each MODIS product. Fire occurrence is recorded if it occurs at least in one of the two products. Each time-series step is based on 9 MODIS tiles: (name,lonmin, latmin, lonmax, latmax): 'h19v08',1111950.519667,1111950.519667,2223901.039333,-0.000000; 'h19v09',1111950.519667,-0.000000,2223901.039333,-1111950.519667; 'h19v10',1111950.519667,-1111950.519667,2223901.039333,-2223901.039333; 'h20v08',2223901.039333,1111950.519667,3335851.559000,-0.000000; 'h20v09',2223901.039333,-0.000000,3335851.559000,-1111950.519667; 'h20v10',2223901.039333,-1111950.519667,3335851.559000,-2223901.039333; 'h21v08',3335851.559000,1111950.519667,4447802.078667,-0.000000; 'h21v09',3335851.559000,-0.000000,4447802.078667,-1111950.519667; 'h21v10',3335851.559000,-1111950.519667,4447802.078667,-2223901.039333; The initial maps derived from MODIS products were concatenated, re-projected, and converted to uint8. In addition, only the data within the DRC borders were retained.