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  • The development of the 2020 national land cover map of Sudan is an important step towards the REDD+ readiness as well as Sudan’s Forest Monitoring System (SFMS). The 2020 land cover map has been developed using 10 m spatial resolution, open-source satellite data, employing an object-based classification approach. The processing was implemented in the Google Earth Engine (GEE), cloud computing environment using 10 m spatial resolution Sentinel-1 and Sentinel-2 data. Use of GEE leverages the use of terabytes of satellite imagery and geospatial datasets. The workflow is mostly reproducible and based on the use of open-source software/platforms (e.g., R, SEPAL, etc.). The methodological approach for land cover mapping takes into consideration the time constraint of the project and comparative advantage and respective technical expertise of FAO and Forests National Corporation (FNC). Descriptions of the legend classes were translated using the land cover classification system (LCCS v3) – an implementation tool of the ISO standard (ISO 19144-2) Land Cover Meta Language (LCML). You can download a zip archive containing: -the shape file in gdb file -legends in lccs file

  • The Lesotho Land Cover Database (LCDB) and ATLAS have been prepared in the framework of the FAO Emergency Program (OSRO/LES/401/EC): “Building Lesotho resilience through the upscale of Climate Smart Agriculture and functional DRR Land Resources Information”. The national Land Cover Legend was prepared using the FAO (ISO standard) Land Cover Classification System (LCCS): a FAO’s 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 shape file's attributes contain the following fields: -ID -Area (km2) -LCS3Code (unique LCCS code) You can download a zip archive containing: -the shape file (.shp)