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Book (stand-alone)The Land Cover Atlas of Sudan 2012
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No results found.The Land Cover Atlas of Sudan provides information on the land cover distribution by administrative divisions. The dataset has been created using the FAO/GLCN methodology and tools. Main data sources include high resolution satellite imagery from SPOT, Landsat, IRS (Indian Satellite), Aster, existing Africover land cover database and ancillary data. The legend was prepared using the Land Cover Classification System (LCCS): 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. Satellite images of Sudan were segmented into homogeneous polygons and they were interpreted according to the FAO/GLCN methodology for the production of a seamless and detailed land cover dataset for the whole country. Field verification was complet ed by national experts who received a customized training on methodology and tools. The final land cover product has around 490,000 polygons, classified into 83 different classes and eventually aggregated into 7 major classes for ease of analysis and display. The Land Cover Atlas is organized into two main sections: country and states. Each section provides information on the distribution of aggregated land cover as map and table. These products provide the user with valuable information on the availability and distribution of land resources through a multifaceted approach. -
Book (stand-alone)Atlas of Malawi Land Cover and Land Cover Change 1990-2010 2012
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No results found.The Atlas of Malawi, land cover and land cover change (1990s-2010s) provides information on the land cover resources, their distribution and changes over time, at national, regional and district levels. The Atlas is published in 2013. The administrative unit layer as well as the water basin layer and a number of ancillary datasets was provided by the Land Resources and Development Department of the Ministry of Agriculture of Malawi. The land cover change database was prepared according to the FA O, Land and Water Division www.fao.org and Global Land Cover Network (GLCN) www.glcn.org land cover change mapping methodology; underpinned by the use of FAO/ISO standards and the Land Cover Mapping Toolbox. The national land cover legend was prepared using the Land Cover Classification System (LCCS): a FAO 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 c lassification uses a set of independent diagnostic criteria that allows the correlation with existing classifications and legends. -
Book (stand-alone)JORDAN - Land Cover Atlas 2019
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No results found.The Jordanian Land Cover Database and Atlas were developed under the Regional Food Security Analysis Network (RFSAN) project. The main objective of the project is to increase and improve provision of goods and services from agriculture, forestry and fisheries in a sustainable manner as well as to increase the understanding of the bio-physical conditions of land in Jordan. The Land Cover Atlas of the Hashemite Kingdom of Jordan provides information on the land cover distribution by sub-national administrative boundaries (governorates and districts) provided by the Royal Geographic Centre (RJGC). The Land Cover Database is compliant with the ISO\FAO standard (ISO 19144-2:2012) based on the land cover classification system (LCCS): Land Cover Meta Language (LCML). LCML was implemented to support the standardization and integration of a national land cover classification system across the world. It provides a set of standard diagnostic attributes that are independent of the scale of interpretation. Its use advocates for a more transparent and comparable way of reporting land cover information. The LCML land cover legend was designed with the software LCCSv3. The main data source includes multispectral Sentinel-2 imagery at 10 m of spatial resolution acquired from April to November 2016 and ancillary georeferenced data (land cover and land use map, vegetation cover, soil map) obtained from different institutions. Sentinel-2 imagery were pre-processed and mosaicked to provide a temporal sequence of free-cloud, calibrated images. Then, an Object-Based Image Analysis workflow was applied to segment the images into homogeneous polygons, that were interpreted according to their spectral, texture and shape characteristics supported by vegetation indices and ancillary datasets. Post-processing finally removed incoherent classifications, clipping and dissolving polygons to official boundaries. The final database comprises 1 million polygons classified according to the LCCS Legend distinguished into 34 classes (23 aggregated classes). The statistical analysis of land cover aggregated class distribution is organized into two sections: • National Land Cover Data Base (LCDB). • LCDB by governorates. This work represents a substantial contribution to understanding land cover and land processes in the Hashemite Kingdom of Jordan and provides valuable baseline data to further monitor land changes in the future.
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