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PresentationLesotho Land Cover (2017–2021) Dashboard. A Google Earth engine dashboard to monitor land cover change and land degradation 2022
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Book (stand-alone)Introductory course to Google Earth Engine 2022
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No results found.FAO Pakistan in collaboration with the FAO headquarters Geospatial Unit is inviting to an introductory course on Google Earth Engine with the objective to provide the basic skills to operate the platform, select, pre-process and analyze satellite imagery relevant to agriculture and food security, in particular for the identification of specific crops in the land and more broadly for land cover mapping, by using an automatic classification approach. The Workshop is thought for specialists in the technical Departmental Units of Agriculture and Food Security. It requires an understanding of the main satellite missions and basic concepts of Remote Sensing. Limited knowledge of scripting language (e.g. Python, R) is a plus. It has the structure of a theoretical presentation and hands-on exercises on the Google Earth Engine code editor. -
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.
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