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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)Land use/land cover and forest cover mapping in Nigeria 2020
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No results found.Within the framework of a Technical Assistance (TA) Agreement (UTF/NIR/066/NIR), the Food and Agriculture Organization of the United Nations (FAO), provided technical support to the Federal Government of Nigeria to undertake a number of activities, which included land use/land cover analysis and production of an updated land cover/land use map for Nigeria. An existing national classification system, adopted by FORMECU in 1998, and comprising 36 classes was aggregated into 12 classes and used for this purpose. A land use/land cover map for 1995 based on the 12 classes was also produced. The land use/land cover analysis were undertaken in SEPAL and SEPAL-CEO (SEPAL-Collect Earth Online) which is an open-source, cloud-based platform. Map mosaics for 2006 and 2016 were produced from free Landsat images extracted from the SEPAL archives and classification was then undertaken to Collect Earth Online using the 12 aggregated land use/land cover classes. The procedure required the use of higher resolution images such as SPOT 5, GeoEye, and IKONOS images. A total of 1667 training data points were collected across the 12 land cover classes over the entire country. Fieldwork (ground-truthing) was carried out in six states to verify and clarify unresolved areas especially among savannas and arable land, tree crop plantation and forest plantation, freshwater forest and mangrove; and led to the collection of 252 additional training data points.
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