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South Kerman region (IRAN) - Land cover map










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    Poster, banner
    Mazandaran province (IRAN) - Land cover map 2019
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    To implement the project Improved Agriculture Monitoring Systems through Satellite Imagery for Iran, three parts of the country were selected as pilot areas: Zanjan and Mazandaran provinces, and south Kerman region. For each area, some basic information was obtained, including crop calendars, statistics on the status of major agricultural products, political boundaries, land use, and land cover maps and climatic Agro-Ecological Zone (AEZ) maps. This poster shows the mapped province of Mazandaran. The process for developing it started from Sentinel-2 satellite images (period: 1 Jan- 31 Dec 2017). Preprocessing was performed using SNAp software. The NDVI was then calculated for each image for 12 months of the year. The map includes orchards, irrigated lands, water bodies, rangelands, and bare-area classes.
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    The Islamic Republic of IRAN - Land cover map (Zanjan province) poster 2019
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    To implement the project Improved Agriculture Monitoring Systems through Satellite Imagery for Iran, three parts of the country were selected as pilot areas: Zanjan and Mazandaran provinces, and south Kerman region. For each area, some basic information was obtained, including crop calendars, statistics on the status of major agricultural products, political boundaries, land use, and land cover maps and climatic Agro-Ecological Zone (AEZ) maps. This poster shows the mapped province of Zanjan. The process for developing it started from Sentinel-2 satellite images (period: 1 Jan- 31 Dec 2017). Preprocessing was performed using SNAp software. The NDVI was then calculated for each image for 12 months of the year. The map includes orchards, irrigated lands, water bodies, rangelands, and bare-area classes.
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    Land Cover Atlas of the Republic of South Sudan 2011
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    The Land Cover Atlas of the Republic of South Sudan provides information on the land cover distribution by administrative and sub-basin divisions. The dataset was created using the FAO/GLCN methodology and tools. Main data sources include satellite imagery from SPOT and Global Land Survey (GLS) Landsat, 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 South 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. A field veri fication was completed by national experts who received a customized training on methodology and tools. The final land cover product has around 100,000 polygons, classified into 43 different classes and eventually aggregated into 7 major classes for ease of analysis and display.

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