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        <identifier>oai:library.wur.nl:wurpubs/631663</identifier>
        <datestamp>2026-04-20</datestamp>
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          <dc:creator>Masolele, R.N.</dc:creator>
          <dc:creator>Marcos, Diego</dc:creator>
          <dc:creator>de Sy, Niki</dc:creator>
          <dc:creator>Abu, Itohan-Osa</dc:creator>
          <dc:creator>Verbesselt, J.</dc:creator>
          <dc:creator>Reiche, J.</dc:creator>
          <dc:creator>Herold, M.</dc:creator>
          <dc:type>Dataset</dc:type>
          <dc:title>Land use following deforestation for Africa</dc:title>
          <dc:date>2024</dc:date>
          <dc:description xml:lang="en">These datasets were generated from the research article "Mapping the diversity of land uses following deforestation across Africa". Here we publish the yearly time series maps showing land use following deforestation across Africa at 30 m resolution covering the year 2001 to 2020 (20 years). The maps are derived from Planet-NICFI images using U-Net deep neural network architecture enhanced with attention. The original landuse maps are derived from 5 m resolution Planet-NICFI imagery (research license with Planet Labs Inc) of 2022. The Planet-NICFI imagery are accessible upon sign up at https://www.planet.com/nicfi/ or https://developers.planet.com/docs/integrations/gee/nicfi/ The landuse dataset has fifteen classes with values ranging from 1 -15, where 1: Larger-scale cropland, 2: Pasture, 3: Mining, 4: Small-scale cropland, 5: Roads, 6: Other land with tree cover, 7: Plantation forest, 8: Coffee, 9: Settlement, 10: Tea plantation, 11: Water, 12: Oil palm, 13: Rubber, 14: Cashew, 15: Cacao</dc:description>
          <dc:description xml:lang="nl">Data Description These datasets were generated from the research article "Mapping the diversity of land uses following deforestation across Africa". Here we publish the yearly time series maps showing land use following deforestation across Africa at 30 m resolution covering the year 2001 to 2020 (20 years). The maps are derived from Planet-NICFI images using U-Net deep neural network architecture enhanced with attention. The original landuse maps are derived from 5 m resolution Planet-NICFI imagery (research license with Planet Labs Inc) of 2022. The Planet-NICFI imagery are accessible upon sign up at https://www.planet.com/nicfi/ or https://developers.planet.com/docs/integrations/gee/nicfi/ The landuse dataset has fifteen classes with values ranging from 1 -15, where 1: Larger-scale cropland, 2: Pasture, 3: Mining, 4: Small-scale cropland, 5: Roads, 6: Other land with tree cover, 7: Plantation forest, 8: Coffee, 9: Settlement, 10: Tea plantation, 11: Water, 12: Oil palm, 13: Rubber, 14: Cashew, 15: Cacao The data is accompanied by the sld and qml file (Visualisation_layer_descriptor_sld_and_qml) to aid in visualisation or legend creation. Data Visualisation at 5 m resolution: https://robertnag82.users.earthengine.app/view/africalu File Naming: LandUseFollowingDeforestation_dl_30m_20010101_20201231_af_epsg.4326_v1.tif Generic variable name: LandUseFollowingDeforestation Method of data production: dl (Deep learning) Spatial support in m: 30m Time reference begin time (YYYYMMDD): i.e. 20010101 Time reference end time: 20201230 Bounding box (2 letters max): af (Refering to Africa) EPSG code: epsg.4326 Version code: v1 JSON field representing the legend. This is important for the visualization of the legend. [ { "Large-scale cropland": "1", "color": "#FFFF00" }, { "Pasture": "2", "color": "#808080" }, { "Mining": "3", "color": "#FFC0CB" }, { "Small-scale cropland": "4", "color": "#F39C12" }, { "Roads": "5", "color": "#800000" }, { "Other land with tree cover/Regrowth ": "6", "color": "#008000" }, { "Plantation forest": "7", "color": "#808000" }, { "Coffee": "8", "color": "#008080" }, { "Settlement": "9", "color": "#FF0000" }, { "Tea plantation": "10", "color": "#3CB371" }, { "Water": "11", "color": "#0000FF" }, { "Oil palm": "12", "color": "#FF00FF" }, { "Rubber": "13", "color": "#4B0082" }, { "Cashew": "14", "color": "#00FF00" }, { "Cocoa": "15", "color": "#00FFFF" } ] Data Use Agreement The datasets are restricted to non-commercial purposes or purposes indicated in the licence document. This include the rights to: (i) use, access, and view Content through the Platform; (ii) download, reproduce, store, display, and print Content; and (iii) create Derivative Products; all for Licensee's own internal, non-commercial business purposes and those are the only rights that are extended. More information on the licence can be accessed here: https://assets.planet.com/docs/ToS_NICFI_GeneralPartners_level2.pdf The user agrees to assume all risks and liabilities associated with the interpretation and use of any data or results obtained from the datasets. Wageningen University, Planet-NICFI, Planet Labs Inc, and any affiliated parties shall not be held liable for any consequences arising from the misuse of the data.</dc:description>
          <dc:publisher>Wageningen University &amp; Research</dc:publisher>
          <dc:format>text/html</dc:format>
          <dc:identifier>https://research.wur.nl/en/datasets/land-use-following-deforestation-for-africa</dc:identifier>
          <dc:identifier>10.5281/zenodo.11065704</dc:identifier>
          <dc:relation>https://edepot.wur.nl/661677</dc:relation>
          <dc:subject xml:lang="en">Life Science</dc:subject>
          <dc:rights>Wageningen University &amp; Research</dc:rights>
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