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                <gco:CharacterString>See the referenced specification</gco:CharacterString>
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                <gco:Boolean>true</gco:Boolean>
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        <gco:CharacterString>This product is developed within the Copernicus Global Land Cover and Tropical Forest Mapping and Monitoring service (LCFM), which is part of the Copernicus Land Monitoring Service (CLMS). It is mainly based on data from Copernicus Sentinel-2 satellites and a pantropical training dataset. The product is generated based on a CatBoost tree-based model.

The primary input consists of Sentinel-2 L2A optical imagery with surface reflectance data at 10m-20m resolution. An additional cloud masking is applied on these data based on a deep learning algorithm. Annual features are generated from these input data sources to ensure consistent coverage despite cloud cover and other data gaps.

An extensive pantropical training database containing precise samples distributed across all biomes and environmental conditions has been collected. A sampling tool developed for tree cover density training data collection that combines image segmentation and Machine Learning for efficient collection over large areas has been employed.</gco:CharacterString>
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        </mcc:MD_Scope>
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        <mmi:MD_MaintenanceFrequencyCode codeList="http://standards.iso.org/iso/19115/resources/Codelists/cat/codelists.xml#MD_MaintenanceFrequencyCode" codeListValue="asNeeded" />
      </mmi:maintenanceAndUpdateFrequency>
    </mmi:MD_MaintenanceInformation>
  </mdb:metadataMaintenance>
</mdb:MD_Metadata>

