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GlobBiomass dataset of forest biomass, Africa (25 m)

Santoro, Maurizio; Cartus, Oliver


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{
  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  }, 
  "description": "<p>The dataset consists of a map of above ground forest biomass (AGB, unit: tons/ha i.e., Mg/ha) of the African continent for the year 2010 (raster dataset) with a pixel size of 25 m x 25 m. AGB is defined as the mass, expressed as oven-dry weight of the woody parts (stem, bark, branches and twigs) of all living trees excluding stump and roots. Per-pixel estimates of above-ground biomass uncertainty expressed as standard error in Mg/ha (raster dataset) are also provided.&nbsp;</p>\n\n<p>The AGB estimates were obtained from spaceborne SAR (ALOS PALSAR, Envisat ASAR), optical (Landsat-7), LiDAR (ICESAT), auxiliary datasets with multiple estimation procedures (Santoro et al., ESSDD, 2020).&nbsp;</p>\n\n<p>In this repository, the AGB data are available in form of tiles of 2&deg; x 2&deg; for the African continent (bounding box:&nbsp;longitude -26&deg;E/+56&deg;E latitude: -36&deg;N/+38&deg;N).</p>\n\n<p>This dataset is the basis for the&nbsp;official GlobBiomass dataset consisting of global estimates of forest biomass with 1 ha pixels (<a href=\"https://doi.pangaea.de/10.1594/PANGAEA.894711\">https://doi.pangaea.de/10.1594/PANGAEA.894711</a>). The dataset in this repository represents the original GlobBiomass dataset of AGB for Africa from which the official dataset was obtained after averaging from 25 m to 100 m.&nbsp;Given the lower accuracy of the 25 m pixel-based estimates, it is recommended to use the official GlobBiomass dataset&nbsp;unless detailed spatial resolution is a fundamental asset.&nbsp;</p>\n\n<p>Technical specifications are provided in the file README_GLOBBIOMASS_Africa_20210428.pdf</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Gamma Remote Sensing", 
      "@id": "https://orcid.org/0000-0002-3339-6991", 
      "@type": "Person", 
      "name": "Santoro, Maurizio"
    }, 
    {
      "affiliation": "Gamma Remote Sensing", 
      "@id": "https://orcid.org/0000-0002-6890-1548", 
      "@type": "Person", 
      "name": "Cartus, Oliver"
    }
  ], 
  "url": "https://zenodo.org/record/4725667", 
  "datePublished": "2018-04-28", 
  "keywords": [
    "forest", 
    "biomass", 
    "Africa", 
    "Earth Observation", 
    "remote sensing"
  ], 
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  "identifier": "https://doi.org/10.5281/zenodo.4725667", 
  "@id": "https://doi.org/10.5281/zenodo.4725667", 
  "@type": "Dataset", 
  "name": "GlobBiomass dataset of forest biomass, Africa (25 m)"
}
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