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Dataset Open Access

Soil organic carbon stock in kg/m2 for 5 standard depth intervals (0–10, 10–30, 30–60, 60–100 and 100–200 cm) at 250 m resolution

Tomislav Hengl

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        <foaf:name>Tomislav Hengl</foaf:name>
            <foaf:name>EnvirometriX Ltd</foaf:name>
    <dct:title>Soil organic carbon stock in kg/m2 for 5 standard depth intervals (0–10, 10–30, 30–60, 60–100 and 100–200 cm) at 250 m resolution</dct:title>
    <dct:issued rdf:datatype="">2018</dct:issued>
    <dcat:keyword>soil carbon</dcat:keyword>
    <dct:issued rdf:datatype="">2018-12-24</dct:issued>
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    <dct:description>&lt;p&gt;Soil organic carbon stock in kg/m2 for 5 standard depth intervals (0&amp;ndash;10, 10&amp;ndash;30, 30&amp;ndash;60, 60&amp;ndash;100 and 100&amp;ndash;200 cm) at 250 m resolution. Derived using soil organic carbon content, bulk density and coarse fragments, predicted from point data at 6 standard depths. Processing steps are described in detail &lt;strong&gt;&lt;a href=""&gt;here&lt;/a&gt;&lt;/strong&gt;. Antartica is not included.&lt;/p&gt; &lt;p&gt;To access and visualize maps use:&amp;nbsp;&lt;strong&gt;&lt;a href=""&gt;;/a&gt;&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;All files internally compressed using &amp;quot;COMPRESS=DEFLATE&amp;quot; creation&amp;nbsp;option in GDAL. File naming convention:&lt;/p&gt; &lt;ul&gt; &lt;li&gt;sol = theme: soil,&lt;/li&gt; &lt;li&gt;organic.carbon.stock = variable: soil organic carbon stock in kg/m2,&lt;/li&gt; &lt;li&gt;msa.kgm2 = determination method: derived from organic carbon content, bulk density and coarse fragments,&lt;/li&gt; &lt;li&gt;m = mean value,&lt;/li&gt; &lt;li&gt;250m = spatial resolution / block support: 250 m,&lt;/li&gt; &lt;li&gt;b0..10cm = vertical reference: 0-10 cm layer below surface,&lt;/li&gt; &lt;li&gt;1950..2017 = time reference: period 1950-2017,&lt;/li&gt; &lt;li&gt;v0.2 = version number: 0.2,&lt;/li&gt; &lt;/ul&gt;</dct:description>
    <dct:description xml:lang="">{"references": ["Sanderman, J., Hengl, T., Fiske, G., (2017). The soil carbon debt of 12,000 years of human land use. PNAS,", "Hengl, T., de Jesus, J.M., Heuvelink, G.B., Gonzalez, M.R., Kilibarda, M., Blagoti\u0107, A., Shangguan, W., Wright, M.N., Geng, X., Bauer-Marschallinger, B. and Guevara, M.A., (2017). SoilGrids250m: Global gridded soil information based on machine learning. PLoS one, 12(2), p.e0169748."]}</dct:description>
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        <rdfs:label>Open Access</rdfs:label>
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            <rdfs:label>Creative Commons Attribution Share Alike 4.0 International</rdfs:label>
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