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ZENODO
Dataset . 2018
License: CC BY SA
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2018
License: CC BY SA
Data sources: Datacite
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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

Authors: Hengl, Tomislav;

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

Abstract

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. 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 here. Antartica is not included. To access and visualize maps use: https://landgis.opengeohub.org All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention: sol = theme: soil, organic.carbon.stock = variable: soil organic carbon stock in kg/m2, msa.kgm2 = determination method: derived from organic carbon content, bulk density and coarse fragments, m = mean value, 250m = spatial resolution / block support: 250 m, b0..10cm = vertical reference: 0-10 cm layer below surface, 1950..2017 = time reference: period 1950-2017, v0.2 = version number: 0.2,

{"references": ["Sanderman, J., Hengl, T., Fiske, G., (2017). The soil carbon debt of 12,000 years of human land use. PNAS, https://dx.doi.org/10.1073/pnas.1706103114", "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. https://doi.org/10.1371/journal.pone.0169748"]}

Keywords

LandGIS, soil carbon

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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