Dataset Open Access
Tomislav Hengl;
Ichsani Wheeler
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. To convert to t/ha multiply by 10. Derived using soil organic carbon content (https://doi.org/10.5281/zenodo.1475457), bulk density (https://doi.org/10.5281/zenodo.1475970) and coarse fragments (https://doi.org/10.5281/zenodo.2525681), predicted from point data at 6 standard depths. Depth to bed rock has been ignored, hence total stocks might be about 10–15% lower then reported. Processing steps are described in detail here. Antarctica is not included.
To access and visualize maps use: https://openlandmap.org
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All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention:
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., Blagotić, 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
Hengl, T., MacMillan, R.A., (2019). Predictive Soil Mapping with R. OpenGeoHub foundation, Wageningen, the Netherlands, 370 pages, www.soilmapper.org, ISBN: 978-0-359-30635-0.
All versions | This version | |
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Views | 4,545 | 3,703 |
Downloads | 7,301 | 6,880 |
Data volume | 13.5 TB | 12.8 TB |
Unique views | 3,816 | 3,222 |
Unique downloads | 1,344 | 1,238 |