Soil bulk density (fine earth) 10 x kg / m-cubic at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution ...
Soil bulk density (fine earth) 10 x kg / m 3 at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution. Processing steps are described in detail here . Antarctica is not included. To access and visualize maps use: OpenLandMap.org If you discover a bug, artifact or inconsistency in the...
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Format: | Dataset |
Language: | English |
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Zenodo
2018
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Subjects: | |
Online Access: | https://dx.doi.org/10.5281/zenodo.2525665 https://zenodo.org/record/2525665 |
Summary: | Soil bulk density (fine earth) 10 x kg / m 3 at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution. Processing steps are described in detail here . Antarctica is not included. To access and visualize maps use: OpenLandMap.org If you discover a bug, artifact or inconsistency in the maps, or if you have a question please use some of the following channels: Technical issues and questions about the code: https://gitlab.com/openlandmap/global-layers/issues General questions and comments: https://disqus.com/home/forums/landgis/ All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention: sol = theme: soil, bulkdens.fineearth = variable: soil bulk density, usda.4a1h = determination method: laboratory method code, m = mean value, 250m = spatial resolution / block support: 250 m, b10..10cm = vertical reference: 10 cm depth below surface, 1950..2017 = time reference: period 1950-2017, v0.2 = version number: 0.2, ... : {"references": ["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", "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., 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."]} ... |
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