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Published November 2, 2018 | Version v0.1
Dataset Open

Predicted USDA soil great groups at 250 m (probabilities)

  • 1. Envirometrix Ltd
  • 2. US Geological Survey Ecosystems

Description

Distribution of the USDA soil great groups based on machine learning predictions from global compilation of soil profiles. To learn more about soil great groups please refer to the Illustrated Guide to Soil Taxonomy - NRCS - USDA. Processing steps are described in detail here. Antartica is not included.

To access and visualize maps use: OpenLandMap.org

If you discover a bug, artifact or inconsistency in the LandGIS maps, or if you have a question please use some of the following channels:

All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention:

  • sol = theme: soil,
  • grtgroup = variable: USDA great group,
  • usda.argiustolls = determination method: USDA soil taxonomy class Argiustolls,
  • p = probability,
  • 250m = spatial resolution / block support: 250 m,
  • s0..0cm = vertical reference: soil surface,
  • 1950..2017 = time reference: period 1950-2017,
  • v0.1 = version number: 0.1,

Files

landgis_soil_types_point_query.jpg

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Additional details

References

  • USDA-NRCS, (2014). Illustrated Guide to Soil Taxonomy: Version 1.0, September 20014, U.S. Department of Agriculture, Natural Resources Conservation Service, National Soil Survey Center.
  • Hengl T, Mendes de Jesus J, Heuvelink GBM, Ruiperez Gonzalez M, Kilibarda M, Blagotić A, et al. (2017) SoilGrids250m: Global gridded soil information based on machine learning. PLoS ONE 12(2): e0169748.
  • 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.