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Maybe, this could be added to the SoilDataPrep documentation - some meta data on the TAXNWRB soil classes:
SoilGrids IDs and classes:
Codes and names:
ftp://ftp.soilgrids.org/legends/TAXNWRB.qml
(explanation: SoilDataPrep creates a tif-map called "soils_catchment", with the most probable soil class; only values are assigned to each pixel. Here you can find, which value is which FAO soil class.)
Maybe, this could be added to the SoilDataPrep documentation - some meta data on the TAXNWRB soil classes:
SoilGrids IDs and classes:
ftp://ftp.soilgrids.org/legends/TAXNWRB.qml
(explanation: SoilDataPrep creates a tif-map called "soils_catchment", with the most probable soil class; only values are assigned to each pixel. Here you can find, which value is which FAO soil class.)
ftp://ftp.soilgrids.org/data/recent/SoilGrids250m_TAXNWRB_legend_June_2016.pdf
ftp://ftp.soilgrids.org/legends/
Explanation & paper on SoilGrids:
https://www.isric.org/explore/soilgrids/
Global gridded soil information based on machine learning:
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0169748#pone.0169748.ref015
FAO legend & explanation of soil types:
http://www.fao.org/3/i3794en/I3794en.pdf
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