Distribution of the USDA soil great groups based on machine learning predictions from global compilation of soil profiles (>350,000 training points). 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. Antarctica is not included. To access and visualize maps use: OpenLandMap.org A back-up copy of all predictions (>65GB) can be downloaded from: http://gofile.me/6J25n/mQ3cHOOMr 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...
iSDAsoil dataset soil texture classes derived from sand, silt and clay fractions at 30 m resolution ...
Soil texture classes (USDA system) for 6 standard soil depths (0, 10, 30, 60, 100 and 200 cm) at 250...
Soil water content (volumetric) in percent for 33 kPa and 1500 kPa suctions predicted at 6 standard ...
Distribution of the USDA soil great groups based on machine learning predictions from global compila...
Distribution of the USDA suborders based on machine learning predictions of great groups (https://do...
Distribution of the USDA orders (12) based on machine learning predictions of great groups (https://...
Sand content in % (kg / kg) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution...
This paper describes the technical development and accuracy assessment of the most recent and improv...
Global maps at 1 km spatial resolution of the predicted soil types (0–100% probabilities) at 1 km re...
Silt content in % (kg / kg) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution...
Publisher's PDFThis paper describes the technical development and accuracy assessment of the most r...
The SoilGrids system (www.soilgrids.org) uses machine learning algorithms to predict soil type and b...
Clay content in % (kg / kg) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution...
<p>observations used as calibration data for producing SoilGrids1km predictions [<a href="http://www...
Coarse fragments % (volumetric) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolu...
iSDAsoil dataset soil texture classes derived from sand, silt and clay fractions at 30 m resolution ...
Soil texture classes (USDA system) for 6 standard soil depths (0, 10, 30, 60, 100 and 200 cm) at 250...
Soil water content (volumetric) in percent for 33 kPa and 1500 kPa suctions predicted at 6 standard ...
Distribution of the USDA soil great groups based on machine learning predictions from global compila...
Distribution of the USDA suborders based on machine learning predictions of great groups (https://do...
Distribution of the USDA orders (12) based on machine learning predictions of great groups (https://...
Sand content in % (kg / kg) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution...
This paper describes the technical development and accuracy assessment of the most recent and improv...
Global maps at 1 km spatial resolution of the predicted soil types (0–100% probabilities) at 1 km re...
Silt content in % (kg / kg) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution...
Publisher's PDFThis paper describes the technical development and accuracy assessment of the most r...
The SoilGrids system (www.soilgrids.org) uses machine learning algorithms to predict soil type and b...
Clay content in % (kg / kg) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution...
<p>observations used as calibration data for producing SoilGrids1km predictions [<a href="http://www...
Coarse fragments % (volumetric) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolu...
iSDAsoil dataset soil texture classes derived from sand, silt and clay fractions at 30 m resolution ...
Soil texture classes (USDA system) for 6 standard soil depths (0, 10, 30, 60, 100 and 200 cm) at 250...
Soil water content (volumetric) in percent for 33 kPa and 1500 kPa suctions predicted at 6 standard ...