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: Technical issues and questions about the code: https://github.com/Envirometrix/LandGISmaps/issues General questions and comments: https://disqus.com/home/forums/landgis/ All files internally compressed using "COMPRESS=DEFLATE" creation option in G...
iSDAsoil dataset soil texture classes derived from sand, silt and clay fractions at 30 m resolution ...
Silt content in % (kg / kg) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution...
Coarse fragments % (volumetric) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolu...
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://...
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...
Soil texture classes (USDA system) for 6 standard soil depths (0, 10, 30, 60, 100 and 200 cm) at 250...
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...
Publisher's PDFThis paper describes the technical development and accuracy assessment of the most r...
Global maps at 1 km spatial resolution of the predicted soil types (0–100% probabilities) at 1 km re...
Potential distribution of biomes (Potential Natural Vegetation) at 250 m spatial resolution based on...
<p>observations used as calibration data for producing SoilGrids1km predictions [<a href="http://www...
iSDAsoil dataset soil texture classes derived from sand, silt and clay fractions at 30 m resolution ...
Silt content in % (kg / kg) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution...
Coarse fragments % (volumetric) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolu...
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://...
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...
Soil texture classes (USDA system) for 6 standard soil depths (0, 10, 30, 60, 100 and 200 cm) at 250...
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...
Publisher's PDFThis paper describes the technical development and accuracy assessment of the most r...
Global maps at 1 km spatial resolution of the predicted soil types (0–100% probabilities) at 1 km re...
Potential distribution of biomes (Potential Natural Vegetation) at 250 m spatial resolution based on...
<p>observations used as calibration data for producing SoilGrids1km predictions [<a href="http://www...
iSDAsoil dataset soil texture classes derived from sand, silt and clay fractions at 30 m resolution ...
Silt content in % (kg / kg) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution...
Coarse fragments % (volumetric) at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolu...