Predicted USDA soil great groups at 250 m (probabilities)
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 detai...
| Main Authors: | , |
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| Format: | Dataset |
| Language: | English |
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2018
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| Subjects: | |
| Online Access: | https://zenodo.org/record/3528062 https://doi.org/10.5281/zenodo.3528062 |
| Summary: | 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: https://disqus.com/home/forums/landgis/ 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, v0.2 = version number: 0.2 |
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