Predicted USDA soil suborders at 250 m (probabilities)
Distribution of the USDA suborders based on machine learning predictions of great groups (https://doi.org/10.5281/zenodo.1476844) from global compilation of soil profiles. To learn more about soil suborders and great groups please refer to the Illustrated Guide to Soil Taxonomy - NRCS - USDA. Proces...
| Main Authors: | , |
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| Format: | Dataset |
| Language: | English |
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2019
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| Subjects: | |
| Online Access: | https://zenodo.org/record/2657408 https://doi.org/10.5281/zenodo.2657408 |
| Summary: | Distribution of the USDA suborders based on machine learning predictions of great groups (https://doi.org/10.5281/zenodo.1476844) from global compilation of soil profiles. To learn more about soil suborders and 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 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, suborder = variable: USDA suborder, usda.ustolls = determination method: USDA soil taxonomy class Ustolls, 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 |
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