SoilGrids1km — Global Soil Information Based on Automated Mapping
Open accessAbstract
BACKGROUND: Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited spatial detail. METHODOLOGY/PRINCIPAL FINDINGS: We present SoilGrids1km--a global 3D soil information system at 1 km resolution--containing spatial predictions for a selection of soil properties (at six standard depths): soil organic carbon (g kg-1), soil pH, sand, silt and clay fractions (%), bulk density (kg m-3), cation-exchange capacity (cmol+/kg), coarse fragments (%), soil organic carbon stock (t ha-1), depth to bedrock (cm), World Reference Base soil groups, and USDA Soil Taxonomy suborders. Our predictions are based on global spatial prediction models which we fitted, per soil variable, using a compilation of major international soil profile databases (ca. 110,000 soil profiles), and a selection of ca. 75 global environmental covariates representing soil forming factors. Results of regression modeling indicate that the most useful covariates for modeling soils at the global scale are climatic and biomass indices (based on MODIS images), lithology, and taxonomic mapping units derived from conventional soil survey (Harmonized World Soil Database). Prediction accuracies assessed using 5-fold cross-validation were between 23-51%. CONCLUSIONS/SIGNIFICANCE: SoilGrids1km provide an initial set of examples of soil spatial data for input into global models at a resolution and consistency not previously available. Some of the main limitations of the current version of SoilGrids1km are: (1) weak relationships between soil properties/classes and explanatory variables due to scale mismatches, (2) difficulty to obtain covariates that capture soil forming factors, (3) low sampling density and spatial clustering of soil profile locations. However, as the SoilGrids system is highly automated and flexible, increasingly accurate predictions can be generated as new input data become available. SoilGrids1km are available for download via http://soilgrids.org under a Creative Commons Non Commercial license.
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Uptake of Se in the presence of sulfate and phosphate is suppressed.
“Uptake of Se in the presence of sulfate and phosphate is suppressed [34,167,178,179].”
From Selenium Cycling Across Soil-Plant-Atmosphere Interfaces: A Critical Review (2015) · cites this paper as [167]
The Results (Model fitting; page unavailable) list mapped soil properties, but not selenium uptake. Searches for selenium uptake with sulfate and phosphate, including sulphate and absorption, found no passage addressing suppression of Se uptake. The cited paper’s discussion of soil mapping does not establish this claim. (LLM, conf=0.76)
Experimental — accuracy not yet measured
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- Authors
- Hengl, T., de Jesus, J. M., MacMillan, R. A., Batjes, N. H., Heuvelink, G. B. M., Ribeiro, E., Samuel-Rosa, A., Kempen, B., Leenaars, J. G. B., Walsh, M. G., & Gonzalez, M. R.
- Affiliations
- ISRIC - World Soil Information (NL)
- Columbia University (US)
- ORCID
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2014-08-29
- Volume
- 9
- Issue
- 8
- Pages
- e105992
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC4149475
- OpenAlex
- W2130560194
- Cited by
- 1,268
- References
- 2
- Citations by year
- 2026: 67 · 2025: 93 · 2024: 106 · 2023: 111 · 2022: 138 · 2021: 146 · 2020: 123 · 2019: 142 · 2018: 121 · 2017: 97 · 2016: 78 · 2015: 39 · 2014: 3 · 2013: 1
- FWCI
- 55.55
- Type
- journal article
- Language
- en
- Update notices
- correction (2014-12-01)
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Socio-Environmental Systems Modeling (acceptedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
- Columbia Academic Commons (Columbia University)
- Funders
- U.S. Department of Agriculture
- Bill and Melinda Gates Foundation
- Alliance for a Green Revolution in Africa
- European Commission
- Chinese Academy of Sciences
- Institute of Soil Science, Chinese Academy of Sciences
- Comisión Nacional para el Conocimiento y Uso de la Biodiversidad, Gobierno de México
- Agriculture and Agri-Food Canada
- Joint Research Centre
- Topics
- Physical Sciences › Environmental Science › Environmental Engineering › Soil Geostatistics and Mapping
- Life Sciences › Agricultural and Biological Sciences › Soil Science › Soil and Environmental Studies
- Physical Sciences › Environmental Science › Management, Monitoring, Policy and Law › Soil and Land Suitability Analysis
- Keywords
- global soil mapping, soil properties, soil organic carbon, soil pH, soil texture, bulk density, cation exchange capacity, soil organic carbon stocks, bedrock depth, soil-forming factors, environmental variables, soil profile database, soil carbon sink
- MeSH terms
- Algorithms, Carbon, Cations, Conservation of Natural Resources, Environment, Geography, Hydrogen-Ion Concentration, Models, Theoretical, Soil, Logistic Models, Ecosystem, Geographic Information Systems, Carbon Sequestration
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