The DOI matches its Crossref record; 96 of the 96 references it cites were found in a registry or an index.
SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty
Open accessAbstract
Abstract. SoilGrids produces maps of soil properties for the entire globe at medium spatial resolution (250 m cell size) using state-of-the-art machine learning methods to generate the necessary models. It takes as inputs soil observations from about 240 000 locations worldwide and over 400 global environmental covariates describing vegetation, terrain morphology, climate, geology and hydrology. The aim of this work was the production of global maps of soil properties, with cross-validation, hyper-parameter selection and quantification of spatially explicit uncertainty, as implemented in the SoilGrids version 2.0 product incorporating state-of-the-art practices and adapting them for global digital soil mapping with legacy data. The paper presents the evaluation of the global predictions produced for soil organic carbon content, total nitrogen, coarse fragments, pH (water), cation exchange capacity, bulk density and texture fractions at six standard depths (up to 200 cm). The quantitative evaluation showed metrics in line with previous global, continental and large-region studies. The qualitative evaluation showed that coarse-scale patterns are well reproduced. The spatial uncertainty at global scale highlighted the need for more soil observations, especially in high-latitude regions.
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Cites
WorldClim 2: new 1‐km spatial resolution climate surfaces for global land areas
Fick, S. E., & Hijmans, R. J. (2017) · International Journal of Climatology · doi:10.1002/joc.5086 · Cited by 16,088
High-Resolution Global Maps of 21st-Century Forest Cover Change
Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., Thau, D., Stehman, S. V., Goetz, S. J., Loveland, T. R., et al. (2013) · Science · doi:10.1126/science.1244693 · Cited by 11,704
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High-resolution mapping of global surface water and its long-term changes
Pekel, J.-F., Cottam, A., Gorelick, N., & Belward, A. S. (2016) · Nature · doi:10.1038/nature20584 · Cited by 5,513
SoilGrids250m: Global gridded soil information based on machine learning
Hengl, T., Mendes de Jesus, J., Heuvelink, G. B. M., Ruiperez Gonzalez, M., Kilibarda, M., Blagotić, A., Shangguan, W., Wright, M. N., Geng, X., Bauer-Marschallinger, B., et al. (2017) · PLOS ONE · doi:10.1371/journal.pone.0169748 · Cited by 4,733
Self-citationGeostatistics for Natural Resources Evaluation
Goovaerts, P. (1997) · doi:10.1093/oso/9780195115383.001.0001 · Cited by 4,449
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Climatologies at high resolution for the earth’s land surface areas
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Cited by
Global soil profiles indicate depth-dependent soil carbon losses under a warmer climate
Wang, M., Guo, X., Zhang, S., Xiao, L., Mishra, U., Yang, Y., Zhu, B., Wang, G., Mao, X., Qian, T., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-33278-w · Cited by 270
Dealing with clustered samples for assessing map accuracy by cross-validation
de Bruin, S., Brus, D. J., Heuvelink, G. B. M., van Ebbenhorst Tengbergen, T., & Wadoux, A. M. J.-C. (2022) · Ecological Informatics · doi:10.1016/j.ecoinf.2022.101665 · Cited by 122
Self-citationAgricultural input shocks affect crop yields more in the high-yielding areas of the world
Ahvo, A., Heino, M., Sandström, V., Chrisendo, D., Jalava, M., & Kummu, M. (2023) · Nature Food · doi:10.1038/s43016-023-00873-z · Cited by 78
“For that we used organic carbon density (hg m −3 ) from SoilGrid v2 35 for the topsoil (0–30 cm).”
MethodThe land–ocean Arctic carbon cycle
Vonk, J. E., Fritz, M., Speetjens, N. J., Babin, M., Bartsch, A., Basso, L. S., Bröder, L., Göckede, M., Gustafsson, Ö., Hugelius, G., et al. (2025) · Nature Reviews Earth & Environment · doi:10.1038/s43017-024-00627-w · Cited by 49
Qiu, H. (2023) · doi:10.5194/egusphere-2023-375-ac5
Metadata
- Authors
- Poggio, L., de Sousa, L. M., Batjes, N. H., Heuvelink, G. B. M., Kempen, B., Ribeiro, E., & Rossiter, D.
- Venue
- SOIL
- Publisher
- Copernicus GmbH
- Published
- 2021-06-14
- Volume
- 7
- Issue
- 1
- Pages
- 217-240
- ISSN
- 2199-3971 (ISSN-L)
- 2199-398X
- OpenAlex
- W3166420679
- Cited by
- 2,333
- References
- 96
- FWCI
- 91.48
- Type
- journal article
- Language
- en
- Open access
- gold
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- CoChat. (2026). Citation check: SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty. https://app.cochat.ai/papers/10.5194/soil-7-217-2021
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- Poggio, L., de Sousa, L. M., Batjes, N. H., Heuvelink, G. B. M., Kempen, B., Ribeiro, E., & Rossiter, D. (2021). SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty. SOIL. https://doi.org/10.5194/soil-7-217-2021
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