Earth System Science Data
Earth System Science Data
Earth System Science Data
Articles | Volume 16, issue 6
Articles | Volume 16, issue 6
https://doi.org/10.5194/essd-16-2941-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-2941-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 6
Data description paper
 | 
25 Jun 2024
Data description paper |  | 25 Jun 2024

BIS-4D: mapping soil properties and their uncertainties at 25 m resolution in the Netherlands

Anatol Helfenstein, Vera L. Mulder, Mirjam J. D. Hack-ten Broeke, Maarten van Doorn, Kees Teuling, Dennis J. J. Walvoort, and Gerard B. M. Heuvelink

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Latest update: 13 Dec 2024
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Short summary
Earth system models and decision support systems greatly benefit from high-resolution soil information with quantified accuracy. Here we introduce BIS-4D, a statistical modeling platform that predicts nine essential soil properties and their uncertainties at 25 m resolution in surface 2 m across the Netherlands. Using machine learning informed by up to 856 000 soil observations coupled with 366 spatially explicit environmental variables, prediction accuracy was the highest for clay, sand and pH.
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