Earth System Science Data
Earth System Science Data
Earth System Science Data
Articles | Volume 16, issue 5
Articles | Volume 16, issue 5
https://doi.org/10.5194/essd-16-2367-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-2367-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 5
Data description paper
 | 
16 May 2024
Data description paper |  | 16 May 2024

European topsoil bulk density and organic carbon stock database (0–20 cm) using machine-learning-based pedotransfer functions

Songchao Chen, Zhongxing Chen, Xianglin Zhang, Zhongkui Luo, Calogero Schillaci, Dominique Arrouays, Anne Christine Richer-de-Forges, and Zhou Shi

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Short summary
A new dataset for topsoil bulk density (BD) and soil organic carbon (SOC) stock (0–20 cm) across Europe using machine learning was generated. The proposed approach performed better in BD prediction and slightly better in SOC stock prediction than earlier-published PTFs. The outcomes present a meaningful advancement in enhancing the accuracy of BD, and the resultant topsoil BD and SOC stock datasets across Europe enable more precise soil hydrological and biological modeling.
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