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Articles | Volume 8, issue 2
Articles | Volume 8, issue 2
https://doi.org/10.5194/soil-8-541-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/soil-8-541-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 8, issue 2
Original research article
 | 
24 Aug 2022
Original research article |  | 24 Aug 2022

On the benefits of clustering approaches in digital soil mapping: an application example concerning soil texture regionalization

István Dunkl and Mareike Ließ

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Latest update: 29 Oct 2025
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Short summary
Digital soil mapping (DSM) allows us to regionalize soil properties by relating them to environmental covariates with the help of an empirical model. Legacy soil data provide a valuable basis to generate high-resolution soil maps with DSM. We studied the usefulness of data-clustering methods to tackle potential sampling bias in legacy soil data while applying DSM for soil texture regionalization. Clustering has proved to be useful in various steps of the DSM process.
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