Articles | Volume 8, issue 2
SOIL, 8, 541–558, 2022
https://doi.org/10.5194/soil-8-541-2022
SOIL, 8, 541–558, 2022
https://doi.org/10.5194/soil-8-541-2022
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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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on soil-2020-102', Anonymous Referee #1, 05 May 2021
    • AC1: 'Reply on RC1', István Dunkl, 06 Jul 2021
  • RC2: 'Comment on soil-2020-102', Anonymous Referee #2, 04 Jun 2021
    • AC2: 'Reply on RC2', István Dunkl, 06 Jul 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (15 Nov 2021) by Bas van Wesemael
AR by István Dunkl on behalf of the Authors (23 Dec 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (17 Feb 2022) by Bas van Wesemael
RR by Anonymous Referee #2 (27 Feb 2022)
ED: Publish subject to minor revisions (review by editor) (23 May 2022) by Bas van Wesemael
AR by István Dunkl on behalf of the Authors (11 Jun 2022)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (16 Jun 2022) by Bas van Wesemael
ED: Publish as is (15 Jul 2022) by John Quinton(Executive Editor)
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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.