Articles | Volume 6, issue 1
https://doi.org/10.5194/soil-6-35-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/soil-6-35-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Machine learning and soil sciences: a review aided by machine learning tools
José Padarian
CORRESPONDING AUTHOR
Sydney Institute of Agriculture & School of Life and Environmental Sciences, University of Sydney, Sydney, New South Wales, Australia
Budiman Minasny
Sydney Institute of Agriculture & School of Life and Environmental Sciences, University of Sydney, Sydney, New South Wales, Australia
Alex B. McBratney
Sydney Institute of Agriculture & School of Life and Environmental Sciences, University of Sydney, Sydney, New South Wales, Australia
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Latest update: 22 Nov 2024
Short summary
The application of machine learning (ML) has shown an accelerated adoption in soil sciences. It is a difficult task to manually review all papers on the application of ML. This paper aims to provide a review of the application of ML aided by topic modelling in order to find patterns in a large collection of publications. The objective is to gain insight into the applications and to discuss research gaps. We found 12 main topics and that ML methods usually perform better than traditional ones.
The application of machine learning (ML) has shown an accelerated adoption in soil sciences. It...