Systematic comparison of five machine-learning models in classification and interpolation of soil particle size fractions using different transformed data
Mo Zhang,Wenjiao Shi,and Ziwei Xu
Mo Zhang
Key Laboratory of Land Surface Pattern and Simulation, State Key
Laboratory of Resources and Environmental Information System, Institute of
Geographic Sciences and Natural Resources Research, Chinese Academy of
Sciences, Beijing 100101, China
School of Earth Sciences and Resources, China University of
Geosciences, Beijing 100083, China
Key Laboratory of Land Surface Pattern and Simulation, State Key
Laboratory of Resources and Environmental Information System, Institute of
Geographic Sciences and Natural Resources Research, Chinese Academy of
Sciences, Beijing 100101, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Ziwei Xu
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Viewed
Total article views: 5,401 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
4,036
1,240
125
5,401
495
137
160
HTML: 4,036
PDF: 1,240
XML: 125
Total: 5,401
Supplement: 495
BibTeX: 137
EndNote: 160
Views and downloads (calculated since 06 Jan 2020)
Cumulative views and downloads
(calculated since 06 Jan 2020)
Total article views: 4,834 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
3,740
978
116
4,834
320
124
143
HTML: 3,740
PDF: 978
XML: 116
Total: 4,834
Supplement: 320
BibTeX: 124
EndNote: 143
Views and downloads (calculated since 14 May 2020)
Cumulative views and downloads
(calculated since 14 May 2020)
Total article views: 567 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
296
262
9
567
175
13
17
HTML: 296
PDF: 262
XML: 9
Total: 567
Supplement: 175
BibTeX: 13
EndNote: 17
Views and downloads (calculated since 06 Jan 2020)
Cumulative views and downloads
(calculated since 06 Jan 2020)
Viewed (geographical distribution)
Total article views: 5,401 (including HTML, PDF, and XML)
Thereof 5,023 with geography defined
and 378 with unknown origin.
Total article views: 4,834 (including HTML, PDF, and XML)
Thereof 4,494 with geography defined
and 340 with unknown origin.
Total article views: 567 (including HTML, PDF, and XML)
Thereof 529 with geography defined
and 38 with unknown origin.
We systematically compared 45 models for direct and indirect soil texture classification and soil particle size fraction interpolation based on 5 machine-learning models and 3 log-ratio transformation methods. Random forest showed powerful performance in both classification of imbalanced data and regression assessment. Extreme gradient boosting is more meaningful and computationally efficient when dealing with large data sets. The indirect classification and log-ratio methods are recommended.
We systematically compared 45 models for direct and indirect soil texture classification and...
