SOIL
SOIL
SOIL
Articles | Volume 4, issue 1
Articles | Volume 4, issue 1
https://doi.org/10.5194/soil-4-1-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/soil-4-1-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
Articles | Volume 4, issue 1
Original research article
 | 
10 Jan 2018
Original research article |  | 10 Jan 2018

Evaluation of digital soil mapping approaches with large sets of environmental covariates

Madlene Nussbaum, Kay Spiess, Andri Baltensweiler, Urs Grob, Armin Keller, Lucie Greiner, Michael E. Schaepman, and Andreas Papritz

Viewed

Total article views: 8,714 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
5,070 3,272 372 8,714 901 215 292
  • HTML: 5,070
  • PDF: 3,272
  • XML: 372
  • Total: 8,714
  • Supplement: 901
  • BibTeX: 215
  • EndNote: 292
Views and downloads (calculated since 09 May 2017)
Cumulative views and downloads (calculated since 09 May 2017)

Viewed (geographical distribution)

Total article views: 8,714 (including HTML, PDF, and XML) Thereof 7,996 with geography defined and 718 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 26 Nov 2025
Download
Short summary
This paper presents an extensive evaluation of digital soil mapping (DSM) tools. Recently, large sets of environmental covariates (e.g. from analysis of terrain on multiple scales) have become more common for DSM. Many DSM studies, however, only compared DSM methods using less than 30 covariates or tested approaches on few responses. We built DSM models from 300–500 covariates using six approaches that are either popular in DSM or promising for large covariate sets.
Read more
Share