Articles | Volume 6, issue 2
https://doi.org/10.5194/soil-6-269-2020
© 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-6-269-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Original research article
| 
14 Jul 2020
Original research article |
| 14 Jul 2020
| 14 Jul 2020
Oblique geographic coordinates as covariates for digital soil mapping
Anders Bjørn Møller
CORRESPONDING AUTHOR
Department of Agroecology, Aarhus University, Tjele, 8830, Denmark
Amélie Marie Beucher
Department of Agroecology, Aarhus University, Tjele, 8830, Denmark
Nastaran Pouladi
Department of Agroecology, Aarhus University, Tjele, 8830, Denmark
Mogens Humlekrog Greve
Department of Agroecology, Aarhus University, Tjele, 8830, Denmark
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- Mapping benthic sediment types and composition in a turbid Jamaican bay using hydroacoustic data and different spatially explicit interpolation techniques K. McLaren 10.1016/j.rsma.2024.103655
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- Downscaling satellite soil moisture for landscape applications: A case study in Delaware, USA D. Warner et al. 10.1016/j.ejrh.2021.100946
- The patchiness of soil 13C versus the uniformity of 15N distribution with geomorphic position provides evidence of erosion and accelerated organic matter turnover M. Ghotbi et al. 10.1016/j.agee.2023.108616
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- Using local ensemble models and Landsat bare soil composites for large-scale soil organic carbon maps in cropland T. Broeg et al. 10.1016/j.geoderma.2024.116850
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Latest update: 21 Nov 2024
Short summary
Decision trees have become a widely adapted tool for mapping soil properties in geographic space. However, it is problematic to implement spatial relationships in the models. We present a new method which uses geographic coordinates along several axes tilted at oblique angles in the models. We test this method on four spatial datasets. The results show that the new method is at least as accurate as other proposed alternatives, has a computational advantage and is flexible and interpretable.
Decision trees have become a widely adapted tool for mapping soil properties in geographic...
