Articles | Volume 4, issue 2
https://doi.org/10.5194/soil-4-123-2018
© Author(s) 2018. 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-4-123-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Original research article
| 
29 May 2018
Original research article |
| 29 May 2018
| 29 May 2018
Uncertainty indication in soil function maps – transparent and easy-to-use information to support sustainable use of soil resources
Lucie Greiner
CORRESPONDING AUTHOR
Swiss Soil Monitoring Network (NABO), Agroscope, 8046 Zurich,
Switzerland
Madlene Nussbaum
School of Agricultural, Forest and Food Science (HAFL), Bern
University of Applied Sciences (BFH), 3052 Zollikofen, Switzerland
Andreas Papritz
Institute of Biogeochemistry and Pollutant Dynamics, Swiss Federal
Institute of Technology (ETH), 8092 Zurich, Switzerland
Stephan Zimmermann
Forest Soils and Biogeochemistry, Soil Functions and Soil Protection,
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), 8903
Birmensdorf, Switzerland
Andreas Gubler
Swiss Soil Monitoring Network (NABO), Agroscope, 8046 Zurich,
Switzerland
Adrienne Grêt-Regamey
Planning of Landscape and Urban Systems, Swiss Federal Institute of
Technology (ETH), 8093 Zurich, Switzerland
Armin Keller
Swiss Soil Monitoring Network (NABO), Agroscope, 8046 Zurich,
Switzerland
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Cited
17 citations as recorded by crossref.
- Identifying opportunities to improve digital soil mapping in India: A systematic review P. Dash et al. 10.1016/j.geodrs.2021.e00478
- How and to What Extent Does Topography Control the Results of Soil Function Assessment: A Case Study From the Alps in South Tyrol (Italy) F. Gruber et al. 10.3390/soilsystems3010018
- Stakeholder interpretation of probabilistic representations of uncertainty in spatial information: an example on the nutritional quality of staple crops C. Chagumaira et al. 10.1080/13658816.2021.2020278
- Soil assessment in Denmark: Towards soil functional mapping and beyond L. Gomes et al. 10.3389/fsoil.2023.1090145
- An Application of Information Theory to a Soil Map:: Implications for Soil Information Systems B. Murphy 10.2139/ssrn.4077504
- Assessment of soil multi-functionality to support the sustainable use of soil resources on the Swiss Plateau L. Greiner et al. 10.1016/j.geodrs.2018.e00181
- Evaluating pedotransfer functions for predicting soil bulk density using hierarchical mapping information in Campania, Italy P. Nasta et al. 10.1016/j.geodrs.2020.e00267
- Machine Learning With GA Optimization to Model the Agricultural Soil-Landscape of Germany: An Approach Involving Soil Functional Types With Their Multivariate Parameter Distributions Along the Depth Profile M. Ließ et al. 10.3389/fenvs.2021.692959
- Digital soil mapping of key secondary soil properties using pedotransfer functions and Indian legacy soil data N. Reddy & B. Das 10.1016/j.geoderma.2022.116265
- A multivariate approach for mapping a soil quality index and its uncertainty in southern France M. Angelini et al. 10.1111/ejss.13345
- A deep spectral prediction network to quantitatively determine heavy metal elements in soil by X-ray fluorescence Q. Zhang et al. 10.1039/D3JA00392B
- Joint Simulation of Spatially Correlated Soil Health Indicators, Using Independent Component Analysis and Minimum/Maximum Autocorrelation Factors A. Boluwade 10.3390/ijgi9010030
- Mapping the phosphorus sorption capacity of Danish soils in four depths with quantile regression forests and uncertainty propagation A. Møller et al. 10.1016/j.geoderma.2022.116316
- Multivariate random forest for digital soil mapping S. van der Westhuizen et al. 10.1016/j.geoderma.2023.116365
- Digital soil mapping and GlobalSoilMap. Main advances and ways forward D. Arrouays et al. 10.1016/j.geodrs.2020.e00265
- Ten challenges for the future of pedometrics A. Wadoux et al. 10.1016/j.geoderma.2021.115155
- Mapping Soil Biodiversity in Europe and the Netherlands M. Rutgers et al. 10.3390/soilsystems3020039
17 citations as recorded by crossref.
- Identifying opportunities to improve digital soil mapping in India: A systematic review P. Dash et al. 10.1016/j.geodrs.2021.e00478
- How and to What Extent Does Topography Control the Results of Soil Function Assessment: A Case Study From the Alps in South Tyrol (Italy) F. Gruber et al. 10.3390/soilsystems3010018
- Stakeholder interpretation of probabilistic representations of uncertainty in spatial information: an example on the nutritional quality of staple crops C. Chagumaira et al. 10.1080/13658816.2021.2020278
- Soil assessment in Denmark: Towards soil functional mapping and beyond L. Gomes et al. 10.3389/fsoil.2023.1090145
- An Application of Information Theory to a Soil Map:: Implications for Soil Information Systems B. Murphy 10.2139/ssrn.4077504
- Assessment of soil multi-functionality to support the sustainable use of soil resources on the Swiss Plateau L. Greiner et al. 10.1016/j.geodrs.2018.e00181
- Evaluating pedotransfer functions for predicting soil bulk density using hierarchical mapping information in Campania, Italy P. Nasta et al. 10.1016/j.geodrs.2020.e00267
- Machine Learning With GA Optimization to Model the Agricultural Soil-Landscape of Germany: An Approach Involving Soil Functional Types With Their Multivariate Parameter Distributions Along the Depth Profile M. Ließ et al. 10.3389/fenvs.2021.692959
- Digital soil mapping of key secondary soil properties using pedotransfer functions and Indian legacy soil data N. Reddy & B. Das 10.1016/j.geoderma.2022.116265
- A multivariate approach for mapping a soil quality index and its uncertainty in southern France M. Angelini et al. 10.1111/ejss.13345
- A deep spectral prediction network to quantitatively determine heavy metal elements in soil by X-ray fluorescence Q. Zhang et al. 10.1039/D3JA00392B
- Joint Simulation of Spatially Correlated Soil Health Indicators, Using Independent Component Analysis and Minimum/Maximum Autocorrelation Factors A. Boluwade 10.3390/ijgi9010030
- Mapping the phosphorus sorption capacity of Danish soils in four depths with quantile regression forests and uncertainty propagation A. Møller et al. 10.1016/j.geoderma.2022.116316
- Multivariate random forest for digital soil mapping S. van der Westhuizen et al. 10.1016/j.geoderma.2023.116365
- Digital soil mapping and GlobalSoilMap. Main advances and ways forward D. Arrouays et al. 10.1016/j.geodrs.2020.e00265
- Ten challenges for the future of pedometrics A. Wadoux et al. 10.1016/j.geoderma.2021.115155
- Mapping Soil Biodiversity in Europe and the Netherlands M. Rutgers et al. 10.3390/soilsystems3020039
Discussed (final revised paper)
Latest update: 14 Dec 2024
Short summary
To maintain the soil resource, spatial information on soil multi-functionality is key. Soil function (SF) maps rate soils potentials to fulfill a certain function, e.g., nutrient regulation. We show how uncertainties in predictions of soil properties generated by digital soil mapping propagate into soil function maps, present possibilities to display this uncertainty information and show that otherwise comparable SF assessment methods differ in their behaviour in view of uncertainty propagation.
To maintain the soil resource, spatial information on soil multi-functionality is key. Soil...
