Articles | Volume 6, issue 2
https://doi.org/10.5194/soil-6-371-2020
© 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-6-371-2020
© 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 Aug 2020
Original research article |
| 14 Aug 2020
| 14 Aug 2020
Comparing three approaches of spatial disaggregation of legacy soil maps based on the Disaggregation and Harmonisation of Soil Map Units Through Resampled Classification Trees (DSMART) algorithm
Yosra Ellili-Bargaoui
CORRESPONDING AUTHOR
UMR SAS, INRAE, Institut Agro,Rennes, France
INTERACT, UniLaSalle, Beauvais, France
Brendan Philip Malone
Agriculture and Food, CSIRO, Canberra, ACT, Australia
Didier Michot
UMR SAS, Institut Agro, INRAE, Rennes, France
Budiman Minasny
Sydney Institute of Agriculture, School of Life and Environmental
Sciences, The University of Sydney, NSW, Australia
Sébastien Vincent
UMR SAS, INRAE, Institut Agro,Rennes, France
Christian Walter
UMR SAS, Institut Agro, INRAE, Rennes, France
Blandine Lemercier
UMR SAS, Institut Agro, INRAE, Rennes, France
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Cited
18 citations as recorded by crossref.
- The accuracy of soil information influences assessment of soil ecosystem services in Brittany, France Y. Ellili-Bargaoui et al. https://doi.org/10.1016/j.geodrs.2023.e00704
- Using a fuzzy logic approach to reveal soil-landscape relationships produced by digital soil maps in the humid tropical region of East Java, Indonesia D. Cahyana et al. https://doi.org/10.1016/j.geodrs.2021.e00468
- Factors Influencing the Spatial Distribution of Regulating Agro-Ecosystem Services in Agriculture Soils: A Case Study of Slovakia J. Makovníková et al. https://doi.org/10.3390/agriculture13050970
- Assessment of six soil ecosystem services by coupling simulation modelling and field measurement of soil properties Y. Ellili-Bargaoui et al. https://doi.org/10.1016/j.ecolind.2020.107211
- Hand-feel soil texture observations to evaluate the accuracy of digital soil maps for local prediction of soil particle size distribution: A case study in Central France A. RICHER-de-FORGES et al. https://doi.org/10.1016/j.pedsph.2022.07.009
- Disaggregation of conventional soil maps: a review A. Lázaro-López et al. https://doi.org/10.1071/SR20288
- Remote Sensing Data for Digital Soil Mapping in French Research—A Review A. Richer-de-Forges et al. https://doi.org/10.3390/rs15123070
- Multiscale evaluations of global, national and regional digital soil mapping products in France B. Lemercier et al. https://doi.org/10.1016/j.geoderma.2022.116052
- Sampling and classifier modification to DSMART for disaggregating soil polygon maps T. Easher et al. https://doi.org/10.1016/j.geoderma.2023.116360
- Digital soil mapping outputs on soil classification and sugarcane production in Brazil W. Mendes & J. Demattê https://doi.org/10.1016/j.jsames.2022.103881
- Mapping soil properties at multiple depths from disaggregated legacy soil maps in the Brittany region, France Y. Ellili-Bargaoui et al. https://doi.org/10.1016/j.geodrs.2020.e00342
- Evaluating Conventional and Digital Soil Mapping for Updating Soil Maps in Iran: Opportunities, Challenges, and Implications for Sustainable Land Management S. Sani & R. Kharazmi https://doi.org/10.1134/S1064229325604433
- Pruned hierarchical Random Forest framework for digital soil mapping: Evaluation using NEON soil properties C. Xu et al. https://doi.org/10.1016/j.geoderma.2025.117392
- Does Increasing Number of Field Observations Necessarily Improve the Performance of an ML-Based Soil Parent Material Prediction? T. Takáts et al. https://doi.org/10.1007/s41748-026-01134-2
- Digital disaggregation of soil subgroups using DSMART in a Mediterranean semiarid landscape Y. Turgut et al. https://doi.org/10.1038/s41598-026-48899-0
- The nature of information and the implication for making predictions about soil properties using soil maps B. Murphy https://doi.org/10.1016/j.soilad.2024.100025
- Comparing disaggregation approaches DSMART and PPD in disaggregating soil series maps T. EASHER et al. https://doi.org/10.1016/j.pedsph.2023.12.004
- Exploring the untapped potential of hand-feel soil texture data for enhancing digital soil mapping: Revealing hidden spatial patterns from field observations A. Eymard et al. https://doi.org/10.1016/j.geoderma.2023.116769
18 citations as recorded by crossref.
- The accuracy of soil information influences assessment of soil ecosystem services in Brittany, France Y. Ellili-Bargaoui et al. https://doi.org/10.1016/j.geodrs.2023.e00704
- Using a fuzzy logic approach to reveal soil-landscape relationships produced by digital soil maps in the humid tropical region of East Java, Indonesia D. Cahyana et al. https://doi.org/10.1016/j.geodrs.2021.e00468
- Factors Influencing the Spatial Distribution of Regulating Agro-Ecosystem Services in Agriculture Soils: A Case Study of Slovakia J. Makovníková et al. https://doi.org/10.3390/agriculture13050970
- Assessment of six soil ecosystem services by coupling simulation modelling and field measurement of soil properties Y. Ellili-Bargaoui et al. https://doi.org/10.1016/j.ecolind.2020.107211
- Hand-feel soil texture observations to evaluate the accuracy of digital soil maps for local prediction of soil particle size distribution: A case study in Central France A. RICHER-de-FORGES et al. https://doi.org/10.1016/j.pedsph.2022.07.009
- Disaggregation of conventional soil maps: a review A. Lázaro-López et al. https://doi.org/10.1071/SR20288
- Remote Sensing Data for Digital Soil Mapping in French Research—A Review A. Richer-de-Forges et al. https://doi.org/10.3390/rs15123070
- Multiscale evaluations of global, national and regional digital soil mapping products in France B. Lemercier et al. https://doi.org/10.1016/j.geoderma.2022.116052
- Sampling and classifier modification to DSMART for disaggregating soil polygon maps T. Easher et al. https://doi.org/10.1016/j.geoderma.2023.116360
- Digital soil mapping outputs on soil classification and sugarcane production in Brazil W. Mendes & J. Demattê https://doi.org/10.1016/j.jsames.2022.103881
- Mapping soil properties at multiple depths from disaggregated legacy soil maps in the Brittany region, France Y. Ellili-Bargaoui et al. https://doi.org/10.1016/j.geodrs.2020.e00342
- Evaluating Conventional and Digital Soil Mapping for Updating Soil Maps in Iran: Opportunities, Challenges, and Implications for Sustainable Land Management S. Sani & R. Kharazmi https://doi.org/10.1134/S1064229325604433
- Pruned hierarchical Random Forest framework for digital soil mapping: Evaluation using NEON soil properties C. Xu et al. https://doi.org/10.1016/j.geoderma.2025.117392
- Does Increasing Number of Field Observations Necessarily Improve the Performance of an ML-Based Soil Parent Material Prediction? T. Takáts et al. https://doi.org/10.1007/s41748-026-01134-2
- Digital disaggregation of soil subgroups using DSMART in a Mediterranean semiarid landscape Y. Turgut et al. https://doi.org/10.1038/s41598-026-48899-0
- The nature of information and the implication for making predictions about soil properties using soil maps B. Murphy https://doi.org/10.1016/j.soilad.2024.100025
- Comparing disaggregation approaches DSMART and PPD in disaggregating soil series maps T. EASHER et al. https://doi.org/10.1016/j.pedsph.2023.12.004
- Exploring the untapped potential of hand-feel soil texture data for enhancing digital soil mapping: Revealing hidden spatial patterns from field observations A. Eymard et al. https://doi.org/10.1016/j.geoderma.2023.116769
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