Articles | Volume 6, issue 2
SOIL, 6, 371–388, 2020
https://doi.org/10.5194/soil-6-371-2020
SOIL, 6, 371–388, 2020
https://doi.org/10.5194/soil-6-371-2020

Original research article 14 Aug 2020

Original research article | 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 et al.

Related authors

Additional soil organic carbon storage potential in global croplands
José Padarian, Budiman Minasny, Alex B. McBratney, and Pete Smith
SOIL Discuss., https://doi.org/10.5194/soil-2021-73,https://doi.org/10.5194/soil-2021-73, 2021
Revised manuscript under review for SOIL
Short summary
The influence of training sample size on the accuracy of deep learning models for the prediction of soil properties with near-infrared spectroscopy data
Wartini Ng, Budiman Minasny, Wanderson de Sousa Mendes, and José Alexandre Melo Demattê
SOIL, 6, 565–578, https://doi.org/10.5194/soil-6-565-2020,https://doi.org/10.5194/soil-6-565-2020, 2020
Short summary
Game theory interpretation of digital soil mapping convolutional neural networks
José Padarian, Alex B. McBratney, and Budiman Minasny
SOIL, 6, 389–397, https://doi.org/10.5194/soil-6-389-2020,https://doi.org/10.5194/soil-6-389-2020, 2020
Short summary
Disaggregating a regional-extent digital soil map using Bayesian area-to-point regression kriging for farm-scale soil carbon assessment
Sanjeewani Nimalka Somarathna Pallegedara Dewage, Budiman Minasny, and Brendan Malone
SOIL, 6, 359–369, https://doi.org/10.5194/soil-6-359-2020,https://doi.org/10.5194/soil-6-359-2020, 2020
Short summary
Machine learning and soil sciences: a review aided by machine learning tools
José Padarian, Budiman Minasny, and Alex B. McBratney
SOIL, 6, 35–52, https://doi.org/10.5194/soil-6-35-2020,https://doi.org/10.5194/soil-6-35-2020, 2020
Short summary

Related subject area

Soil and methods
Estimation of soil properties with mid-infrared soil spectroscopy across yam production landscapes in West Africa
Philipp Baumann, Juhwan Lee, Emmanuel Frossard, Laurie Paule Schönholzer, Lucien Diby, Valérie Kouamé Hgaza, Delwende Innocent Kiba, Andrew Sila, Keith Sheperd, and Johan Six
SOIL, 7, 717–731, https://doi.org/10.5194/soil-7-717-2021,https://doi.org/10.5194/soil-7-717-2021, 2021
Short summary
The central African soil spectral library: a new soil infrared repository and a geographical prediction analysis
Laura Summerauer, Philipp Baumann, Leonardo Ramirez-Lopez, Matti Barthel, Marijn Bauters, Benjamin Bukombe, Mario Reichenbach, Pascal Boeckx, Elizabeth Kearsley, Kristof Van Oost, Bernard Vanlauwe, Dieudonné Chiragaga, Aimé Bisimwa Heri-Kazi, Pieter Moonen, Andrew Sila, Keith Shepherd, Basile Bazirake Mujinya, Eric Van Ranst, Geert Baert, Sebastian Doetterl, and Johan Six
SOIL, 7, 693–715, https://doi.org/10.5194/soil-7-693-2021,https://doi.org/10.5194/soil-7-693-2021, 2021
Short summary
Developing the Swiss mid-infrared soil spectral library for local estimation and monitoring
Philipp Baumann, Anatol Helfenstein, Andreas Gubler, Armin Keller, Reto Giulio Meuli, Daniel Wächter, Juhwan Lee, Raphael Viscarra Rossel, and Johan Six
SOIL, 7, 525–546, https://doi.org/10.5194/soil-7-525-2021,https://doi.org/10.5194/soil-7-525-2021, 2021
Short summary
Predicting the spatial distribution of soil organic carbon stock in Swedish forests using a group of covariates and site-specific data
Kpade O. L. Hounkpatin, Johan Stendahl, Mattias Lundblad, and Erik Karltun
SOIL, 7, 377–398, https://doi.org/10.5194/soil-7-377-2021,https://doi.org/10.5194/soil-7-377-2021, 2021
Short summary
Improved calibration of the Green–Ampt infiltration module in the EROSION-2D/3D model using a rainfall-runoff experiment database
Hana Beitlerová, Jonas Lenz, Jan Devátý, Martin Mistr, Jiří Kapička, Arno Buchholz, Ilona Gerndtová, and Anne Routschek
SOIL, 7, 241–253, https://doi.org/10.5194/soil-7-241-2021,https://doi.org/10.5194/soil-7-241-2021, 2021
Short summary

Cited articles

Abdel-Kader, F. H.: Digital soil mapping at pilot sites in the northwest coast of Egypt: a multinomial logistic regression approach, Egypt. J. Remote Sens. Space Sci. 14, 29–40, 2011. 
Arrouays, D., Poggio, L., Salazar Guerreroc, O. A., and Mulder, V. L.: Digital soil mapping and Global Soil Map, Main advances and ways forward, Geoderma Reg., 21, 20–30, https://doi.org/10.1016/j.geodrs.2020.e00265, 2020. 
Baize, D. and Girard, M. C.: Référentiel pédologique 2008, Association française pour l'étude du sol, 2008. 
Bergeri, I., Michel, R., and Boutin, J. P.: Everything (or almost everything) about the Kappa coefficient, Medecine Tropropicale, 62, 634–636, 2002. 
Beven, K. J. and Kirkby, M. J.: A physically based, variable contributing area model of basin hydrology/Un modèle à base physique de zone d'appel variable de l'hydrologie du bassin versant, Hydrol. Sci. Bull., 24, 43–69, https://doi.org/10.1080/02626667909491834, 1979.