Using bias correction and ensemble modelling for predictive mapping and related uncertainty: A case study in digital soil mapping

• Published in: Geoderma Vol. 403; p. 115153
• Main Authors: Sylvain, Jean-Daniel, Anctil, François, Thiffault, Évelyne
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2021
• Subjects: Bias correction; case studies; Cations exchange capacity; Digital soil mapping; Ensemble modelling; environmental management; Organic carbon; prediction; Predictive mapping; Remote sensing; Soil texture; uncertainty; Uncertainty assessment; variance; Bias correction; Organic carbon; Ensemble modelling; Digital soil mapping; Predictive mapping; pH; Soil texture; Uncertainty assessment; Cations exchange capacity; Remote sensing

•Bias correction increase the representativeness and linearity of predictions.•Ensemble models allow uncertainty assessment and optimize accuracy of predictions.•Global soil maps are subject to bias that may impact environmental modelling. In this study, we explored the potential benefits of using b...