A comparison of country-scale subsoil predictions between a numeric and a taxonomic soil classification system

• Published in: Geoderma Regional Vol. 40; p. e00902
• Main Authors: Flynn, Trevan, Clarke, Catherine, Kostecki, Rosana, Rebi, Ansa
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.03.2025
• Subjects: algorithms; class; Digital soil mapping; Google Earth Engine; Gradient tree boost; Internet; Maximum entropy; savannas; shrublands; soil classification; South Africa; subsoil; trees; South Africa; Gradient tree boost; South Africa; Digital soil mapping; Google Earth Engine; Maximum entropy

Traditional soil classification systems are designed to communicate information; however, surveyor biases and tacit knowledge can lead to subjective soil class designations. Consequently, different soil scientists may classify the same soil differently. This becomes a critical issue when mapping soi...