Pruned hierarchical Random Forest framework for digital soil mapping: Evaluation using NEON soil properties

• Published in: Geoderma Vol. 459; p. 117392
• Main Authors: Xu, Chengcheng, Huang, Jingyi, Hartemink, Alfred E., Chaney, Nathaniel W.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.07.2025; Elsevier
• Subjects: Digital soil mapping; POLARIS; Pruned Hierarchical Random Forest (pHRF); Soil covariates; Soil properties estimation; Uncertainty reduction; Uncertainty reduction; Soil properties estimation; Pruned Hierarchical Random Forest (pHRF); Soil covariates; Digital soil mapping; POLARIS

•A pruned Hierarchical Random Forest (pHRF) method was developed to address data imbalance issues in soil surveys.•The pHRF method showed out-of-bag scores over 0.7 at multiple taxonomic levels for soil classification.•This approach provided narrower prediction intervals and reduced the uncertaintie...