Spatiotemporal prediction of soil organic carbon density in Europe (2000–2022) using earth observation and machine learning

This article describes a comprehensive framework for soil organic carbon density (SOCD, kg/m3) modeling and mapping, based on spatiotemporal random forest (RF) and quantile regression forests (QRF). A total of 45,616 SOCD observations and various Earth observation (EO) feature layers were used to pr...

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Bibliographic Details

Published in:	PeerJ
Main Authors:	Xuemeng Tian, Sytze de Bruin, Rolf Simoes, Mustafa Serkan Isik, Robert Minarik, Yu-Feng Ho, Murat Şahin, Martin Herold, Davide Consoli, Tomislav Hengl
Format:	Article
Language:	English
Published:	PeerJ Inc. 2025-07-01
Subjects:	Soil organic carbon density Machine learning Earth observation Uncertainty Spatial aggregation Time series
Online Access:	https://peerj.com/articles/19605.pdf