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...

全面介紹

書目詳細資料

發表在:	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
格式:	Article
語言:	英语
出版:	PeerJ Inc. 2025-07-01
主題:	Soil organic carbon density Machine learning Earth observation Uncertainty Spatial aggregation Time series
在線閱讀:	https://peerj.com/articles/19605.pdf