Drivers of Organic Carbon Stocks in Different LULC History and along Soil Depth for a 30 Years Image Time Series

• Published in: Remote sensing (Basel, Switzerland) Vol. 13; no. 11; p. 2223
• Main Authors: Tayebi, Mahboobeh, Fim Rosas, Jorge Tadeu, Mendes, Wanderson de Sousa, Poppiel, Raul Roberto, Ostovari, Yaser, Ruiz, Luis Fernando Chimelo, dos Santos, Natasha Valadares, Cerri, Carlos Eduardo Pellegrino, Silva, Sérgio Henrique Godinho, Curi, Nilton, Silvero, Nélida Elizabet Quiñonez, Demattê, José A. M.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.06.2021
• Subjects: Algorithms; Bioclimatology; Boreholes; Carbon; Clay; Clay minerals; Clay soils; Climate change; Environmental monitoring; Ethanol; Geology; Influence; Land cover; Land use; land use and cover history; Learning algorithms; Machine learning; Mineralization; Mineralogy; Model testing; Organic carbon; Organic soils; Precipitation; Prediction models; random forest; Remote monitoring; Remote sensing; Satellite imagery; Soil analysis; Soil classification; Soil depth; Soil dynamics; soil organic carbon stocks; Soil properties; Soil types; Soils; Subsoils; Sugarcane; Time series; Topography; Topsoil; Variables; Vegetation; Brazil

Soil organic carbon (SOC) stocks are a remarkable property for soil and environmental monitoring. The understanding of their dynamics in crop soils must go forward. The objective of this study was to determine the impact of temporal environmental controlling factors obtained by satellite images over...