Predicting and Mapping of Soil Organic Carbon Using Machine Learning Algorithms in Northern Iran

Predicting and Mapping of Soil Organic Carbon Using Machine Learning Algorithms in Northern Iran

Estimation of the soil organic carbon (SOC) content is of utmost importance in understanding the chemical, physical, and biological functions of the soil. This study proposes machine learning algorithms of support vector machines (SVM), artificial neural networks (ANN), regression tree, random fores...

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Bibliographic Details
Main Authors: Mostafa Emadi, Ruhollah Taghizadeh-Mehrjardi, Ali Cherati, Majid Danesh, Amir Mosavi, Thomas Scholten
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:Remote Sensing
Subjects:
soil organic carbon
carbon sequestration
machine learning
deep neural networks
susceptibility
big data
Online Access:https://www.mdpi.com/2072-4292/12/14/2234

Internet

https://www.mdpi.com/2072-4292/12/14/2234

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