Using Machine Learning Algorithms to Estimate Soil Organic Carbon Variability with Environmental Variables and Soil Nutrient Indicators in an Alluvial Soil

Using Machine Learning Algorithms to Estimate Soil Organic Carbon Variability with Environmental Variables and Soil Nutrient Indicators in an Alluvial Soil

Soil organic carbon (SOC) is an important indicator of soil quality and directly determines soil fertility. Hence, understanding its spatial distribution and controlling factors is necessary for efficient and sustainable soil nutrient management. In this study, machine learning algorithms including...

Full description

Bibliographic Details
Main Authors: Kingsley JOHN, Isong Abraham Isong, Ndiye Michael Kebonye, Esther Okon Ayito, Prince Chapman Agyeman, Sunday Marcus Afu
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Land
Subjects:
geostatistic
machine learning
geospatial modeling
predictive mapping
soil fertility indices
environmental covariates
Online Access:https://www.mdpi.com/2073-445X/9/12/487

Internet

https://www.mdpi.com/2073-445X/9/12/487

Similar Items