Mapping Within-Field Soil Health Variations Using Apparent Electrical Conductivity, Topography, and Machine Learning

Mapping Within-Field Soil Health Variations Using Apparent Electrical Conductivity, Topography, and Machine Learning

High-resolution maps of soil health measurements could help farmers finetune input resources and management practices for profit maximization. Within-field soil heath variations can be mapped using local topography and apparent electrical conductivity (ECa) as predictors. To address these issues, a...

Full description

Bibliographic Details
Main Authors: Kabindra Adhikari, Douglas R. Smith, Harold Collins, Chad Hajda, Bharat Sharma Acharya, Phillip R. Owens
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Agronomy
Subjects:
digital soil mapping
ECa
precision agriculture
random forests
soil quality
terrain attributes
Online Access:https://www.mdpi.com/2073-4395/12/5/1019

Internet

https://www.mdpi.com/2073-4395/12/5/1019

Similar Items