Highly Efficient JR Optimization Technique for Solving Prediction Problem of Soil Organic Carbon on Large Scale

Highly Efficient JR Optimization Technique for Solving Prediction Problem of Soil Organic Carbon on Large Scale

We utilized remote sensing and ground cover data to predict soil organic carbon (SOC) content across a vast geographic region. Employing a combination of machine learning and deep learning techniques, we developed a novel data fusion approach that integrated Digital Elevation Model (DEM) data, MODIS...

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Bibliographic Details
Main Authors: Harsh Vazirani, Xiaofeng Wu, Anurag Srivastava, Debajyoti Dhar, Divyansh Pathak
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Sensors
Subjects:
GeoBlendMDWC
optimization
regression
soil organic carbon (SOC) detection
satellite imagery
machine learning algorithms
Online Access:https://www.mdpi.com/1424-8220/24/22/7317
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