Estimating Soil Moisture Over Winter Wheat Fields During Growing Season Using Machine-Learning Methods

Estimating Soil Moisture Over Winter Wheat Fields During Growing Season Using Machine-Learning Methods

Soil moisture is vital for the crop growth and directly affects the crop yield. The conventional synthetic aperture radar (SAR) based soil moisture monitoring is often influenced by vegetation cover and surface roughness. The machine-learning methods are not constrained by physical parameters and ha...

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Bibliographic Details
Main Authors: Lin Chen, Minfeng Xing, Binbin He, Jinfei Wang, Jiali Shang, Xiaodong Huang, Min Xu
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Feature selection
machine-learning technology
polarimetric decomposition
RADARSAT-2 synthetic aperture radar (SAR)
soil moisture
Online Access:https://ieeexplore.ieee.org/document/9384159/

Internet

https://ieeexplore.ieee.org/document/9384159/

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