Soil Moisture Content Retrieval from Remote Sensing Data by Artificial Neural Network Based on Sample Optimization

Soil Moisture Content Retrieval from Remote Sensing Data by Artificial Neural Network Based on Sample Optimization

Soil moisture content (SMC) plays an essential role in geoscience research. The SMC can be retrieved using an artificial neural network (ANN) based on remote sensing data. The quantity and quality of samples for ANN training and testing are two critical factors that affect the SMC retrieving results...

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Bibliographic Details
Main Authors: Qixin Liu, Xingfa Gu, Xinran Chen, Faisal Mumtaz, Yan Liu, Chunmei Wang, Tao Yu, Yin Zhang, Dakang Wang, Yulin Zhan
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Sensors
Subjects:
soil moisture content
artificial neural network
sample optimization
synthetic aperture radar
optical remote sensing image
Online Access:https://www.mdpi.com/1424-8220/22/4/1611

Internet

https://www.mdpi.com/1424-8220/22/4/1611

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