Estimating Time Series Soil Moisture by Applying Recurrent Nonlinear Autoregressive Neural Networks to Passive Microwave Data over the Heihe River Basin, China

Estimating Time Series Soil Moisture by Applying Recurrent Nonlinear Autoregressive Neural Networks to Passive Microwave Data over the Heihe River Basin, China

A method using a nonlinear auto-regressive neural network with exogenous input (NARXnn) to retrieve time series soil moisture (SM) that is spatially and temporally continuous and high quality over the Heihe River Basin (HRB) in China was investigated in this study. The input training data consisted...

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Bibliographic Details
Main Authors: Zheng Lu, Linna Chai, Shaomin Liu, Huizhen Cui, Yanghua Zhang, Lingmei Jiang, Rui Jin, Ziwei Xu
Format: Article
Language:English
Published: MDPI AG 2017-06-01
Series:Remote Sensing
Subjects:
soil moisture (SM)
time series
neural network of nonlinear auto-regressive models with exogenous input (NARXnn)
Heihe River Basin (HRB)
Online Access:http://www.mdpi.com/2072-4292/9/6/574

Internet

http://www.mdpi.com/2072-4292/9/6/574

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