Estimating time-dependent vegetation biases in the SMAP soil moisture product
<p>Remotely sensed soil moisture products are influenced by vegetation and how it is accounted for in the retrieval, which is a potential source of time-variable biases. To estimate such complex, time-variable error structures from noisy data, we introduce a Bayesian extension to triple co...
Main Authors: | , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2018-08-01
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Series: | Hydrology and Earth System Sciences |
Online Access: | https://www.hydrol-earth-syst-sci.net/22/4473/2018/hess-22-4473-2018.pdf |