A Bayesian approach to retrieve soil parameters from SAR data: Effect of prior information

Soil moisture retrieval from SAR images is always affected by speckle noise, model errors and uncertainties associated to soil parameters, which impact negatively on the accuracy of soil moisture estimates. A Bayesian approach has been proposed to deal with these issues. As a natural advantage of th...

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Guardado en:
Detalles Bibliográficos
Publicado: 2012
Materias:
Bayesian methods
Inverse problems
Prior information
Radar applications
Soil moisture
Synthetic aperture radar
Bayesian approaches
Soil conditions
Soil moisture retrievals
Soil parameters
Speckle noise
Bayesian networks
Computer simulation
Geologic models
Image analysis
Uncertainty analysis
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_0277786X_v8536_n_p_Barber
http://hdl.handle.net/20.500.12110/paper_0277786X_v8536_n_p_Barber
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paper:paper_0277786X_v8536_n_p_Barber
record_format dspace
spelling paper:paper_0277786X_v8536_n_p_Barber2023-06-08T15:26:36Z A Bayesian approach to retrieve soil parameters from SAR data: Effect of prior information Bayesian methods Inverse problems Prior information Radar applications Soil moisture Synthetic aperture radar Bayesian approaches Bayesian methods Prior information Radar applications Soil conditions Soil moisture retrievals Soil parameters Speckle noise Bayesian networks Computer simulation Geologic models Image analysis Inverse problems Soil moisture Uncertainty analysis Synthetic aperture radar Soil moisture retrieval from SAR images is always affected by speckle noise, model errors and uncertainties associated to soil parameters, which impact negatively on the accuracy of soil moisture estimates. A Bayesian approach has been proposed to deal with these issues. As a natural advantage of the Bayesian approach, prior information about soil condition can be easily included. Based on simulations, the effect of prior information has been analyzed. It follows from simulations using the Oh's model that the soil moisture estimator is very sensitivity to the roughness prior. © 2012 SPIE. 2012 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_0277786X_v8536_n_p_Barber http://hdl.handle.net/20.500.12110/paper_0277786X_v8536_n_p_Barber
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Bayesian methods
Inverse problems
Prior information
Radar applications
Soil moisture
Synthetic aperture radar
Bayesian approaches
Bayesian methods
Prior information
Radar applications
Soil conditions
Soil moisture retrievals
Soil parameters
Speckle noise
Bayesian networks
Computer simulation
Geologic models
Image analysis
Inverse problems
Soil moisture
Uncertainty analysis
Synthetic aperture radar
spellingShingle Bayesian methods
Inverse problems
Prior information
Radar applications
Soil moisture
Synthetic aperture radar
Bayesian approaches
Bayesian methods
Prior information
Radar applications
Soil conditions
Soil moisture retrievals
Soil parameters
Speckle noise
Bayesian networks
Computer simulation
Geologic models
Image analysis
Inverse problems
Soil moisture
Uncertainty analysis
Synthetic aperture radar
A Bayesian approach to retrieve soil parameters from SAR data: Effect of prior information
topic_facet Bayesian methods
Inverse problems
Prior information
Radar applications
Soil moisture
Synthetic aperture radar
Bayesian approaches
Bayesian methods
Prior information
Radar applications
Soil conditions
Soil moisture retrievals
Soil parameters
Speckle noise
Bayesian networks
Computer simulation
Geologic models
Image analysis
Inverse problems
Soil moisture
Uncertainty analysis
Synthetic aperture radar
description Soil moisture retrieval from SAR images is always affected by speckle noise, model errors and uncertainties associated to soil parameters, which impact negatively on the accuracy of soil moisture estimates. A Bayesian approach has been proposed to deal with these issues. As a natural advantage of the Bayesian approach, prior information about soil condition can be easily included. Based on simulations, the effect of prior information has been analyzed. It follows from simulations using the Oh's model that the soil moisture estimator is very sensitivity to the roughness prior. © 2012 SPIE.
title A Bayesian approach to retrieve soil parameters from SAR data: Effect of prior information
title_short A Bayesian approach to retrieve soil parameters from SAR data: Effect of prior information
title_full A Bayesian approach to retrieve soil parameters from SAR data: Effect of prior information
title_fullStr A Bayesian approach to retrieve soil parameters from SAR data: Effect of prior information
title_full_unstemmed A Bayesian approach to retrieve soil parameters from SAR data: Effect of prior information
title_sort bayesian approach to retrieve soil parameters from sar data: effect of prior information
publishDate 2012
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_0277786X_v8536_n_p_Barber
http://hdl.handle.net/20.500.12110/paper_0277786X_v8536_n_p_Barber
_version_ 1768541750705520640

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