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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| Formato: | CONF |
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| Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_0277786X_v8536_n_p_Barber |
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todo:paper_0277786X_v8536_n_p_Barber2023-10-03T15:16:45Z A Bayesian approach to retrieve soil parameters from SAR data: Effect of prior information Barber, M. Maas, M. Perna, P. Grings, F. Karszenbaum, H. 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. CONF info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar 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 Barber, M. Maas, M. Perna, P. Grings, F. Karszenbaum, H. 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. |
| format |
CONF |
| author |
Barber, M. Maas, M. Perna, P. Grings, F. Karszenbaum, H. |
| author_facet |
Barber, M. Maas, M. Perna, P. Grings, F. Karszenbaum, H. |
| author_sort |
Barber, M. |
| 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 |
| url |
http://hdl.handle.net/20.500.12110/paper_0277786X_v8536_n_p_Barber |
| work_keys_str_mv |
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| _version_ |
1807319514770046976 |