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

Matias Barber; Martin Maas; Pablo Perna; Francisco Grings; Haydee Karszenbaum

doi:10.1117/12.974253

21 November 2012 A Bayesian approach to retrieve soil parameters from SAR data: effect of prior information

Matias Barber, Martin Maas, Pablo Perna, Francisco Grings, Haydee Karszenbaum

Proceedings Volume 8536, SAR Image Analysis, Modeling, and Techniques XII; 85360N (2012) https://doi.org/10.1117/12.974253
Event: SPIE Remote Sensing, 2012, Edinburgh, United Kingdom

Abstract

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.

Citation Download Citation

Matias Barber, Martin Maas, Pablo Perna, Francisco Grings, and Haydee Karszenbaum "A Bayesian approach to retrieve soil parameters from SAR data: effect of prior information", Proc. SPIE 8536, SAR Image Analysis, Modeling, and Techniques XII, 85360N (21 November 2012); https://doi.org/10.1117/12.974253

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