Speckle noise and soil heterogeneities as error sources in a bayesian soil moisture retrieval scheme for SAR data

Soil moisture retrieval from SAR images is always affected by speckle noise and uncertainties associated to soil parameters, which impact negatively on the accuracy of soil moisture estimates. In this paper a soil moisture Bayesian estimator from polarimetric SAR images is proposed to address these...

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Detalles Bibliográficos
Autores principales: Barber, M., Grings, F., Perna, P., Piscitelli, M., Maas, M., Bruscantini, C., Jacobo-Berlles, J., Karszenbaum, H.
Formato: JOUR
Materias:
Bayesian methods
inverse problems
radar applications
soil moisture
synthetic aperture radar
Backscattering coefficients
Bayesian approaches
Bayesian estimators
Bayesian model
Bayesian retrieval
Error sources
Mathematical modeling
Multilooking
Optimum parameters
Polarimetric SAR
Prior information
Radar applications
SAR data
SAR Images
Scattering model
Soil conditions
Soil heterogeneity
Soil moisture retrievals
Soil parameters
Spatial heterogeneity
Speckle effects
Speckle noise
Statistical distribution
Algorithms
Bayesian networks
Computer simulation
Estimation
Inverse problems
Polarimeters
Soil moisture
Speckle
Synthetic aperture radar
Uncertainty analysis
Geologic models
accuracy assessment
algorithm
backscatter
Bayesian analysis
error analysis
heterogeneity
inverse problem
noise
numerical model
statistical distribution
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_19391404_v5_n3_p942_Barber
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

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