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Soil Permittivity Estimation over Croplands Using Polsar Data
Journal
International Geoscience and Remote Sensing Symposium (IGARSS)
Date Issued
2022-01-01
Author(s)
Bhogapurapu, Naravanarao
Dey, Subhadip
Bhattacharya, Avik
Lopez-Martinez, Carlos
Hajnsek, Irena
Rao, Y. S.
Abstract
Polarimetric Synthetic Aperture Radar (SAR) data has been extensively used to estimate soil permittivity because of its high sensitivity to the dielectric properties of the target. However, the presence of vegetation cover induces bias in the permittivity estimates. This work utilizes the scattering-type parameters: alpha (overline{alpha}) and theta (theta-{text{FP}}) to estimate soil permittivity using the X-Bragg as the dominant surface scattering model. A theoretical study ascertains that the recently proposed theta-{text{FP}} is fairly robust towards the depolarizing component in the X-Bragg model. Hence, it is expected to produce better inversion accuracy. This study analyzes major phenology stages of Canola using the UAVSAR full-pol SAR data and the ground measurements acquired during the SMAPVEX12 campaign over Manitoba, Canada. The proposed method achieved an RMSE of 5.9 for soil permittivity with a Pearson coefficient, r=0.83. Further, the temporal trend of the soil permittivity estimates also agrees with in-situ measurements for the entire timeframe.
Volume
2022-July
Subjects