Time-series polarimetric bistatic scattering decomposition using comprehensive modified first-order radiative transfer model at C-band for vegetative terrain and validation

ABSTRACT The sensitivity of the bistatic scattered signal to both the soil and vegetation physical properties in microwave sensing of vegetation is subject to uncertainties. A multi-angular and fully polarimetric data acquisition from a bistatic system increases the number of observations. Thus, optimum bistatic system parameters for vegetation monitoring are necessary to develop an understating of microwave interactions with the surface and vegetation properties. In this study, C-band fully polarimetric bistatic scatterometer (BiSCAT) system was designed to measure the scattering response of vegetated terrain in the forward specular plane. The correlation analysis between the measured bistatic scattering coefficient ( ) and in-situ soil/vegetation properties, such as plant water content (PWC) and soil moisture ( ), was used to find the optimum specular incidence angle of the BiSCAT system. The optimum parameters of the BiSCAT system were used as input to the modified first-order radiative transfer model (MRTM) for the simulation for vegetation. Kirchhoff’s approximate (KA) model for soil surface in forward specular plane was simplified for soil contribution within MRTM. Additionally, the temporal patterns of are modelled by employing the empirical formulation between the vegetation optical depth and PWC. The MRTM offers an understanding of co-polarized electromagnetic signal interaction with the temporal change in vegetation constituents and soil surface parameters. The model is limited to providing insights into co-polarized radar return from the target due to the incapability of yielding the cross-polarization factor from the KA model in the forward specular direction. The contributions of surface, vegetation, surface-vegetation, vegetation-surface and surface-vegetation-surface were quantified to better understand microwave’s interaction with the vegetation. The model is calibrated using a constrained non-linear least-square optimization algorithm. The performance indices of simulating yields good agreement with the BiSCAT measurements.