The inability to monitor wetland drag coefficients at a regional scale is rooted in the difficulty to determine vegetation structure from remote sensing data. Based on the fact that the backscattering coefficient is sensitive to marsh vegetation structure, this paper presents a methodology to estimate the drag coefficient from a combination of SAR images, interaction models and ancillary data. We use as test case a severe fire event occurred in the Paraná River Delta (Argentina) at the beginning of 2008, when 10% of the herbaceous vegetation was burned up. A map of the reduction of the wetland drag coefficient is presented.

Soil moisture is a key geophysical variable that can be estimated using remote sensing techniques by making use of the known relation between soil backscattering and dielectric constant in the microwave regime. However, since SAR systems observations depends on geometrical and dielectrical surface parameters (besides instrument parameters like operation frequency, incidence angle and received/transmitted polarization), the uncertainties associated to a given retrieval scheme are difficult to evaluate. In this paper, these uncertainties associated to the estimation of soil dielectric constant from a single quadpol SAR image are studied using a physically based interaction model (i.e. a two-layer version of the SPM model at second order) coupled with a Bayesian approach. The overall scheme was validated using SAOCOM quad-pol data and in situ soil dielectric constant measurements in experimental agricultural plots in Argentina. Both a theoretical end-to-end experiments and actual retrieval from real SAR data were implemented. From the simulations, the intrinsic ambiguities in the estimations of soil dielectric constant from a single image were studied, and the benefits of using two images with different incidence angles were discussed. Finally, by analyzing SAOCOM data using the proposed retrieval scheme, soil dielectric constant were estimated and compared with in situ measurements, with and RMSE error of ≤ 2.

Accuracy of Kirchhoff approximation (KA) for rough-surface electromagnetic wave scattering is studied by comparison with accurate numerical solutions in the context of three-dimensional dielectric surfaces. The Kirchhoff tangent plane approximation is examined without resorting to the principle of stationary phase. In particular, it is shown that this additional assumption leads to zero cross-polarized backscattered power, but not the tangent plane approximation itself. Extensive numerical results in the case of a bisinusoidal surface are presented for a wide range of problem parameters: height-to-period, wavelength, incidence angles, and dielectric constants. In particular, this paper shows that the range of validity inherent in the KA includes surfaces whose curvature is not only much smaller, but also comparable to the incident wavelength, with errors smaller than 5% in total reflectivity, thus presenting a detailed and reliable source for the validity of the KA in a three-dimensional fully polarimetric formulation.

Soil moisture (SM) is a key geophysical variable that can be estimated at regional scales using remote sensing techniques, by making use of the known relationship between soil reflectivity and the dielectric constant in the microwave regime. In this context, the exploitation of available illuminators of opportunity that currently emit large amounts of power at microwave frequencies (compared to typical synthetic aperture radar systems) is promising. Some published techniques estimate SM by analyzing the interference pattern (IP) between direct and reflected signal as measured by a single antenna (i.e., IP technique). In this letter, a new approach to simulate the IP is proposed, in which the soil roughness is modeled straightforwardly using the second-order small perturbation model. Results illustrate that the ``notch'' in the VV-polarization IP (related to the Brewster angle) can only be directly observed for very low values of soil rms roughness (s < 0.5 cm). For typical values of soil roughness (s~ 1.2 cm), the notch disappears and only a minimum in the IP is observed near the Brewster angle.

We present a fully coherent, analytic model of the backscattering intensity in all HH,HV,VH, and VV channels, for the volume scattering of radiation from a layer of finite thickness, such as a vegetation layer over bare soil. We aim for a simple, not numerically intensive, model that could be used either as a forward model in a Bayesian estimation scheme, or else as a preliminary means to identify key features of a concrete problem, for its further analysis by more sophisticated theoretical and numerical approaches.