AbstractuAmicrowave scattering model has been developed for layered vegetation based on an iteratlve solution of the radiative transfer equation up to the second order to account for multiple scattering within the canopy and between the ground and the canopy'. The model is designed to operate over a wide frequency range for both deciduous and coniferous forest and to account for th_ branch size distribution, leaf orientation distribution, and branch orientation distribution for each size. The canopy is modeled as a two-layered medium above a rough interface. The upper layer is the crown containing leaves, stems, and branches. The lower layer is the trunk region modeled as randomly positioned cylinders with a preferred orientation distribution above an irregular soil surface. Comparisons of this model with measurements from deciduous and coniferous forests show good agreements at several frequencies for both ilke and cross polarizations. Major features of the model needed to realize the agreement include allowance for (1) branch size distribution, (2) second-order effects, and (3) tree component models valid over a wide range of frequencies.

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Electromagnetic backscattering from a sparse distribution of lossy dielectric particles having random orientation and position is studied. The paper begins by using the Foldy approximation to find an equation for the mean field. From this equation, an effective permittivity for the scattering medium is obtained. The correlation of the scattered field is found by employing the distorted Born approximation, i.e., particles embedded in the effective medium are assumed to be single scatterers. The above method is then used to find the backscattering coefficients from a leaf canopy. The leaf canopy is modeled by a half space of dielectric discs that are small in comparison to a wavelength. Numerical results show that the depolarized cross section is a sensitive function of leaf inclination angle statistics.

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A K-distribution has been developed to characterize the statistical properties of multi-look processed polarimetric S A R data.The probability density function (PDF) was derived as the product of a Gamma distributed random variable and the polarimetric covariance matrix. The latter characterizes the speckle and the former depicts the inhomogeneity (texture). For multi-look data incoherently averaged from correlated one-look samples, we found that, for better modeling, the number of looks has to assume a noninteger value. A procedure was developed to estimate the equivalent number of looks and the parameter of the K-distribution. Experimental results using NASNJPL Qlook and 16-look polarimetric S A R data substantiated this multi-look K-distribution.We also found that the multi-look process reduced the inhomogeneity and made the K-distribution less significant.