Imaging radar polarization signatures: Theory and observation

Abstract

We have converted a conventional synthetic aperture radar system into an imaging radar polarimeter by employing two orthogonally polarized antennas and recording both the amplitude and absolute phase measurements of the received electric fields. This enables us to measure the complete complex scattering matrix for each individual resolution element in the radar image. The Stokes matrix, derived from the scattering matrix, is then used to synthesize the scattering coefficient for any desired combination of transmit and receive antenna polarizations, allowing us to measure the variation of the scattering coefficient with polarization. This polarization information can be displayed in a new and useful way, producing the polarization signature for each point in an image. Comparison of the theoretical and observed polarization signatures permits identification of the dominant scattering mechanisms contributing to the measured radar backscatter. For example, the ocean and smoother lava flows have polarization signatures which are similar to those predicted by a slightly rough dielectric surface model; thus the model likely approximates the physical mechanisms responsible for the reflected energy from these surfaces. Urban areas, on the other hand, exhibit polarization signatures which resemble those predicted by dihedral corner reflector geometries. The coefficient of variation, a parameter derived from the polarization signature, is a measure of resolution scale variation of a surface and indicates the degree to which polarization filtering can be used to enhance or suppress the return from a collection of scatterers. Our observations show that the ocean has a low coefficient of variation; thus the return from the ocean is highly polarized, and polarization effects can be used successfully to suppress or enhance the return from the ocean. Parks and other vegetated areas exhibit a large coefficient of variation, suggesting that the return from these areas contains a considerable component that is randomly polarized; varying the transmit and receive polarizations will not change the return from the vegetated areas appreciably.

Análise dos parâmetros estruturais de tipologias florestais utilizando dados SAR em banda L

“…Nevertheless variations in the floristic composition, forest structure and management practices can have an important effect on the results (HOEKMAN and QUINÕNES, 2000). The high correlation among biomass and L-σ 0 hh and σ 0 hv , saturated at 100ton/ha for both polarizations was found by WATANABE et al (2006) at a temperate coniferous forest. The same authors, using the target decomposition of Freeman and Durden (FREEMAN and DURDEN, 1998) to generate a scattering model of each tree component, where volume scattering is around 80-90%, when the biomass exceeds 50 ton/ha.…”

“…The σ 0 values at different polarizations were obtained taking into account the average of pixels available at each ROI (sample area), which correspond to the same plots inventoried during the field survey. In the SAR image, the ROI area includes the sample dimension with a sufficient amount of pixels representative for the theme, reducing so the statistical uncertainties and the influence of speckle noise (WATANABE et al, 2006).…”

“…The relation between σ 0 hh and tree height tends to be high due mainly to the low capacity the wave penetration because of the high incidence angle, thus the interaction tends to happen in the canopy. According to VAN ZYL et al (1987) in this situation, the attenuation by the canopy is stronger and thus single and double scattering is reduced and volume scattering dominates. Due to the importance of the incidence angle (Ө) the evaluation of backscatter was also done together with the biophysical parameters (Table 3) by multiple regression.…”

“…The knowledge of the interaction mechanisms between SAR (Synthetic Aperture Radar) signals and the structural properties of forests was investigated in the several studies ( VAN ZYL et al, 1987;KASISCHKE et al, 1997;CHAMPION et al, 1998;COOPS, 2002;NEEFF et al, 2005). Characteristics of forest coverage (e.g.…”

“…For younger stands the component of surface scattering is of around 20%, and the volumetric scattering components are below 70%. Yet, in according to WATANABE et al (2006), the origin of the dependency among the forest species was examined for the σ 0 HHabove-ground biomass. It is concluded that a possible cause of the dependency is the different characteristics of the stands rather than forest species.…”