DECOMPOSITION OF POLARIMETRIC SYNTHETIC-APERTURE RADAR BACKSCATTER FROM UPLAND AND FLOODED FORESTS

The goal of this research was to decompose polarimetric Synthetic Aper ture Radar (SAR) imagery of upland and flooded forests into three back scatter types: single reflection, double reflection, and cross-polariz ed backscatter. We used a decomposition method that exploits the covar iance matrix of backscatter terms. First we applied this method to SAR imagery of dihedral and trihedral corner reflectors positioned on a s mooth, dry lake bed, and verified that it accurately isolated the diff erent backscatter types. We then applied the method to decompose multi -frequency Jet Propulsion Laboratory (JPL) airborne SAR (AIRSAR) backs catter from upland and flooded forests to explain scattering component s in SAR imagery from forested surfaces. For upland ponderosa pine for est in California, as SAR wavelength increased from C-band to P-band, scattering with an odd number of reflections decreased and scattering with an even number of reflections increased. There was no obvious tre nd with wavelength for cross-polarized scattering. For a bald cypress- tupelo floodplain forest in Georgia, scattering with an odd number of reflections dominated at C-band. Scattering power with an even number of reflections from the hooded forest was strong at L-band and stronge st at P-band. Cross-polarized scattering may not be a major component of total backscatter at all three wavelengths. Various forest structur al classes and land cover types were readily distinguishable in the im agery derived by the decomposition method. More importantly, the decom position method provided a means of unraveling complex interactions be tween radar signals and vegetated surfaces in terms of scattering mech anisms from targets. The decomposed scattering components were additio ns to the traditional HH and VV backscatter. One cautionary note: the method was not well suited to targets with low backscatter and a low s ignal-to-noise ratio.