Abstract

After reflecting on the past decomposition studies using the polarimetric synthetic aperture radar (PolSAR) technique and data in Earth observation (EO) studies, three primary issues are identified. Elements C12 and C32 of a covariance matrix, [C], are essential in the decomposition and cannot be ignored. Existing algorithms cannot adequately distinguish urban targets with large azimuth orientation angles from vegetation. The algorithms are complex in the formulation and procedure. To resolve the issues and envision future algorithm development, we have articulated three key modules. They are a separation factor to separate an azimuthally symmetric or asymmetric target, a diplane to model an asymmetric target in an urban area, and a procedure to derive an equivalent azimuth-orientation angle for the diplane. Then, a four-component decomposition algorithm was developed. The algorithm has been applied to multiple airborne and spaceborne PolSAR C- and L-band datasets covering areas in Canada, France, Morocco, and the USA. The primary radar target types included trihedral and dihedral corner reflectors (CRs), airport runway/taxiway, urban targets with azimuth-orientation angles ranging between 0° and 45°, ocean and inland water surfaces, city parks, grassland, forests, farmland, and desert. The separation factor delineates a symmetric or asymmetric target at a correct average rate of 92.7%. The diplane coupled with the derived equivalent azimuth-orientation angles correctly modeled radar backscatter from dihedral CRs and urban asymmetric targets. The algorithm delineated each type of ground target with an appropriate and dominant single, double, or volume scattering. Furthermore, the algorithm has four readily interpretable components, and its mathematical expression is not complicated. Therefore, the primary objectives to resolve the above three issues and to have an algorithm with well-balanced usability in EO studies and complexity in formulation and procedure are achieved.

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