Urban density estimation from polarimetric SAR images using polarization orientation angle

In this paper, an urban density estimation algorithm from polarimetric synthetic aperture radar (SAR) images is proposed. Polarization orientation angle (POA) and four power components derived by four-component decomposition are utilized in the proposed algorithm. The dependence of the four decomposition components on POA can be lessened by rotating the elements of the coherency matrix by the POA. However, a level of POA dependence remains even after the correction. The proposed algorithm utilizes POA-corrected components, but pixels are grouped into several categories according to POA. Then, each component´s scattering intensity is normalized for all pixels in each POA space. Finally, both the normalized intensity of volume scattering power (Pv) and that of the subtraction of surface scattering power (Ps) from double bounce scattering power (Pd) are combined to estimate urban density.