The application of differential synthetic aperture radar interferometry (DInSAR) techniques has been traditionally limited to the single-polarimetric case. The launch of satellites with polarimetric capabilities has triggered the synergy between polarimetric and interferometric algorithms, leading to a significant improvement in final DInSAR products. During the last years, the different polarimetric optimization techniques available have been successfully applied to the so-called classical phase quality estimators, i.e., the coherence and the amplitude dispersion estimators. In this context, a new estimator to evaluate the pixels' phase quality, referred to as temporal sublook coherence (TSC), has recently demonstrated to provide promising results in DInSAR applications. The nature of this estimator, which is based on exploiting the spectral properties of pointlike scatterers through the coherence evaluation of different sublooks of the image spectrum, allows its adaptation to the existing polarimetric optimization methods. This letter presents the benefits of extending the TSC estimator to work with fully polarimetric data. For this purpose, a fully polarimetric data set consisting of ten X-band ground-based SAR (GB-SAR) images is employed. The final DInSAR results obtained by means of TSC polarimetric optimization are compared with the ones obtained with its classical single-polarimetric approach, achieving up to more than a twofold increase in the pixels' density.

Peer Reviewed