Adaptive Model-Based Polarimetric Decomposition Using PolInSAR Coherence

The overestimation of volume scattering power and the scattering mechanism ambiguity are still present in model-based decompositions even with the implementation of the deorientation processing. These effects are demonstrated and investigated. One possible reason is because of the limited dynamic range of the models themselves that are not fully satisfied for the mixed scene cases. An empirical volume scattering model is proposed, using the repeat-pass polarimetric synthetic aperture radar interferometry (PolInSAR) coherence, to extend the model dynamic range to be more adaptive. PolInSAR coherence is sensitive to different types of forests and terrains. The proposed model inherits these characteristics. In addition, it considers the cross-polarization power induced by oriented man-made structures. Thereby, a model-based polarimetric decomposition scheme is developed. The efficiency of the proposed method is demonstrated using E-SAR airborne and ALOS/PALSAR spaceborne repeat-pass PolInSAR datasets. Comparative experiments are carried out and show that the proposed decomposition overcomes the scattering mechanism ambiguity between forests and oriented built-up areas, since it successfully identifies the oriented buildings as double- or odd-bounce man-made structures while keeping the volume scattering dominant for the forests. Besides, the stable decomposition performance over the oriented built-up patches with quite different orientation angles also validates the improvement of the proposed decomposition. In addition, the demonstrations with short and long temporal baselines validate the generality of the proposed method.