Target Characterization and Scattering Power Components From Dual-Pol Sentinel-1 SAR Data

Target characterization parameters are pivotal in accurately identifying and assessing diverse land cover targets in radar polarimetry. While full-polarimetric (full-pol) synthetic aperture radar (SAR) data offer numerous parameters, characterizing targets with HH-HV or VV-VH dual-polarimetric (dual-pol) SAR data has traditionally relied on backscatter intensity alone due to limited polarimetric information, which leads to ambiguities in characterizing diverse land cover targets. In response to this limitation, this study introduces a novel target characteristic parameter $\overline {\alpha }_{(k)}$ derived from dual-pol single-look complex (SLC) and ground range detected (GRD) SAR data that are capable of discriminating between “dihedral-like” (buildings, bridges, ships, and so on) and “surface-like” (water bodies, bare fields, runways, and so on) targets, by employing a data-driven approach. We first derive a set of normalized descriptors independently of SLC and GRD SAR data to formulate two indices that characterize “dihedral-like” and “surface-like” targets. Using the two indices, we derive the dual-pol target characteristic parameter, providing a novel perspective on the intricate nature of radar responses from diverse land cover targets acquired by dual-pol SAR sensors. Furthermore, we employ this parameter to extract three scattering power components: “dihedral-like” ( $P_{d-l}$ ), unpolarized ( $P_{u}$ ), and “surface-like” ( $P_{s-l}$ ) from both dual-pol SLC and GRD SAR data. We assess the proposed target characteristic parameter and scattering power components using Sentinel-1 images acquired over diverse land cover targets spanning six continents. This novel approach enables improved global land cover characterization with operational SAR missions such as Sentinel-1 and upcoming NASA-ISRO SAR (NISAR) missions.