Soil salinization is a global problem, which seriously damages the ecological environment and considerably reduces agricultural productivity, especially in arid regions. Synthetic aperture radar (SAR) has been widely used in remote sensing due to its weather and sunlight independence. Polarimetric SAR has great potential for large-scale mapping and monitoring salt-affected soils. In this study, we investigate the characteristics of saline soil in extremely arid regions using dual-band quadrature-polarimetric (quad-pol) SAR images acquired by GF-3 (C-band) and ALOS-2 (L-band). Firstly, the effectiveness of the modified dielectric mixing model and integral equation model (IEM) in describing saline soil is evaluated. Secondly, the potential relationships between polarimetric parameters and salinity are discussed in both the C- and L-band, respectively, such as co-polarization ratio, scattering entropy H, and scattering angle $\alpha$. Finally, a linear regression model for monitoring salt content is established. The main contributions of this article are as follows: (1) Simulation results suggest that the radar backscattering coefficient is a weak function of salinity at low water content, but our experimental data show that soil salinity significantly contributes to the radar backscattering coefficient, which indicates the modified dielectric mixing model and IEM model is not applicable in extremely arid areas. (2) A negative correlation between the co-polarization ratio and salinity is observed, and the correlation coefficients are 0.64 (C-band) and 0.71 (L-band). Besides, scattering entropy and scattering angle exhibit a positive correlation with salinity in the C-band with correlation coefficients 0.686 and 0.669, respectively, whereas a negative correlation is found in the L-band with correlation coefficients 0.682 and 0.680, respectively. This can be attributed to the different penetration depths and sensitivity to the surface roughness of the electromagnetic waves at two frequencies. (3) A regression model for salinity estimating based on radar backscattering coefficient, co-polarization ratio, and scattering entropy is established, with a determination coefficient ($R^2$) of 0.79 and a root mean square error (RMSE) of 6.56%, allowing us to determine soil salinity from quad-pol SAR images without using backscattering models. Therefore, our results can be a reference for future soil salinity monitoring and inversion.

The Chinese Chang’E-7 (CE-7) mission is planned to land in the lunar south polar region, and then deploy a mini-flying probe to fly into the cold trap to detect the water ice. The selection of a landing site is crucial for ensuring both a safe landing and the successful achievement of its scientific objectives. This study presents a method for landing site selection in the challenging environment of the lunar south pole, utilizing multi-source remote sensing data. First, the likelihood of water ice in all cold traps within 85°S is assessed and prioritized using neutron spectrometer and hyperspectral data, with the most promising cold traps selected for sampling by CE-7’s mini-flying probe. Slope and illumination data are then used to screen feasible landing sites in the south polar region. Feasible landing sites near cold traps are aggregated into larger landing regions. Finally, high-resolution illumination maps, along with optical and radar images, are employed to refine the selection and identify the optimal landing sites. Six potential landing sites around the de Gerlache crater, an unnamed cold trap at (167.10°E, 88.71°S), Faustini crater, and Shackleton crater are proposed. It would be beneficial for CE-7 to prioritize mapping these sites post-launch using its high-resolution optical camera and radar for further detailed landing site investigation and evaluation.

For ultra-high resolution spaceborne spotlight synthetic aperture radar data processing, an imaging algorithm is proposed in this paper, which takes into account the variation of the effective velocity caused by the curved orbit. First, an airborne SAR one-step motion compensation (MOCO) method is performed to compensate for the errors introduced by the curved orbit. Then, an azimuth decompression filter is utilized to separate the rang-focusing and the azimuth-focusing after a modified Stolt interpolation. Finally, a residual range cell migration correction (RCMC) and the azimuth compression are implemented successively, considering the range dependence of the effective velocity. Simulation results confirm the effectiveness of the proposed algorithm.

Polarimetric synthetic aperture radar (SAR) provides an effective way to understand the physical properties of planetary surfaces. Rocks are the products of specific geological events, recording the evolution of impact craters on airless bodies. Multiple-scattered radar echoes from the surface or near-surface rocks generally exhibit high circular polarization ratio (CPR). In this paper, we systematically investigate the relationship between radar CPR and rock abundance of lunar regolith using Mini-RF SAR data. A total of 51 craters with diameters of 11.8-200 km are selected for analysis. The mean values of Mini-RF CPR and Diviner rock abundance are calculated for the interior and exterior of each crater. Statistical results show a close correlation between Mini-RF CPR and Diviner rock abundance, where high radar CPR and Diviner rock abundance are observed at the blocky ejecta. However, we find the difference of mean CPR value between crater interior and exterior is smaller than that of Diviner rock abundance. This may be attributed to the near surface rocks that contribute to radar CPR but are not considered in the inversion of Diviner rock abundance. Therefore, the concept of volumetric rock abundance is introduced, indicating the proportion of rocks with diameters larger than one-tenth of the radar wavelength within the detection area. A three component CPR model is then developed to link radar CPR to volumetric rock abundance. Furthermore, an inverse powerlaw relationship between volumetric rock abundance and crater ages is discovered, which further indicates the feasibility of using SAR data to estimate rock abundance of lunar regolith.

The channel imbalance and crosstalks are the two major factors for the polarimetric calibration of the circular quad-polarimetric (CQP) synthetic aperture radar (SAR) systems. In existing methods using distributed targets, the latter is usually ignored, which may lead to unbearable errors in target classification, surface parameter inversion, and so on. To address this issue, this article proposes a modified iterative calibration method using distributed targets that satisfy quasi-azimuth symmetry to calibrate both the channel imbalance and crosstalks of the CQP SAR systems. First, a stable distributed target selection strategy is proposed based on the correlation coefficient of LL polarization and RR polarization, the cross- and co-polarization backscatter ratio, and the equivalent number of looks (ENL). These parameters are insensitive to polarization distortion, and their typical ranges are determined via numerical simulations. Their combination helps select the targets that satisfy the quasi-azimuth symmetry, which is critical for calibrating the crosstalks. Then, the calibration can be conducted using the selected target. Finally, the phase ambiguity of the receive channel imbalance ratio, commonly found in distributed-target-based algorithms, is eliminated using a dipole target. Through the calibration of Gaofen-3 data and the statistical analysis of residual distortion, the effectiveness of the proposed method is verified.