In this study, a methodology is proposed to use dual-polarimetric synthetic aperture radar (SAR) to identify the spatial distribution of soil liquefaction. The latter is a phenomenon that occurs in conjunction with seismic events of a magnitude generally higher than 5.5-6.0 and which affects loose sandy soils located below the water table level. The methodology consists of two steps: first the spatial distributions of soil liquefaction is estimated using a constant false alarm rate method applied to the SPAN metric, namely the total power associated with the measured polarimetric channels, which is ingested into a bitemporal approach to sort out dark areas not genuine. Second, the obtained masks are read in terms of the physical scattering mechanisms using a child parameter stemming from the eigendecomposition of the covariance matrix-namely the degree of polarization. The latter is evaluated using the coseismic scenes and contrasted with the preseismic one to have rough information on the time-variability of the scattering mechanisms occurred in the area affected by soil liquefaction. Finally, the obtained maps are qualitatively contrasted against state-of-the-art optical and interferometric SAR methodologies. Experimental results, obtained processing a time-series of ascending and descending Sentinel-1 SAR scenes acquired during the 2023 Turkiye-Syria earthquake, confirm the soundness of the proposed approach.

The characterization of the lunar surface and subsurface through the utilization of synthetic aperture radar data has assumed a pivotal role in the domain of lunar exploration science. This investigation concentrated on the polarimetric analysis aimed at identifying water ice within a specific crater, designated Erlanger, located at the lunar north pole, which is fundamentally a region that is perpetually shaded from solar illumination. The area that is perpetually shaded on the moon is defined as that region that is never exposed to sunlight due to the moon's slightly tilted rotational axis. These permanently shaded regions serve as cold traps for water molecules. To ascertain the presence of water ice within the designated study area, we conducted an analysis of two datasets from the Chandrayaan mission: Mini-SAR data from Chandrayaan-1 and Dual-Frequency Synthetic Aperture Radar (DFSAR) data from Chandrayaan-2. The polarimetric analysis of the Erlanger Crater, located in a permanently shadowed region of the lunar north pole, utilizes data from the Dual-Frequency Synthetic Aperture Radar (DFSAR) and the Mini-SAR. This study focuses exclusively on the L-band DFSAR data due to the unavailability of S-band data for the Erlanger Crater. The crater, identified by the PSR ID NP_869610_0287570, is of particular interest for its potential water ice deposits. The analysis employs three decomposition models-m-delta, m-chi, and m-alpha-derived from the Mini-SAR data, along with the H-A-Alpha model known as an Eigenvector and Eigenvalue model, applied to the DFSAR data. The H-A-Alpha helps in assessing the entropy and anisotropy of the lunar surface. The results reveal a correlation between the hybrid polarimetric models (m-delta, m-chi, and m-alpha) and fully polarimetric parameters (entropy, anisotropy, and alpha), suggesting that volume scattering predominates inside the crater walls, while surface and double bounce scattering are more prevalent in the right side of the crater wall and surrounding areas. Additionally, the analysis of the circular polarization ratio (CPR) from both datasets suggests the presence of water ice within and around the crater, as values greater than 1 were observed. This finding aligns with other studies indicating that the high CPR values are indicative of ice deposits in the lunar polar regions. The polarimetric analysis of the Erlanger Crater contributes to the understanding of lunar polar regions and highlights the potential for future exploration and resource utilization on the Moon.

The separation of surface adsorbed water and internal water at the grain level is important for understanding the behavior of water on the lunar surface. Polarized spectroscopy can distinguish surface specular reflection from volume scattering, thus has a great potential to be applied at infrared wavelengths to distinguish surface adsorbed water from internal water. Using an FTIR spectrometer, we measured the polarized infrared spectra of optical grade CaF2 containing zero internal water, and opal samples with internal water. We found that for both polarized parallel and perpendicular branches, the 3 mu m water absorption depth is stronger for smaller grain size fractions of CaF2 samples, but is weaker for smaller grain size fractions of opal samples. The parallel branch detected stronger water bands compared to the perpendicular branch for both samples. We also discovered that the parallel to perpendicular ratio spectra show minimal variation among different grain size fractions for CaF2 samples, while the opal samples exhibit an increase in 3 mu m absorption depth with increasing grain size. In addition, the ratio spectra can largely suppress organic contamination. These observations indicate that polarized infrared spectroscopy can detect variations in the relative content of surface-adsorbed water and internal water. Polarized infrared diffuse spectroscopy is promising for applications in remote sensing to distinguish between surface adsorbed water and internal water.

Mini-SAR data for characterization of lunar craters with water ice has been done by the use of enhanced radar Circular Polarization Ratio (CPR) as an indicator of water ice. In this study, we have examined the ability of supervised Machine Learning (ML) technique to classify craters having anomalous high CPR in the cold traps of water ice in polar region. Since elevated CPR values alone, can be an ambiguous signature, caused by wavelength scale corner reflectors and presence of low volatiles such as water ice, study attempts to recognize dominance of anomalous class inside craters rim. In addition to CPR- a key indicator of frozen volatiles, considering backscattering coefficient, surface roughness and surface temperature as input parameters to support vector machine algorithm. The results obtained from supervised ML classification has enabled detection of additional 14 anomalous craters including Cabeus A, having favorable factors of surface temperature less than 120K, low surface roughness and low backscattering coefficient (S1) similar or equal to -21.1 dB, Thereby enhancing detection of craters with water ice.

Radar measured elevated circular polarization ratio (CPR) from lunar polar region are not unique signature of lunar water ice deposits, It may also be caused by wavelength scale roughness e.g. fragments from fresh ejecta which forms corner reflectors. Thus, there is a need to assess the role of other remotely sensed parameters along with elevated CPR for water ice detection. The study derives the morphological parameters like crater diameter (D), crater depth (d), crater floor diameter, d/D ratio along with annual temperature, surface roughness and backscattering coefficient (S1). Association of these parameters for fresh craters and craters with water ice was studied. The results indicate that morphological parameters such as surface slope, surface roughness and d/D ratio influences crater which exhibits high CPR only in their interiors (anomalous). Furthermore, analyzing d/D ratio and surface roughness with CPR shows unambiguous separation between them. These observations emphasizes role of morphometry in detecting craters having water ice.

The Qinghai-Tibet Railway (QTR) is the highest plateau artificial facility, connecting Lhasa and Golmud over Qinghai-Tibet Plateau. Climate change and anthropogenic activities are changing the condition of plateau, with potential influences on the stabilities of QTR. Synthetic aperture radar interferometry (InSAR) technique could retrieve ground millimeter scale deformation utilizing phase information from SAR images. In this study, the structure and deformation features of QTR are retrieved and analyzed using time-series interferometry with Sentinel-1A and TerraSAR-X images. The backscattering and coherence features of QTR are analyzed in medium and very high-resolution SAR images. Then, the deformation results from different SAR datasets are estimated and analyzed. Experimental results show that some of the QTR sections undergo serious deformation, with the maximum deformation rate of -20 mm/year. Moreover, the detailed deformation feature in the Beiluhe has been analyzed as well as the effects of different cooling measurements underline QTR embankment. It is also found that embankment-bridge transition along QTR is prone to undergo deformation. Our study demonstrates the application potential of high-resolution InSAR in deformation monitoring of QTR.

The Space Applications Centre (SAC), one of the major centers of the Indian Space Research Organization (ISRO), is developing a high resolution, dual-frequency Synthetic Aperture Radar as a science payload on Chandrayaan-2, ISRO's second moon mission. With this instrument, ISRO aims to further the ongoing studies of the data from S-band MiniSAR onboard Chandrayaan-1 (India) and the MiniRF of Lunar Reconnaissance Orbiter (USA). The SAR instrument has been configured to operate with both L- and S-bands, sharing a common antenna. The S-band SAR will provide continuity to the MiniSAR data, whereas L-band is expected to provide deeper penetration of the lunar regolith. The system will have a selectable slant-range resolution from 2 m to 75 m, along with standalone (L or S) and simultaneous (L and S) modes of imaging. Various features of the instrument like hybrid and full-polarimetry, a wide range of imaging incidence angles (similar to 10 degrees to similar to 35 degrees) and the high spatial resolution will greatly enhance our understanding of surface properties especially in the polar regions of the Moon. The system will also help in resolving some of the ambiguities in interpreting high values of Circular Polarization Ratio (CPR) observed in MiniSAR data. The added information from full-polarimetric data will allow greater confidence in the results derived particularly in detecting the presence (and estimating the quantity) of water ice in the polar craters. Being a planetary mission, the L&S-band SAR for Chandrayaan-2 faced stringent limits on mass, power and data rate (15 kg, 100 W and 160 Mbps respectively), irrespective of any of the planned modes of operation. This necessitated large-scale miniaturization, extensive use of on-board processing, and devices and techniques to conserve power. This paper discusses the scientific objectives which drive the requirement of a lunar SAR mission and presents the configuration of the instrument, along with a description of a number of features of the system, designed to meet the science goals with optimum resources. (C) 2015 COSPAR. Published by Elsevier Ltd. All rights reserved.

High Circular Polarization Ratio (CPR) was thought to be a robust diagnostic of water-ice on the lunar surface. Recent researches have reported such findings on walls, floors, and proximal ejecta of impact craters, as well as on sunlit zones. These signatures could not be explained with water-ice as the probable cause. In an attempt to explain such sightings, this paper portrays the character of radar waves backscattered from the lunar surface. This characterization is performed with the aid of daughter products derived from the Stokes vector.

We have employed the Arecibo Observatory Planetary Radar (AO) transmitter and the Mini-RF radar onboard NASA's Lunar Reconnaissance Orbiter (LRO) as a receiver to collect bistatic data of the lunar surface. In this paper, we demonstrate the ability to form bistatic polarimetric imagery with spatial resolution on the order of 50m, and to create polarimetric maps that could potentially reveal the presence of ice in lunar permanently shadowed craters. We discuss the details of the signal processing techniques that are required to allow these products to be formed.