Understanding the reachability of water ice by future in-situ experiments near the lunar poles is crucial for supporting growing exploration plans and constraining the uncertainties on its genesis and distribution. To achieve this objective, we perform a thorough three-dimensional mapping of the distribution of water ice in the lunar polar regions (70 degrees onward), integrating radar, optical, and neutron detector observations from the Lunar Reconnaissance Orbiter mission (LRO). Our analysis reveals similar to 5-to-8-fold larger expanse of subsurface water ice (similar to 1-3 m depth) compared to surface water ice (up to 1 m depth) for the north and south poles, respectively. Our investigation cannot rule out the possibility of deep-seated water ice deposits in the lunar poles that remains beyond the detection capabilities of existing instruments on LRO. Moreover, we find that the extent of water ice in the northern polar region (similar to 1100 +/- 74 km(2)) is twice that in the southern polar region (similar to 562 +/- 54 km(2)). Our mapping also suggests that the dichotomous latitudinal distribution and the antipodal longitudinal distribution of water ice are likely driven by Mare volcanism and preferential cratering. We provide additional evidence that outgassing during Imbrian volcanism was probably the primary source of subsurface water ice in the lunar poles, which favors larger expanse over meteoritic sources.

Appropriate environmental sensing methods and visualization representations are crucial foundations for the in situ exploration of planets. In this paper, we developed specialized visualization methods to facilitate the rover's interaction and decision-making processes, as well as to address the path-planning and obstacle-avoidance requirements for lunar polar region exploration and Mars exploration. To achieve this goal, we utilize simulated lunar polar regions and Martian environments. Among them, the lunar rover operating in the permanently shadowed region (PSR) of the simulated crater primarily utilizes light detection and ranging (LiDAR) for environmental sensing; then, we reconstruct a mesh using the Poisson surface reconstruction method. After that, the lunar rover's traveling environment is represented as a red-green-blue (RGB) image, a slope coloration image, and a theoretical water content coloration image, based on different interaction needs and scientific objectives. For the rocky environment where the Mars rover is traveling, this paper enhances the display of the rocks on the Martian surface. It does so by utilizing depth information of the rock instances to highlight their significance for the rover's path-planning and obstacle-avoidance decisions. Such an environmental sensing and enhanced visualization approach facilitates rover path-planning and remote-interactive operations, thereby enabling further exploration activities in the lunar PSR and Mars, in addition to facilitating the study and communication of specific planetary science objectives, and the production and display of basemaps and thematic maps.

Landing in the permanently shadowed regions (PSRs) on the Moon requires high-resolution topographic information and accurate navigation. Owing to low Sun elevation angles, there is no direct solar illumination in PSR, making it difficult to acquire high-resolution optical images for terrain relative navigation (TRN). Synthetic aperture radar (SAR) onboard lunar orbiter can acquire the high-resolution digital elevation model (DEM) of PSR with the interference phases from repeat-passes, or alternatively, from multiantenna observations in a single orbit pass. In this article, SAR images from dual-antenna observations obtained in single orbit passes are simulated with two-scale model and Range-Doppler algorithm for the interference phases based on the DEM data from the lunar orbiter laser altimeter (LOLA). Hence, we generate DEMs of PSR in two prominent lunar south polar craters, Shoemaker and Shackleton. After geometric correction, the influence of radar parallax in DEM data are removed. The generated DEM data are used to illustrate the possibility of TRN in PSR with the image-matching algorithm. The slope angle image of the PSR from the generated DEM is taken as the reference image for navigation, while high-resolution slope angle image from LOLA DEM data is taken as the real-time image from the flyer. The speeded-up robust features algorithm matches the feature points in the reference image and real-time image. The location of the matched points determines the position and motion vector of the flyer. The simulation proves the DEM data from InSAR can provide detailed topographic information and can be used for navigation in regions of permanent shadows.

Obtaining high-visibility images of the lunar polar permanently shadowed region (PSR) is quite important for internal landforms and material existence exploration. However, PSR images usually have poor quality due to a lack of sufficient illumination. Existing researches, that attempt to address this problem, face challenges caused by relying on virtual assumptions, manual processing, and paired data. To solve these problems, we aim to avoid using paired datasets and directly optimize PSR images, and accordingly propose a zero-shot parameter learning model (ZSPL-PSR) for PSR image enhancement. Our ZSPL-PSR, which enhances PSR images by estimating parameters to adjust image properties, consists of a parameter learning network and a parameter weight learning structure. Particularly, first, a parameter learning network that integrates robust information is constructed to separately estimate the midtone brightness parameters, shadow brightness parameters, and contrast parameters. Where these parameters are beneficial for iteratively improve the overall brightness, shadow brightness, and contrast of the image. Second, a parameter weight learning structure is exploited to coordinate the priority of different parameter maps. In addition, to highlight the terrain details in the enhanced PSR image, we use USM sharpening for postprocessing. The experimental results display the fully interpretable enhanced PSR maps of the lunar north and south poles and their sharpened versions, showcasing rich landforms in PSR. To validate the model performance, a benchmark PSR testing set has been constructed, and extensive comparisons conducted on it demonstrated that ZSPL-PSR exceeds other zero-shot learning methods significantly in image quality. Our code is available at https://github.com/dl-zfq/ZSPL-PSR.

In China's Chang'e 7 mission, a miniflyer will be carried for in-situ water ice measurement in permanently shadowed regions (PSRs) around the lunar south pole. The extreme cold environment within PSRs causes serious challenges for the safety of the miniflyer. Predication of temperatures in PSR is critical for designing the internal heating system and the heat source capacity. Conducting in-situ detection mission in relatively warm temperature can reduce the threat of the cold environment and save energy to maintain a suitable operation temperature for payloads. Since the polar-orbiting satellite lunar reconnaissance orbiter passes over the same location in the polar region with intervals of about a month, the temporally continuous observation is unavailable. Simulation is necessary to determine the temporally continuous temperatures of PSR during the mission. In this article, a numerical model of the temperatures in PSR is presented. The ray tracing approach is used to calculate the shadowing effect of terrain on scattered sunlight and thermal radiation. The PSR temperatures are simulated with the one-dimensional heat conduction equation. Simulated temperatures are compared with Diviner data for validation. The spatial and temporal temperature distributions of PSRs in crater Shackleton, which is the preferred landing site for the Chang'e 7 mission, are simulated from 2026 to 2028. The simulated temperature in high temporal resolution of one Earth hour can be applied to analyzing diurnal and seasonal temperatures in PSRs and is helpful for thermal management and design of the internal heating system. The time windows with relatively warm temperature in PSR at regions with slope angles less than 5(degrees) are recommended to save energy and reduce the hazards of the extremely cold environment.

A microwave radiation model with coherent surface scattering is developed for analyzing the topographic effects of the lunar permanently shadowed region (PSR) on microwave radiometric observations. The coherent surface scattering to the observer, which comes from the nearby surface due to the variation in the surface slope, is quantified by the ray-tracing method. In addition, the vertical distribution of temperatures of the PSR is estimated by a 1-D thermal model with 3-D shading and scattering effects. The impact of coherent scattering on microwave brightness temperatures (TBs) by a nadir-look radiometer becomes more noticeable with high-resolution microwave TB data, such as 4 pix/degrees by 4 pix/degrees in this study. The rise in TB at certain locations in PSR may reach up to similar to 8 K at 37 GHz. However, when compared with the low resolution of the TB by Chang'E-2, the averaged contribution of coherent surface scattering is less than 1 K. Meanwhile, there is a discrepancy between the model-generated microwave TB and the measured TB of Chang'E-2, both in small and large craters. This discrepancy may be explained by a calibration issue or the uncertainty of model parameters. Nonetheless, the trend in the model-generated TB is consistent with the measurements, indicating that the proposed model has the potential to predict TB effectively within the PSR.

Studies of the lunar surface from Synthetic Aperture Radar (SAR) data have played a prominent role in the exploration of the lunar surface in recent times. This study uses data from SAR sensors from three Moon missions: Chandrayaan-1 Mini-SAR, Lunar Recon-naissance Orbiter (LRO) Mini-RF and Chandrayaan-2 Dual Frequency Synthetic Aperture Radar (DFSAR). DFSAR sensor is the first of its kind to operate at L-band and S-band in fully and hybrid polarimetric modes. Due to the availability of only L-band data out of the two bands (L-and S-band) for the study site, this study only used DFSAR's L-band data. The dielectric characterization and polarimetric analysis of the lunar north polar crater Hermite-A was performed in this study using Chandrayaan-1 Mini-SAR, LRO Mini-RF and Chandrayaan-2 DFSAR data. Hermite-A lies in the Permanently Shadowed Region (PSR) of the lunar north pole and whose PSR ID is NP_879520_3076780. Because of its location within the PSR of the lunar north pole, the Hermite-A makes an ideal candidate for a probable location of water-ice deposits. This work utilizes S-band hybrid polarimetric data of Mini-SAR and Mini-RF and L -band fully polarimetric data of DFSAR for the lunar north polar crater Hermite-A. This study characterizes the scattering mechanisms from three decomposition techniques of Hybrid Polarimetry namely m-delta, m-chi, and m-alpha decompositions, and for fully polari-metric data Barnes decomposition technique was applied which is based on wave dichotomy. Eigenvector and Eigenvalue-based decom-position model (H-A-Alpha decomposition) was also applied to characterize the scattering behavior of the crater. This study utilizes the hybrid-pol and fully polarimetric data-based Integral Equation Model (IEM) to retrieve the values of dielectric constant for Hermite-A crater. The dielectric constant values for the Hermite-A crater from Chandrayaan-1 Mini-SAR and LRO Mini-RF are similar, which goes further in establishing the presence of water-ice in the region. The values of the dielectric constant for Chandrayaan-2 in some regions of the crater especially on the left side of the crater is also around 3 but overall the range is relatively higher than the com-pact/hybrid polarimetric data. The dielectric characterization and polarimetric analysis of the Hermite-A indicatively illustrate that the crater may have surface ice clusters in its walls and on some areas of the crater floor, which can be explored in the future from the synergistic use of remote sensing data and in-situ experiments to confirm the presence of the surface ice clusters.(c) 2022 COSPAR. Published by Elsevier B.V. All rights reserved.

Direct sampling has never been performed in the permanently shadowed regions (PSRs) of lunar poles up to now. In the Chinese Chang'e-7 (CE-7) mission, a mini-flyer will fly from the lander in a solar illuminated region at the lunar south polar region to the nearby PSRs to collect samples for analysis. In this letter, four potential craters of the lunar south pole, including Shackleton, Shoemaker, de Gerlache, and Slater are discussed for this proposal. Design principles of the landing site, sampling site, and flight route are presented. The local surface slopes are calculated using a digital elevation model (DEM) to select a flat area as a potential landing site, which should allow ample time for solar illumination to support the rover from the lander and allow the flyer to reach the neighboring PSRs. Mini-RF data are applied for further validation of the flat landing and sampling sites, particularly for some rocky rough surfaces that are not identified in DEM and optical images of PSRs. The craters de Gerlache and Slater are found to be suitable for further analysis when high-resolution synthetic aperture radar (SAR) data are acquired by the new polarimetric SAR carried by CE-7.

Dielectric inversion of lunar permanently shadowed region (PSR) of moon poles has been studied for estimation of possible water-ice content. The Campbell model was directly applied to mini-SAR data for inversion on the Hermite-A crater region. However, this letter presents quantitative analysis that the lunar surface topography, i.e., surface roughness and slopes, and underlying dielectric media, and so on, can significantly affect this inversion. The model is actually degenerated into a half-space model without topographic account. This letter presents a two-layer model of Kirchhoff-approximation surface/small perturbation approximation subsurface to take account of all these topographic factors for PSR dielectric inversion.

Knowledge of the amount of water ice on the lunar surface will play a crucial role in future lunar missions. The discovery of large quantities of water ice on the Moon will have very significant implications for human space exploration. In this letter, the methodology for quantification of water ice is developed. Quantification of water ice present in the permanently shadowed region (PSR) of Hermite-A Crater is done by comparing simulated dielectric constant values obtained using the Campbell model and laboratory-measured dielectric constant values of terrestrial analogue of lunar soil for various percentages of water ice content. From this analysis, it is observed that about 66.32% of the total PSR of Hermite-A Crater is covered with different percentages of water ice. In this letter, all the pixels of the PSR of Hermite-A Crater, with a spatial resolution of 7.4 m/pixel, have been mapped with their corresponding water ice content ranging from 0% to 9%.