NAC Images Research Articles

Autonomous construction of lunar infrastructure with in-situ boulders

Significant infrastructure is required to establish a long-term presence of humans on the lunar surface. In-situ resource utilization (ISRU) is a fundamental approach to ensure the viability of such construction. Here, we investigate the feasibility of constructing blast shields as one example of lunar infrastructure using unprocessed lunar boulders and an autonomous robotic excavator. First, we estimate the volume of unprocessed material required for the construction of blast shield segments. Secondly, we quantify the amount of available boulders in two exploration zones (located at the Shackleton-Henson Connecting Ridge and the Aristarchus Plateau pyroclastic deposit) using LRO NAC images and boulder size-frequency distribution laws. In addition, we showcase an alternative approach that relies on Diviner rock abundance data. Thirdly, we use a path planning algorithm to derive the distance, energy, and time required to collect local material and construct blast shield elements. Our results show that our construction method requires two orders of magnitudes less energy than alternative ISRU construction methods, while maintaining realistic mission time and payload capacity margins.

Multiphase photoclinometry as applied to the lunar photometry with LROC NAC data

An original method for photometric and geometric correction of LROC NAC data with high resolution (up to 0.5 m/pix) has been developed. The technique is based on photogrammetry and multiphase photoclinometry and allows us to obtain a longitudinal slope map and digital elevation model (DEM) with the resolution of LROC NAC CDR input images as well as to map parameters of model phase function. Obtained DEMs, requiring only LROC NAC images and LRO SPICE-kernels, exhibit significantly fewer defects and artifacts compared to existing DEMs, because they are derived from the same images they correct (self-orthorectification).This method was used to study the area of the photometric anomaly, the Irregular Mare Patch (IMP) formation Ina. A zoning map of the correlation diagram of phase ratio vs. equigonal albedo shows significant differences in the optical (photometric) properties of the regolith for hummocky and blocky formations of the IMP Ina, compared to the surrounding areas, which indicates the different nature of their formation, age, and surface roughness, contradicting some models of the IMP formation. The analysis reveals the incompleteness or inconsistencies of previously proposed models of the IMP's formation mechanisms. The high-quality DEM of the Ina formation and surrounding area with a resolution of 0.5 m/pixel was constructed.

LOLA DEM Assisted Photogrammetric Processing of Lunar Reconnaissance Orbiter NAC Images for the Lunar South Pole

Abstract. Because of its special significance, exploration missions and research at the Lunar South Pole (LSP) are of considerable importance. The mapping products of the LSP such as Digital Ortho Maps (DOMs) and Digital Elevation Models (DEMs) are essential to support exploration missions. However, in the LSP region, the available data are relatively limited. The large amounts of shadows and the special environment of the LSP has an important impact on both image matching and generation of mapping products. In this paper, we propose a photogrammetric processing method to improve the accuracy of the LRO NAC images by using LOLA DEM as auxiliary control data. The LOLA DEM was first rendered using the same illumination conditions as the corresponding LRO NAC raw images, and then matched to the LRO NAC DOMs. Next, the corresponding elevations of the tie points between LOLA DEMs and LRO NAC images were extracted and automatically added to the control network for bundle adjustment. In order to verify the feasibility of the method, we selected 17 LRO NAC images near the LSP at 85° south latitude. The results show that the proposed method can efficiently acquire uniformly distributed elevation control points for bundle adjustment and the generated DEM has a good consistency with the LOLA DEM.

Large-Scale Block Bundle Adjustment of LROC NAC Images for Lunar South Pole Mapping Based on Topographic Constraint

Large-Scale Block Bundle Adjustment of LROC NAC Images for Lunar South Pole Mapping Based on Topographic Constraint

Time-Based Rational Function Model for Block Adjustment of Long-Strip LROC NAC Images Using Sparse Elevation Controls

Time-Based Rational Function Model for Block Adjustment of Long-Strip LROC NAC Images Using Sparse Elevation Controls

3D POINT CLOUD COMPLETION USING TERRAIN-CONTINUOUS CONSTRAINTS AND DISTANCE-WEIGHTED INTERPOLATION FOR LUNAR TOPOGRAPHIC MAPPING

Abstract. Stereo vision has been proven to be an efficient tool for 3D reconstruction in lunar topographic mapping. However, point clouds reconstructed from pairs of stereo images always suffer from occlusions and illumination changes, especially in Lunar environments, resulting in incomplete geometric information. 3D point cloud completion is usually required for refining photogrammetric point clouds and enabling further applications. In this work, we address the problem of completing and refining 3D photogrammetric point clouds based on the assumption that 3D terrain should be continuous and with consistent slope change. We proposed a generalized strategy for 3D point cloud completion of lunar topographic mapping, including distance-weighted point cloud interpolation, terrian-continuous constrained outlier detection, and contour-based hole filling. We carried out experiments on two datasets of point clouds generated from 12 pairs and 6 pairs of stereo LROC NAC images covering the Apollo 17 and the Chang’E-4 landing sites, respectively. As a result, the holes in the initial DTM have been smoothly filled and the completeness of the whole DTM has been greatly improved. The incomplete area of the experimental areas has dropped by 100% and 93%, respectively. Finally, we constructed DTM with a resolution of 10 m covering a 33 km × 60 km area of the Apollo 17 landing site with RMSE of 4 m and a 12 km × 56 km area of Chang’E-4 landing site with RMSE of 4 m compared with LOLA laser points as a reference.

Clinical Utility of CT-based Attenuation-correction in Myocardial Perfusion SPECT Imaging.

We aimed to investigate and compare the role of computed tomography (CT)-based attenuation-corrected images (AC) with non-attenuation-corrected images (NAC) obtained by single-photon emission computed tomography/computed tomography (SPECT/CT) myocardial perfusion imaging (MPI). The data of 124 patients who were applied one-day stress-rest Tc-99m sestamibi SPECT/CT MPI and who had coronary angiography (CAG) results within ±3 months were retrospectively reviewed. AC and NAC images were visually evaluated by two nuclear medicine specialists in a consensus. CAG results were used as the reference standard. Specificity, sensitivity, and accuracy were calculated as 66%, 61%, 71%, 79% and 69%, 70% for AC and NAC imaging in the whole group, respectively. There was no statistically significant difference between AC and NAC images for specificity, sensitivity, and accuracy in the male and female subgroups. In the diagnosis of right coronary artery (RCA) disease, CT AC significantly increased the specificity from 87% to 96%. However, in the left anterior descending artery (LAD) region, the specificity was significantly reduced from 95% to 77%. CT-based AC did not significantly contribute to diagnostic performance for increased specificity for the RCA and reduced specificity in the LAD region. Therefore, AC images should always be evaluated side by side with NAC images to benefit from the different advantages of both techniques.

Determination of the Spatial Extent of the Engine Exhaust-Disturbed Region of the Chang'E-4 Landing Site Using LROC NAC Images

The regolith of the Chang'E-4 landing site was disturbed by its engine exhaust. To explore the interaction between the engine exhaust and the regolith, it was necessary to identify the exhaust-disturbed region. This article focuses on determining the extent of the disturbed region by using lunar reconnaissance orbiter camera narrow angle camera (LROC NAC) images. For this purpose, the tools of temporal-ratio images, phase-ratio images, reflectance profiles, and reflectance isoline graphs are employed. The reflectance profiles and isoline graphs derived from the temporal-ratio images reveal the reflectance changes before and after landing. Compared with the reflectance profiles, isoline graphs further include the spatial information of isolines, thus more robust to noise. Based on the magnitudes of changed reflectance around the lander, the engine exhaust-disturbed region was further divided into the focus disturbed region (FDR) and the diffuse disturbed region (DDR). The final estimated spatial extent along the north–south and east–west directions of the FDR were ∼9.6 and ∼10.8 m, and those of the DDR were ∼75 and ∼80 m. As compared with the estimated spatial extent of the Chang'E-3 landing site, the DDR of the Chang'E-4 landing site was larger, but the FDR was smaller. We attributed this to geological and topography factors. The reflectance changes between the FDR and the undisturbed region increased by ∼10±1%. This indicates similar processes causing the variations in the regolith properties, likely including the smoothing of the surface from microscopic to macroscopic by destroying fine-grained regolith components, or changing of the surface maturity.

Photometry of LROC NAC resolved rock-rich regions on the Moon

The study and investigation of meter and sub-meter scale geological features, especially boulders and boulder fields, on the surface of airless bodies can provide insight into the evolution of the regolith and the contribution of various processes to its formation. Prior studies have examined the photometric properties of the lunar regolith surrounding young craters using image ratios. We extend this methodology to extracting surface properties, in particular the roughness characteristics, exclusive to boulder fields and the boulders that constitute them around impact craters. Our understanding of the response of boulders to space weathering, micrometeorite abrasion, thermal fatigue, and consequently their evolution into regolith can be improved by characterizing the surface roughness of the uppermost layer of boulders. In this study, rock-rich regions on the Moon are investigated using photometric roughness by employing a normalised logarithmic phase ratio difference metric to measure and compare the slope of the phase curve (reflectance versus phase angle) of a rock-rich field to a rock-free field. We compare the photometric roughness of rock-rich fields on simulated images with the photometric roughness of rock-rich fields on LROC NAC images (0.5 m/pixel). The simulated terrains are constructed with a set of geologically informed rock properties, i.e., rock size, shape, and size frequency distribution. The artificial terrains are then converted to reflectance images using the Hapke AMSA (Hapke, 2002) reflectance model. Using this technique, we determine that rock-rich surfaces are not necessarily photometrically rougher than rock-free areas. Additionally, we find the roughness of resolved rock fields to indicate the presence of diverse sub-mm scale rock roughness (microtopography) and, possibly, variable rock single scattering albedo. These latter properties are likely controlled by rock petrology and material response to weathering and erosion. Spatial clustering of photometrically smooth and rough boulder fields in the downrange and uprange of two craters is observed, reflecting ejecta asymmetry and possibly indicating asymmetric modification of ejecta rock surfaces during the impact excavation process.

A Generative Adversarial Network for Pixel-Scale Lunar DEM Generation from High-Resolution Monocular Imagery and Low-Resolution DEM

Digital elevation models (DEMs) provide fundamental data for scientific and engineering applications in lunar exploration missions. Lunar DEMs have been mainly generated by laser altimetry and stereophotogrammetry. Complementarity to stereo photogrammetry, reflection-based surface reconstruction methods, such as shape from shading (SFS), have been studied and applied in lunar DEM reconstruction from a single image. However, this method often suffers from solution ambiguity and instability. In this paper, we propose a generative adversarial network (GAN)-based method that is able to generate high-resolution pixel-scale DEMs from a single image aided by a low-resolution DEM. We have evaluated the accuracy of the reconstructed high-resolution DEMs from 25 LROC NAC images of four regions using LROC NAC DEMs (2 m/pixel) as ground truth. The experimental results demonstrate good accuracy and adaptability to changes in illumination conditions. The root mean square error (RMSE) can reach about 2 m in areas where the degree of elevation variation is less than 100 m, and the RMSE value ranges from around 3 m to 10 m without considering the degree of the elevation variation in large-area reconstruction. As high-resolution monocular images and low-resolution DEMs are available for the entire lunar surface, the proposed GAN-based method has great potential in high-resolution lunar DEM reconstruction for lunar mapping applications.

Automatic Mapping of Small Lunar Impact Craters Using LRO‐NAC Images

AbstractImpact craters are the most common feature on the Moon’s surface. Crater size–frequency distributions provide critical insight into the timing of geological events, surface erosion rates, and impact fluxes. The impact crater size–frequency follows a power law (meter‐sized craters are a few orders of magnitude more numerous than kilometric ones), making it tedious to manually measure all the craters within an area to the smallest sizes. We can bridge this gap by using a machine learning algorithm. We adapted a Crater Detection Algorithm to work on the highest resolution lunar image data set (Lunar Reconnaissance Orbiter‐Narrow‐Angle Camera [NAC] images). We describe the retraining and application of the detection model to preprocessed NAC images and discussed the accuracy of the resulting crater detections. We evaluated the model by assessing the results across six NAC images, each covering a different lunar area at differing lighting conditions. We present the model’s average true positive rate for small impact craters (down to 20 m in diameter) is 93%. The model does display a 15% overestimation in calculated crater diameters. The presented crater detection model shows acceptable performance on NAC images with incidence angles ranging between ∼50° and ∼70° and can be applied to many lunar sites independent to morphology.

PyNAPLE: Lunar Surface Impact Crater Detection

ABSTRACT In the last 20 yr, over 600 impact flashes have been documented on the lunar surface. This wealth of data presents a unique opportunity to study the meteoroid flux of the Earth–Moon environment, and in recent years the physical properties of the impactors. However, other than through serendipitous events, there has not been yet a systematic search and discovery of the craters associated to these events. Such a meteoroid-crater link would allow us to get insight into the crater formation via these live observations of collisions. Here, we present the pynaple (python NAC Automated Pair Lunar Evaluator) software pipeline for locating newly formed craters using the location and epoch of an observed impact flash. We present the first results from pynaple, having been implemented on the 2017-09-27 impact flash. A rudimentary analysis on the impact flash and linked impact crater is also performed, finding that the crater’s ejecta pattern indicates an impact angle between 10–30°, and although the rim-to-rim diameter of the crater is not resolvable in current LRO NAC images, using crater scaling laws we predict this diameter to be 24.1–55.3 m, and using ejecta scaling predict a diameter of 27.3–37.7 m. We discuss how pynaple will enable large scale analyses of sub-kilometer scale cratering rates and refinement of both scaling laws, and the luminous efficiency.

PIXEL-RESOLUTION DTM GENERATION FOR THE LUNAR SURFACE BASED ON A COMBINED DEEP LEARNING AND SHAPE-FROM-SHADING (SFS) APPROACH

Abstract. High-resolution Digital Terrain Models (DTMs) of the lunar surface can provide crucial spatial information for lunar exploration missions. In this paper, we propose a method to generate high-quality DTMs based on a synthesis of deep learning and Shape from Shading (SFS) with a Lunar Reconnaissance Orbiter Narrow Angle Camera (LROC NAC) image as well as a coarse-resolution DTM as input. Specifically, we use a Convolutional Neural Network (CNN)-based deep learning architecture to predict initial pixel-resolution DTMs. Then, we use SFS to improve the details of DTMs. The CNN-model is trained based on the dataset with 30, 000 samples, which are formed by stereo-photogrammetry derived DTMs and orthoimages using LROC NAC images as well as the Selenological and Engineering Explorer and LRO Elevation Model (SLDEM). We take Chang’E-3 landing site as an example, and use a 1.6 m resolution LROC NAC image and 5 m resolution stereo-photogrammetry derived DTM as input to test the proposed method. We evaluate our DTMs with those from stereo-photogrammetry and deep learning. The result shows the proposed method can generate 1.6 m resolution high-quality DTMs, which can clearly improve the visibility of details of the initial DTM generated from the deep learning method.

CNN-Based Large Area Pixel-Resolution Topography Retrieval From Single-View LROC NAC Images Constrained With SLDEM

The production of high-resolution Digital Terrain Models (DTMs) based on images is often hampered by the lack of appropriate stereo observations. Here, we propose a deep learning-based reconstruction of pixel-resolution DTMs from Lunar Reconnaissance Orbiter (LRO) single-view Narrow Angle Camera (NAC) images, constrained by Selenological and Engineering Explorer and LRO LOLA Elevation Models (SLDEM). The procedure is carried out for a set of adjacent images, and the mosaicking of a contiguous large-area DTM is demonstrated. The approach is applied to the CE-3 and CE-4 landing sites, involving six multiple coverage and eight adjacent NAC L/R image pairs, respectively. For the DTM reconstruction, we use an improved Convolutional Neural Network (CNN) architecture with a weighted sum loss function involving three loss terms. We demonstrate that our method is robust and can deal with images acquired under varying illumination conditions. The DTM mosaic (1.5 m pixel size) covering the CE-4 landing area (72.8 km x 30.3 km) is without apparent seams between the individual image boundaries and consistent with the SLDEM (60 m pixel size) in terms of overall elevation, trend, and scale, but is showing considerably more morphologic detail.

Can High b Value Diffusion Be a Surrogate Marker for PET-A MR/PET Study in Neurooncology Set Up.

Purpose: Hybrid whole-body magnetic resonance/positron emission tomography (MR/PET) systems are new diagnostic tools enabling the simultaneous acquisition of morphologic and multiparametric functional data, which allow for a diversified characterization of oncological diseases. This study aimed to compare the diagnostic ability of MRI with the diffusion-weighted image (DWI), and simultaneous integrated positron emission tomography MR/PET to detect malignant lesions and elucidate the utility and limitations of these imaging modalities in preoperative and postoperative follow up in cancer patients.Material and Methods: A total of 45 patients undergoing simultaneous MR/PET for CNS ICSOL in our institution between January 2016 and July 2020 were considered in this study. Post-processing was done in Siemens syngo software to generate a b2000 image. This image was then inverted to grayscale and compared with the NAC image of PET.Results: The lesion-based sensitivity, specificity, positive predictive value, and negative predictive value for DWI were 92.3, 83.3, 97.3, and 62.5%, respectively (at 95% CI and p was 0.000). The lesion-based sensitivity, specificity, positive predictive value, and negative predictive value for PET were 97.4, 71.4, 94.9, and 83.3%, respectively (at 95% CI and p was 0.000). The lesion-based sensitivity and specificity of DWI were comparable with those of PET.Conclusions: Although DWI and FDG-PET reflect different tissue properties, there is an association between the measures of both methods in CNS tumors probably because of the coupling of cellularity with tumor metabolism as seen on FDG and other PET tracers. Our study shows that DWI acts as a surrogate biomarker for FDG PET and other tracers in tumors. The method of DWI image generation is simple, radiation-free, and cost-effective in a clinical setup. The simultaneous DWI-PET study provides evidence and confirms the role of DWI in surveillance imaging of tumors.

Peering into lunar permanently shadowed regions with deep learning

The lunar permanently shadowed regions (PSRs) are expected to host large quantities of water-ice, which are key for sustainable exploration of the Moon and beyond. In the near future, NASA and other entities plan to send rovers and humans to characterize water-ice within PSRs. However, there exists only limited information about the small-scale geomorphology and distribution of ice within PSRs because the orbital imagery captured to date lacks sufficient resolution and/or signal. In this paper, we develop and validate a new method of post-processing LRO NAC images of PSRs. We show that our method is able to reveal previously unseen geomorphological features such as boulders and craters down to 3 meters in size, whilst not finding evidence for surface frost or near-surface ice. Our post-processed images significantly facilitate the exploration of PSRs by reducing the uncertainty of target selection and traverse/mission planning.

Location and Accuracy Validation of Lunar Landing Point Based on Multi-source Images

High-precision positioning of the landing site is a critical step in the mission and an important prerequisite for surface operations of the lander and rover. In this paper, a high-precision positioning method of the landing site was designed based on image feature matching and multiple image localization methods. And the positioning experiment and accuracy validation were carried out in ChangE-3 landing site. On the basis of high-precision image matching and geometric transformation, the matching precision between the sequent descent images reached sub-pixel, and the matching accuracy between LRO NAC image and medium-resolution descent image was better than 1 pixel. The landing position was calculated to be (44.1196^°N, 19.5148^°W). This method comprehensively utilized multi-source images, and didnt entirely depend on the mapping accuracy of the landing base map. It was a further refinement of the matching results between the images and landing base map. So, this high-precision positioning method can be applied in future deep space exploration missions.

Lunar Crater Ina: Analysis of the Morphology of Intracrater Landforms

We present the results of geological and morphological analysis of LROC NAC images of a small volcanic crater Ina, D-shaped in plan view (2.9 × 1.9 km), and its immediate surroundings. This crater is located at the top of a very gently sloping shield volcano, the slopes of which, judging by the density of superimposed small craters, were formed ~3.5 Ga ago. Inside the crater there is a region with uneven relief and low hills, the density of small craters on which corresponds to an age of <100 Ma. In a number of works, the formations inside the Ina crater are considered to be manifestations of very young volcanism, while in other works, hills with an apparent age of <100 Ma are considered to be composed of “magmatic foam” such as massive pumice, which could affect the formation of small craters on them, reducing their diameters and thereby underestimating their measured spatial density. Accordingly, the Ina crater may be ancient and have the same age as the slopes of the shield volcano. In this paper, we studied the degree of morphological “freshness” of formations inside the Ina structure and compared the morphology of small craters superimposed on the hills inside Ina and on the slopes of the shield volcano adjacent to the Ina structure. In addition, model calculations of the thickness of the regolith layer for the cases of a “normal” target and a target consisting of “magmatic foam” have been performed. It is shown that the morphological freshness of the formations inside the Ina crater does not agree with the assumption about the ancientry of this crater, and morphologically “fresh” small craters on the hills inside Ina barely differ from those on the slopes of the shield volcano. These observations appear to contradict the “magmatic foam” hypothesis and support the conclusion that Ina’s structure is young.

Characterizing southern portion of Mare Vaporum with improved Chandrayaan-1 M3 data

We investigate a southern portion of Mare Vaporum using Chandrayaan-1 M3 images for which we suppress striped noise. Additional data processing allows us to analyze such spectral parameters as the depths and positions of the absorption bands near 1 and 2 μm. Mineral types were mapped using the cluster analysis of Adams diagram for pyroxenes. We inspected, in particular, the areas of pyroclastic deposits around the crater Hyginus and small areas in the crater which have the 2 μm band shifted to longer wavelengths. We examined the areas with phase-ratio analysis of LROC NAC images: the areas associated with clinopyroxenes are distinguished both in albedo and phase-ratio (56°/23°) images, perhaps, having higher roughness than surrounding surface; Whereas the areas associated with pyroclastic glasses does not seen neither in albedo nor phase-ratio images.

Removal of topographic effects from LROC NAC images as applied to the inner flank of the crater Hertzsprung S

We describe a technique of geometric and photometric corrections of high-resolution LROC NAC data at the level of NAC resolution. The technique does not exploit external DEMs, requiring solely LROC NAC images and LRO SPICE-kernels, i.e. a principle of self-orthorectification is realized. This significantly suppresses the topography influence on photometric data both in albedo and phase-ratio images. The proposed technique significantly expands the effectiveness of the phase-ratio method on the basis of LROC NAC data allowing the use of ratio components with similar illumination/observation (difference between solar azimuths is not more 30°) conditions not only exactly the same. The method also produces additional high-precision, high-resolution information about the topography of the lunar surface. We apply this to the area around a young 700 ​m crater (0.778°N, 132.95°W) located on the inner flank of the wall of the crater Hertzsprung S. We detect ejecta asymmetry around the crater, which shows that the impact creating the crater was oblique. We also found structures generated, perhaps, with wind-like processes during crater formation.