Lunar Craters Research Articles

The LCROSS Impact Crater as Seen by ShadowCam and Mini‐RF: Size, Context, and Excavation of Copernican Volatiles

AbstractThe Lunar CRater Observations and Sensing Satellite (LCROSS) impacted a Centaur rocket stage into a permanently shadowed region (PSR) in Cabeus crater, excavating water ice and other volatiles. We used the Miniature Radio Frequency (Mini‐RF) instrument on the Lunar Reconnaissance Orbiter and the ShadowCam instrument on the Korean Pathfinder Lunar Orbiter to detect the probable 22‐m diameter crater that resulted from the LCROSS impact. The crater formed superposed upon a dense small crater population along a crater ray from a larger pre‐existing crater. From its geologic context, the ice and regolith excavated by LCROSS were likely modified within the last 0.1–0.5 Gyr. An upper limit for the excavated volatiles is ~0.9 Gyr, as the location was not a PSR prior to that time. A young age for the LCROSS‐detected volatiles supports the idea that they were mostly emplaced by an exogenic mechanism, such as from comets or the solar wind.

POSIT: An automated tool for detecting and characterizing diverse morphological features in raster data - Application to pockmarks, mounds, and craters

Accurate detection and characterization of seafloor morphologies are crucial for marine researchers and industries involved in underwater mapping, environmental monitoring, or resource exploration. Although their detection has relied on visual inspection of detailed bathymetries, few efforts to automate the process can be found in the literature. This study presents a novel MatLab computer code called POSIT (Feature Signature Detection) based on the convolution and correlation with a structural element containing the shape to search for. POSIT is successfully tested on both synthetic and real datasets, encompassing marine and terrestrial digital elevation models of different resolution and on a digital image. The centroids of submarine pockmarks and mounds, terrestrial volcanic craters and lunar craters are calculated with zero dispersion and perfect location, and their geometric parameters and confidence are provided.

A review on deep learning-based automated lunar crater detection

A review on deep learning-based automated lunar crater detection

Global Lunar Crater Density Using Buffered Nonsparseness Correction

The density of craters on a planetary surface directly relates to the age of the surface. As the surface ages, however, craters can be erased by subsequent large impacts via direct overprinting, known as geometric crater obliteration. Such counts become increasingly limited as surfaces become more heavily cratered. Techniques to infer the statistics of the regions obliterated by craters were developed in the past decade. Such techniques, however, have only been used for regional studies. Herein, we present a study of the global density of lunar impact craters ≥20 km in diameter using both traditional crater-counting and buffered nonsparseness correction (BNSC) crater-counting techniques. By comparing the measurements, we quantify the influence of geometric crater obliteration on the visible lunar crater record. Our results reveal that geometric crater obliteration erased up to three-fifths of craters ≥20 km in diameter that formed on the most ancient lunar terrains, whereas younger surfaces, like the Procellarum KREEP Terrane, show little to no evidence of such crater obliteration. The differences in derived crater densities highlight ancient surfaces in which the effects of geometric crater obliteration must be considered to characterize their cratering histories. Furthermore, our results identify the most heavily cratered area on the Moon, a region of the lunar highlands between Smythii basin and the South Pole–Aitken (SPA) basin (Smythii–SPA–Highlands); the number of impacts revealed by the BNSC technique for this region is consistent with estimates derived from the abundance of highly siderophile elements and from modeling crustal porosity.

Accurate Mapping and Evaluation of Small Impact Craters within the Lunar Landing Area

Impact craters, as the most distinct lunar structural unit and geological structure, are marked on the Moon’s surface. For over a decade, researchers have focused on identifying and exploring large- to medium-sized impact craters on the surface of the Moon (craters with a diameter greater than 1 km). Small impact craters have obvious statistical significance owing to their magnitude in numbers. The identification and analysis of small craters provide indispensable clues for the study of lunar geological evolution. However, such craters only remain in specific images and regions. At present, there is no comprehensive record of small impact craters in the existing lunar impact crater databases. The small impact craters on the surface of the Moon are enormous and vary in size by orders of magnitude, exhibiting small target characteristics in space. The present study focuses on the identification and spatial analysis of small impact craters on the surface of the Moon. A feature amplification strategy-based identification model was established for small impact crater detection, achieving accurate recognition of the small impact craters on the surface of the Moon (with a recall rate of 86.97% and a false-positive rate as low as 0.54% ± 0.16%). In total, 228,897, 142,872, and 42,008 new small lunar impact craters (with diameters as low as 4.5 m) were identified in the ten lunar landing areas of returned samples from the Apollo, Luna, and Chang’e-5 missions. In addition, the spatial distribution characteristics of small impact craters during different geological periods in the landing area are provided. Data on the newly identified small impact craters will provide an important basis for revealing the lunar impact fluxes and young lunar surface dating in lunar geological evolution research.

Possible Anthropogenic Contributions to the LAMP-observed Surficial Icy Regolith within Lunar Polar Craters: A Comparison of Apollo and Starship Landings

This work assesses the potential of midsized and large human landing systems to deliver water from their exhaust plumes to cold traps within lunar polar craters. It has been estimated that a total of between 2 and 60 T of surficial water was sensed by the Lunar Reconnaissance Orbiter Lyman Alpha Mapping Project on the floors of the larger permanently shadowed south polar craters. This intrinsic surficial water sensed in the far-ultraviolet is thought to be in the form of a 0.3%–2% icy regolith in the top few hundred nanometers of the surface. We find that the six past Apollo Lunar Module midlatitude landings could contribute no more than 0.36 T of water mass to this existing, intrinsic surficial water in permanently shadowed regions (PSRs). However, we find that the Starship landing plume has the potential, in some cases, to deliver over 10 T of water to the PSRs, which is a substantial fraction (possibly >20%) of the existing intrinsic surficial water mass. This anthropogenic contribution could possibly overlay and mix with the naturally occurring icy regolith at the uppermost surface. A possible consequence is that the origin of the intrinsic surficial icy regolith, which is still undetermined, could be lost as it mixes with the extrinsic anthropogenic contribution. We suggest that existing and future orbital and landed assets be used to examine the effect of polar landers on the cold traps within PSRs.

Ejecta Blankets at Small Craters on the Moon

Impact-derived ejecta covers most of the lunar surface, originating from recent impacts through to the beginning of the geologic record. Despite how common ejecta is, accurate measurements of ejecta thickness are difficult to obtain, and existing estimates of ejecta thickness vary widely. This study uses excavation by meter-scale impacts on the fresh ejecta blankets of larger, kilometer-scale impacts to make point measurements of ejecta thickness. We estimate ejecta thickness at the rims of 73 lunar craters (0.1–4.8 km diameter) and create isopach maps of ejecta thickness for three craters. We derive an equation for ejecta thickness, t=0.14±0.062R(0.77±0.080)r/R(−B) , where r is the horizontal distance from the center of the crater, R is the center-to-rim crater radius, and B describes the rate at which ejecta thickness decays with radial distance. Our average value for B (2.8 ± 0.1) is similar to previous work, though we observe that B can vary significantly within an ejecta blanket.

Quantitative Research on the Morphological Characteristics of Lunar Impact Craters of Different Stratigraphic Ages since the Imbrian Period

Impact craters serve as recorders of lunar evolutionary history, and determining the stratigraphic ages of craters is crucial. However, the age of many craters on the Moon remains undetermined. The morphology of craters is closely related to their stratigraphic ages. In the study, we systematically and quantitatively analyzed seven morphological parameters of 432 impact craters with known stratigraphic ages (Copernican, Eratosthenian, Imbrian), including crater depth, wall width, wall height, rim height, irregularity, volume, and roughness, as well as rock abundance. The study provided a range of morphological parameters for craters from the Copernican, Eratosthenian, and Imbrian. Additionally, we derived power law relationships between five morphological parameters and crater diameter, excluding irregularity and roughness. Furthermore, the transitional crater diameters from simple to complex crater morphology were determined for the Copernican and Eratosthenian, approximately 13 km and 15 km, respectively. These results suggest systematic differences in the lunar regolith in different stratigraphic ages. For impact craters of the same diameter, as crater age increases, irregularity tends to be greater, while crater depth, wall width, wall height, rim height, volume, roughness, and rock abundance tend to be smaller. Therefore, in cases where the diameter is determined, the actual values of morphological parameters and rock abundance can be used to constrain the stratigraphic age information of craters of an unknown age.

An overview and perspective of identifying lunar craters

An overview and perspective of identifying lunar craters

Temperature Dependence of the Dielectric Constant on the Lunar Surface Based on Mini-RF and Diviner Observations

Radar observation is an effective way to understand subsurface structures in terms of the dielectric constant, whose controlling factors include chemical composition, packing density, and water/ice content. Recently, laboratory measurements have shown that the dielectric constant of lunar regolith simulants also depends on the temperature, which has never been evaluated from remote sensing data. In this study, we estimated the dielectric constant from the Miniature Radio Frequency (Mini-RF) data on a lunar crater floor in the north polar region at two different local times (i.e., different surface temperatures). We calculated the dielectric constant using the inversion method and obtained the bolometric surface temperature from the Diviner Lunar Radiometer Experiment (Diviner) data. The histograms of the estimated dielectric constant values are different between the two local times. This could be interpreted as a result of the temperature dependence of the dielectric constant, while further evaluation of the influence of topography on the incidence angle and small surface roughness is needed. Nevertheless, our result suggests that the temperature dependence of the dielectric constant should be considered when interpreting S-band radar observations of the Moon and other celestial bodies with large surface temperature differences.

Automated Lunar Crater Identification with Chandrayaan-2 TMC-2 Images using Deep Convolutional Neural Networks.

Terrestrial planets and their moons have impact craters, contributing significantly to the complex geomorphology of planetary bodies in our Solar System. Traditional crater identification methods struggle with accuracy because of the diverse forms, locations, and sizes of the craters. Our main aim is to locate lunar craters using images from Terrain Mapping Camera-2 (TMC-2) onboard the Chandrayaan-II satellite. The crater-based U-Net model, a convolutional neural network frequently used in image segmentation tasks, is a deep learning method presented in this study. The task of crater detection was accomplished with the proposed model in two steps: initially, it was trained using Resnet18 as the backbone and U-Net based on Image Net as weights. Secondly, TMC-2 images from Chandrayaan-2 were used to detect craters based on the trained model. The model proposed in this study comprises a neural network, feature extractor, and optimization technique for lunar crater detection. The model achieves 80.95% accuracy using unannotated data and precision and recall are much better with annotated data with an accuracy of 86.91% in object detection with TMC-2 ortho images. 2000 images have been considered for the present work as manual annotation is a time-consuming process and the inclusion of more images can enhance the performance score of the model proposed.

An Image Retrieval Method for Lunar Complex Craters Integrating Visual and Depth Features

In the geological research of the Moon and other celestial bodies, the identification and analysis of impact craters are crucial for understanding the geological history of these bodies. With the rapid increase in the volume of high-resolution imagery data returned from exploration missions, traditional image retrieval methods face dual challenges of efficiency and accuracy when processing lunar complex crater image data. Deep learning techniques offer a potential solution. This paper proposes an image retrieval model for lunar complex craters that integrates visual and depth features (LC2R-Net) to overcome these difficulties. For depth feature extraction, we employ the Swin Transformer as the core architecture for feature extraction and enhance the recognition capability for key crater features by integrating the Convolutional Block Attention Module with Effective Channel Attention (CBAMwithECA). Furthermore, a triplet loss function is introduced to generate highly discriminative image embeddings, further optimizing the embedding space for similarity retrieval. In terms of visual feature extraction, we utilize Local Binary Patterns (LBP) and Hu moments to extract the texture and shape features of crater images. By performing a weighted fusion of these features and utilizing Principal Component Analysis (PCA) for dimensionality reduction, we effectively combine visual and depth features and optimize retrieval efficiency. Finally, cosine similarity is used to calculate the similarity between query images and images in the database, returning the most similar images as retrieval results. Validation experiments conducted on the lunar complex impact crater dataset constructed in this article demonstrate that LC2R-Net achieves a retrieval precision of 83.75%, showcasing superior efficiency. These experimental results confirm the advantages of LC2R-Net in handling the task of lunar complex impact crater image retrieval.

Modelling science return from the lunar crater radio telescope on the far side of the moon.

The era following the separation of CMB photons from matter, until the emergence of the first stars and galaxies, is known as the Cosmic Dark Ages. Studying the electromagnetic radiation emitted by neutral hydrogen having the 21 cm rest wavelength is the only way to explore this significant phase in the Universe's history, offering opportunities to investigate essential questions about dark matter physics, the standard cosmological model andinflation. Due to cosmological redshift, this signal is now only observable at frequencies inaccessible from the Earth's surface due to ionospheric absorption and reflection. With the Lunar Crater Radio Telescope (LCRT), we aim to conduct unprecedented measurements of the sky-averaged redshifted signal spectrum in the 4.7-47 MHz band, by deploying a 350 m diameter parabolic reflector mesh inside a lunar crater on the far side of the Moon and suspending a receiver at its focus. This work discusses the feasibility of the LCRT science goals through the development of a science model, with emphasis on post-processing techniques to extract the Dark Ages signal from the galactic foreground dominating the expected raw data. This model can be used to vary critical instrument and mission parameters to understand their effect on the quality of the retrieved signal. This article is part of a discussion meeting issue 'Astronomy from the Moon: the next decades (part 2)'.

Lightweight tensorial convolutional neural network for lunar impact crater detection

Impact crater detection is one of the most important and critical studies of the geological history of planetary surfaces. Recent literature on crater identification demonstrates the powerful potential of deep-learning algorithms. However, these methods potentially assumed that the detection is conducted in devices with sufficient computing resources, and used networks with massive learnable parameters to obtain superb performance. In this paper, we proposed a lightweight tensorial convolutional neural network (CNN) for lunar impact crater detection. Specifically, we develop a tensorial you only look once (TYOLO) network by representing the convolutional kernels in tensor train (TT) decomposition. Thus, the parameter redundancy of TYOLO can be greatly reduced. To the best of our knowledge, this is the first work that considers the lightweight CNN model for impact crater detection. We demonstrate the lunar impact crater detection results over the ChangE-2 lunar digital orthophotos model (DOM) and digital evaluated model (DEM). Experimental results show that the proposed TYOLO network can obtain 1.44×speed up and 39× compression with 2.4% improvement in crater detection. Overall, the proposed network demonstrates great potential in spacecraft with emerging computing resource constraints.

Magnetic signatures of lunar impact craters

The Moon almost certainly had an internally generated magnetic field in its past, but the duration of the dynamo, its temporal stability, and the surface field intensity are poorly known. Impact cratering events heat portions of the crust above the Curie temperature, allowing the ambient magnetic field strength to be recorded as the crater cools. We systematically analyzed the magnetic signatures of lunar impact craters with diameters greater than 90 km using recent magnetic field models and crater databases. Craters were classified as having evidence for impact-related central magnetization or demagnetization, and synthetic magnetic field models were used to estimate the number of incorrect identifications. In total, about 15% of craters were found to have impact-related magnetized or demagnetized signatures. The proportion of pre-Nectarian and Nectarian aged craters in the magnetized class is about 2%–3%, and there is little evidence for magnetized craters in the Imbrian and younger periods. The percentage of craters in the demagnetized class is about 0.3%–3% in the pre-Nectarian and Nectarian periods and abruptly increases to 16% in the Imbrian period. Our observations are consistent with the presence of strong dynamo fields during portions of the older pre-Nectarian and Nectarian periods, with a weakening (or cessation) of the dynamo at the beginning of the younger Imbrian period. These results differ from paleomagnetic analyses of lunar samples that imply the existence of strong dynamo field strengths from the pre-Nectarian up until at least the first half of the Imbrian period.

Slope Stability Analysis and Soil Mechanical Properties of Impact Craters around the Lunar South Pole

Water ice has been found in the permanently shadowed regions of impact craters around the lunar South Pole, which makes them ideal areas for in situ exploration missions. However, near the rim of impact craters, construction and exploration activities may cause slope instability. As a result, a better understanding of the shear strength of lunar soil under higher stress conditions is required. This paper mainly uses the finite element method to analyze slope stability to determine the position and shape of the slip surface and assess the safety factor. The height and gradient of the slope, the shear strength of lunar soil, and the lunar surface mission all influence the stability of the slope. We also analyze the soil mechanical properties of a soil slope adjacent to the traverse path of the Chang’E-4 Yutu-2 rover. Determining the stability of the slope at the lunar South Pole impact crater under various loading conditions will enhance the implementation of the lunar surface construction program. In this respect, this paper simulates a lunar mission landing at the Shackleton and Shoemaker craters and indicates that areas with higher cohesion lunar soil may be more stable for exploration in the more complex terrain of the South Pole.

Surface morphology inside the PSR area of lunar polar crater Shoemaker in comparison with that of the sunlit areas

Our study is based on a photogeological analysis of the hill-shade images produced from the LOLA digital terrain models and on a stereometric analysis of LROC NAC images. Our results demonstrate that surface morphology of the permanently shadowed floor of crater Shoemaker is nearly identical to that of the regularly illuminated mare surface at the Lunokhod-2 working area and the surface of the highland plain of the Apollo-16 landing site, being dominated by populations of craters smaller than 1 km in diameters. Craters on the Shoemaker floor have approximately the same depth-to-diameter ratios as those within the Lunokhod-2 and Apollo-16 areas. The observed surface morphology of the Shoemaker floor is the result of meteorite bombardment like in other areas of the Moon. Within the permanently shadowed surface areas we detected no morphological peculiarities that could result from the absence of the diurnal temperature variations that excludes the temperature-related creep component of the downslope material movement. This probably means that in the areas with regular solar illumination, the role of the downslope movement of debris by thermally induced creep mechanisms is secondary compared to shaking by close and distant meteorite impacts and locally by moonquakes.

Identification of Lunar Craters in the Chang’e-5 Landing Region Based on Kaguya TC Morning Map

Impact craters are extensively researched geological features that contribute to various aspects of lunar science, such as evaluating the model age, regolith thickness, etc. The method for identifying impact craters has gradually transitioned from manual counting to automated identification. Automatic crater detection based on the digital elevation model (DEM) is commonly used to detect larger craters. However, using only DEM has limitations in discerning smaller craters (diameter < ~1 km). This study utilizes an improved Faster R-CNN algorithm and the Kaguya Terrain Camera (TC) morning map to detect small impact craters in the Chang’e-5 (CE-5) landing site. It uses model fusion to improve the precision of small crater identification. The results show a recall rate of 96.33% and a precision value of 90.19% for craters with diameters exceeding 200 m. The model found a total of 187,101 impact craters in the CE-5 region. The spatial distribution density of impact craters with diameters ranging from 100 m to 200 m is approximately 2.5706/km2. For craters with diameters ranging from 200 m to 1 km, the average spatial distribution density is about 0.9016/km2. By the unbiased impact crater density of chronological analysis, the model age of the Im2 and Em4 geological units in the CE-5 region is 3.78 Ga and 2.07 Ga, respectively.

Lunar polar volatile remobilization in regolith-filled craters

Under lunar polar cold traps, volatile molecules within porous regolith may experience temperature and depth dependent slow mobility. Many degraded lunar craters exhibit thick regolith fill based on models of topographic diffusion and observations of fresh and degraded craters. Regolith has a low thermal conductivity relative to megaregolith and may act as a blanket for internal lunar heat flow, leading to increased temperatures at depth. We develop 2D thermal models of fresh and regolith-filled lunar craters over depths of meters to hundreds of meters below the surface. We find that the base of the stability and slow mobility zones migrate upward with regolith fill, which leads to temperatures that may increase the sublimation rate of volatiles at depth. For a notional cold trap crater 1.6 km in diameter and 3.6 billion years old, topographic diffusion fills it with approximately 90 m of regolith, and the regolith fill's blanketing effect causes the 110 K isotherm to shift about 180 m upward. This places it approximately 25 m below the current cold trap surface and well above the initial crater floor. The slow water ice mobility zone below the 110 K isotherms also shifts upward with regolith fill, potentially increasing volatile concentrations at shallower depths. These secondary volatile concentrations may be targets for sampling and testing hypotheses of volatile system processes. In addition, remobilized volatile concentrations may be a resource for future In-Situ Resource Utilization (ISRU) applications. The thick regolith fill in degraded craters and volatile remobilization potential in lunar subsurface cold traps have implications for future exploration instruments, sampling, and ISRU architectures.

Recalibration of the lunar chronology due to spatial cratering-rate variability

Cratering chronologies are used to derive the history of planetary bodies and assume an isotropic flux of impactors over the entire surface of the Moon. The impactor population is largely dominated by near-Earth-objects (NEOs) since ∼3.5 billion years ago. However, lunar impact probabilities from the currently known NEO population show an excess of impacts close to the poles compared to the equator as well as a latitudinal dependency of the approach angle of impactors. This is accompanied by a variation of the impact flux and speed with the distance from the apex due to the synchronicity of the lunar orbit around the Earth. Here, we compute the spatial dependency of the cratering rate produced by such variabilities and recalibrate the lunar chronology. We show that it allows to reconcile the crater density measured at mid-latitudes around the Chang'e-5 landing site with the age of the samples collected by this mission. Our updated chronology leads to differences in model ages of up to 30% compared to other chronology systems. The modeled cratering rate variability is then compared with the distribution of lunar craters younger than ∼1 Ma, 1 Ga and 4 Ga. The general trend of the cratering distribution is consistent with the one obtained from dynamical models of NEOs, thus potentially reflecting a nonuniform distribution of orbital parameters of ancient impactor populations, beyond 3.5 Ga ago, i.e., planetary leftovers and cometary bodies. If the nonuniformity of the cratering rate could be tested elsewhere in the Solar System, the recalibrated lunar chronology, corrected from spatial variations of the impact flux and approach conditions of impactors, could be extrapolated on other terrestrial bodies such as Mercury and Mars, at least over the last 3.5 billion years. The modeled cratering rate presented here has strong implications for interpreting results of the Artemis program, aiming to explore the South Pole of our satellite, in particular when it will come to link the radiometric age of the samples collected in this region and the crater density of the sampled units.