Lunar Images Research Articles

Study on the volume of landslides in lunar impact craters

The lunar exploration project is of great significance, among which the statistics and measurement of lunar landslide are an important part of lunar exploration. With the help of Google Earth software, lunar image data were obtained, and the volume calculation and analysis of landslides in 14 meteorite impact craters on the Moon were performed using the Alfred S. McEwen formula. It is found by calculation and observation that the diameter of the crater is proportional to the volume of the landslide in most of the meteorite impact craters on the moon.

Automatic detection for small-scale lunar impact crater using deep learning

The impact crater is the most dominant geomorphic structural units over the planetary surface and its accurate extraction is of great significance to investigate the evolution of the Moon, the impact history of the solar system and the space environment. Through the impact crater’s identification, especially small-scale, and their spatial distribution characteristics, the impact flux, morphological characteristics, age of impact craters and surface degradation can be revealed. Therefore, this paper presents an automatic method for the impact crater detection, especially small-scale ones, using anchor-free deep learning. Due to the limitation of traditional object proposals for detecting different types of impact craters, we retrain the anchor-free CenterNet model using a transfer learning strategy, where the detection task of impact crater is formulated into the detection of its center point and regression of its property (i.e., size) without non-maximal suppression. We select the stacked Hourglass network as backbone to aggregate different levels of feature for enhancing the capability of estimating the impact crater centers. Moreover, we find the center points of impact craters on the image features’ heatmap only based on their locations, instead of box overlap, which allows us to detect different types of impact craters, even the impact craters that contain other impact craters. The model is trained in an end-to-end manner and applied to detect the impact craters on the lunar images between ±50° of latitude, with the spatial resolution of 100 m/pixel, from Wide Angle Camera (WAC) onboard Lunar Reconnaissance Orbiter (LRO) mission. The obtained results are compared relative to an existing crater database both qualitatively and quantitatively that suggests the reliability and robustness of the developed method in the automatic detection of small-scale impact craters, where the smallest one is 500 m. Moreover, the developed method is capable to detect different types of impact craters, including dispersal and connective ones, with the recall of 73.66% and precision of 78.27% compared with an existing crater database. The code is publicly available at https://github.com/ShuoweiZhang/crater_detection.

Characterization of the East—West Spatial Uniformity for GOES-16/17 ABI Bands Using the Moon

The Advanced Baseline Imager (ABI) is the primary instrument onboard the NOAA Geostationary Operational Environmental Satellite-R Series (GOES-R) satellites, providing continuous weather imagery over the vast area in the Western Hemisphere. It is imperative to ensure consistent calibration accuracy within the instrument’s field of regard (FOR). This paper characterized the spatial uniformity in the east–west (EW) direction for the six ABI visible and near-infrared (VNIR) bands of the first two GOES-R satellites, GOES-16 (G16) and GOES-17 (G17), using a special collection of lunar chasing images during their post-launch testing and post-launch product testing (PLT/PLPT) periods. The EW response versus scan-angle (RVS) is examined with the normalized lunar irradiance ratios at varying scan angles combined from multiple lunar-chasing events. The impacts of straylight from the Earth were found in some of the B01–B03 lunar images. The straylight, including those scattered into the spacelook scenes near the polar regions and those leaked into space near the Moon, can cause RVS variation up to 1% for B01 and to a lesser magnitude for the other two bands. Straylight correction algorithms are applied for the accurate ABI lunar image irradiance calculation. After the corrections, the RVS variation is reduced to less than 0.3% for all the VNIR bands of both G16/17 in full-disk (FD) images. Results of this study also confirm that the Global Space-based Inter-Calibration System (GSICS) Implementation of the ROLO (GIRO) model has high relative accuracy for the ABI VNIR bands when the lunar images are collected within a relatively short time. The method described in this paper can be applied to validate the EW spatial uniformity for imagers on other geostationary satellites, including the recently launched GOES-18 and the future GOES-U satellites.

Augmented Reality Based on Apollo Lunar Imagery: Searching for Stars and Adding Virtual Objects

Abstract Based on photogrammetric models of the first three Apollo landing sites, we have created a method to project virtual objects onto photos taken on the lunar surface. We have applied this method to search for stars in high-resolution scans of Apollo lunar photos and to restore views of the starry sky in some iconic images. Our method can be used to incorporate computer-generated 3D graphics, such as constellation boundaries, and coordinate and contour lines, into lunar images. This research has several applications, including the visualization of digital terrain models, the creation of a virtual planetarium based on lunar photos, and demonstration of object motion in lunar gravity for educational purposes.

L2AMF-Net: An L2-Normed Attention and Multi-Scale Fusion Network for Lunar Image Patch Matching

The terrain-relative navigation (TRN) method is often used in entry, descent and landing (EDL) systems for position estimation and navigation of spacecraft. In contrast to the crater detection method, the image patch matching method does not depend on the integrity of the database and the saliency of the crater features. However, there are four difficulties associated with lunar images: illumination transformation, perspective transformation, resolution mismatch, and the lack of texture. Deep learning offers possible solutions. In this paper, an L2-normed attention and multi-scale fusion network (L2AMF-Net) was proposed for patch descriptor learning to effectively overcome the above four difficulties and achieve lunar image patch matching accurately and robustly. On the one hand, an L2-Attention unit (LAU) was proposed to generate attention score maps in spatial and channel dimensions and enhance feature extraction. On the other hand, a multi-scale feature self and fusion enhance structure (SFES) was proposed to fuse multi-scale features and enhance the feature representations. L2AMF-Net achieved a 95.57% matching accuracy and excellent performance compared with several other methods in lunar image patch dataset generated in this paper. Experiments verified the illumination, perspective and texture robustness of L2AMF-Net and the validity of the attention module and feature fusion structure.

Multiple-instrument-based spectral irradiance of the Moon

A model of lunar spectral irradiance incorporates data from multiple spacecraft and surface telescopic observations. Using 12 data sources derived from 90,000 lunar images, models that are smooth across both geometry and wavelength and involve only about 35 derived coefficients are found with a mean weighted residual of <0.5 % . An irradiance libration model derived from lunar orbiter observations is used to reduce the number of coefficients required. Derivation uses iterative assignment of a single scaling factor for each band in each instrument, which is effectively the long-term lunar calibration coefficient for that band. Calibration of 26 instruments and two other published models reveals that although eight instruments agree within about 3% over 400 to 840 nm, some large biases exist. The model provides a sensitive assessment of instrument response trends.

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.

Focused Lunar Imaging Experiment Using the Back Projection Algorithm Based on Sanya Incoherent Scatter Radar

Previous ground-based, radar lunar imaging experiments have usually employed the Range-Doppler (RD) algorithm. This algorithm performs in the frequency domain and has high computational efficiency. However, in the case of a long coherent integration time, the defocus phenomenon will appear, and the image will be smeared. This study proposes the use of the back projection (BP) algorithm to obtain focused lunar images to solve this problem. The BP algorithm is a time-domain algorithm which is frequently employed in synthetic aperture radar (SAR) imaging and can theoretically achieve the focused imaging of each pixel in an arbitrarily long coherent integration time. However, the largest drawback of this algorithm is its high computational complexity. Therefore, this study only applies this method to map local regions of the moon. We select Sanya incoherent scatter radar (SYISR) as the transmitting and receiving device and utilize the linear frequency modulation chirp pulse to transmit right-hand, circularly polarized electromagnetic waves and to receive left-hand, circularly polarized echoes. RD and BP algorithms are simultaneously adopted to image the Pythagoras crater region, and a contrastive analysis is performed. The results show that the BP algorithm can be well applied to a ground-based, radar lunar imaging experiment and that it has a better focusing performance, but the effect is not as obvious as expected. Thus, the processing method needs to be further improved. In addition, the computational efficiency of BP is very low, and certain fast algorithms need to be applied to improve it.

Robust Crater Detection Algorithm Based on Maximum Entropy Threshold Segmentation

For future lunar exploration and planetary missions, the digital elevation model (DEM) of the target object may not be well prepared before the mission, so developing a new robust crater detection algorithm (CDA) without prepared high-precision DEM is needed to meet the requirements of a high-reliability and high-precision detection and navigation system. In this paper, we presented a new robust lunar CDA method based on maximum entropy threshold segmentation. By calculating the entropy distribution of the ternary image, the threshold for retaining the maximum amount of image information is selected adaptively, a variety of evaluation indicators are proposed, and a multiple-indicator constraint matrix is constructed to realize the extraction and fitting of the craters. The proposed method has the following advantages: (1) it has strong robustness and is capable of extracting complete craters under multiple illumination conditions, which makes it suitable for the extraction of large-scale planetary and lunar images; (2) the extracted crater edges are clear and complete and do not merge with the surrounding environment edge; and (3) it avoids the problem of parameter sensitivity that is present in a traditional CDA algorithm. The proposed method was verified using an image taken by the Chang’e-2 lunar probe, and a comparison with the traditional method based on morphology and adaptive Canny edge detection shows that the number of craters detected increases by more than 35%, while the computational efficiency is improved by more than 40%.

Empirical Analysis of Feature Points Extraction Techniques for Space Applications

Recently, space research advancements have widened the scope of many vision-based techniques. Computer vision techniques with manifold objectives require that valuable features are extracted from input data. This paper attempts to analyze known feature extraction techniques empirically; Scale Invariant Feature Transform (SIFT), Speeded up robust features (SURF), Oriented fast and Rotated Brief (ORB), and Convolutional Neural Network (CNN). A methodology for autonomously extracting features using CNN is analyzed in more detail. The autonomous process demonstrates the use of convolutional neural networks for feature extraction. Those techniques are studied and evaluated empirically on lunar satellite images. For analysis, a dataset containing different affine transformations of a video frame is generated from a sample lunar descent video. The nearest neighbor algorithm is then applied for feature matching. For an unbiased evaluation, a similar process of feature matching is repeated for all the models. Well-known metrics like repeatability and matching scores are employed to validate the studied techniques. The results show that the CNN features showed much better computational efficiency and stable performance concerning matching accuracy for lunar images than other studied algorithms.

Lunar Images in the Cultural Traditions in the South of Western Siberia in the Second Half of the 3rd – the Beginning of the 2nd Millennium BC

The article highlights a series of multicultural images of the developed Bronze Age of the south of Western Siberia, which are connected by a common semantic meaning. The author substantiates lunar semantics of Okunev, Krokhalevka and Samus anthropomorphic characters conveying the idea of significant moon cycles, mainly the new moon, the first quarter and the full moon. The worldviews of the population of these cultures are reconstructed, the probable sources of the lunar cult and the peculiarities of similar views in each community are investigated. Specific iconographic methods of transmitting similar ideological stereotypes by various visual means inherent in the cultural groups of the Upper Ob Region, the Lower Tom Region and the Middle Yenisei in the second half of the 3rd – the beginning of the 2nd millennium BC are revealed

동서 문학 비교연구를 위한 방법론적 제언-달의 이미지 비교를 예로 들어

지금까지 비교문학 연구가 동서 문학의 동질성을 강조해왔다면 최근 연구는 형식론의 도입으로 두 문학의 다른 전통을 이해하고자 하는 경향을 보인다. 본고는 최근의 논의 중 마이너의 장르론과 입의 모델론을 도입하여 비교문학 연구의 새로운 방향을 달의 이미지 비교를 예로 들어 제시한다. 달의 이미지는 일반적으로 중국의 당시와 유럽의 낭만시를 중심으로 비교된다. 본고는 이런 비교 쌍이 장르상 서정시라는 점에서 대응할 뿐 대표성과 시대성에 있어 대응하지 않음을 지적하고 동서문학에서 전통적인 달의 이미지를 살펴보기 위해 이백의 「파주문월」과 스펜서의 「뮤터빌리티에 관한 2개의 칸토」를 비교하여 읽는다. 각각 서정시와 서사시에 해당하는데 달의 이미지와 신화와의 관계 및 달의 상징성을 해석하는데 있어 두드러진 차이를 보인다. 이런 비교 읽기를 통해 본고는 문학과 신화의 상관성에 대한 비교연구, 전근대기 문학에 대한 비교연구의 확대, 달과 서정시 간의 친연성에 대한 연구, 그리고 탈근대적 시각에서 자연과 조화를 이루는 동양적 상상력의 회복가능성에 대한 연구라는 네 가지 연구 방향을 제시한다.

FY-3D MERSI On-Orbit Radiometric Calibration from the Lunar View

Limited by the on-orbital calibration capability, scaling the measured radiance in accuracy and stability is challenging for the Earth observation satellites in the reflective solar bands (RSBs). Although the lunar calibration is a well-developed technique in the RSBs, limited work has been done for Chinese Earth observation satellites. To improve the on-orbital calibration performance, the advanced MEdium Resolution Spectral Imager (MERSI II), which is the primary payload of the fourth satellite of the Fengyun 3 Series (FY-3D), expands the space view angle of the imager in order to capture better lunar images. In this study, we propose an absolute radiometric calibration method based on the FY-3D/MERSI lunar observation data. A lunar irradiance model named ROLO/GIRO has been used together with the necessary data procedures, including dark current count estimation, single pixel irradiance calculation, and full disk lunar irradiance calculation. The calibration coefficients obtained by the lunar calibration are compared with the pre-launch laboratory calibration. The results show that the deviations between the two calibration procedures are in a reasonable range in general. However, a relatively high non-linear response was found in the low energy incidence for some detectors, which leads to the large deviation in the corresponding bands. This study explored an ideal and independent method to validate MERSI on-orbit radiometric performance. The lunar calibration practiced for MERSI also gave a valuable example that can be recommended to the other Chinese Earth observation satellites.

Modeling and application analysis of the pixel-spatial resolution of Yutu 2 rover with large-scale transformed images

<p indent="0mm">In Chang’E-4 lunar exploration mission, Yutu 2 rover tasks are planned and controlled by teleoperation. The rover usually travels between 6 and 9 m to cover a large distance for each planned travel; as a result, the images taken by the Yutu 2 rover differ saliently in scale, rotation, and translation. Consequently, the overlap areas of these images have small sizes, especially when the resolution and morphology of the overlap areas are very different, thereby resulting in image matching difficulties to image matching, and hindering automatic visual positioning between adjacent stations. In this paper, a general pixel-spatial resolution model focusing on lunar images is proposed by introducing the inclination angle to existing models. We further discuss in detail the variation of image scales and the rate of feature matching in terms of station distances, imaging distances, and lunar surface inclination angles or their combinations, and develop the mechanism to choose the equivalent minimal factor subset. Finally, the proposed model is evaluated by using the station data of the Yutu 2 rover collected on the first and second lunar days. Our analysis classified the influence of the pixel-spatial resolution ratio on the rate of image matching into four types. Thus, a general rule was given for describing the image matching rate under different stations, and the constraints to determine the distance and location of adjacent stations in actual tasks were presented. The proposed approach exhibits the potential to be utilized for improving the automation of localization in subsequent lunar explorations.

Matching Method of Lunar Remote Sensing Image Based on Laplacian

In recent years, there is an emerging interest in the exploration of the lunar surface. We can use many images of the lunar with different resolutions sent by more and more satellites that launched to the Moon. However, research on the lunar image matching still faces various difficulties. Significantly differing from the complex physical structure of the Earth’s surface, the lunar surface is mainly craters, ridges and mountains, and its simple physical structure directly leads to the difficulty of extracting the same name points; satellite sensors are easily influenced by multiple factors while imaging, such as the shooting angle of the forward-looking and backward-looking linear array, the sun’s angle of incidence, which is likely to cause some differences in the brightness of the images, and it makes the image matching choose the appropriate image enhancement method. In this paper, taking Chang’e II CCD lunar image as an example, firstly we propose a method of extracting the same-name point of lunar images based on Laplacian and image grayscale matching, and compare it with the commonly used SIFT + RANSAC algorithm, the accuracy rate and processing speed rate increases by 4.55% and 58.3% respectively, which verifies the scientificity and rationality of this method. Our work provides a new idea for the study of lunar image matching technology and lays foundation for the image-based lunar surface research and development.

Deriving terrain factors from high-resolution lunar images: A case study of the Mons Rümker Region

Mons Rümker is a preferred candidate landing region for China's Chang'e-5 (CE-5) mission, from where it is of great significance to select safe landing areas. Lunar terrain factors from Digital Elevation Model (DEM) data, limited by their low resolutions (~10 m/pixel), are inapplicable to evaluating the lunar landing area safety, in spite of the fact that lunar remote sensing imagery has higher resolution (~50 cm/pixel). In this paper, we extracted terrain factors in divided square girds by the aid of the high-resolution Lunar Reconnaissance Orbiter (LRO) Narrow-angle Camera (NAC) images, namely, flat area percentage (Fap), distribution pattern of uneven objects (NNI) based on the double-threshold Otsu method, and roughness based on gray level histogram analysis. Mons Rümker can be divided into four geological units, named as LD, B1, B2, and B3, respectively. Unit B1 has a higher roughness and a lower Fap. Unit B2 and B3 are characterized with the highest Fap and the lowest roughness. NNIs of Unit B1, B2, and B3 are >1 while LD's is <1. Thus, the distribution patterns of uneven objects in Unit LD are clustered but dispersed in all Unit B1, B2, and B3. This paper tends to take Fap and roughness as the main terrain factors to evaluate the safety for CE-5 landing in Mons Rümker with NNI being a supplement to Fap. According to Standard 1–3 mentioned in this paper, we would classify the divided square grids of the Mons Rümker region as the safe or unsafe areas, and then discriminate five potential landing areas for CE-5 probe safe landing.

Modeling Radar Albedos of Laboratory‐Characterized Particles: Application to the Lunar Surface

AbstractWe analyze lunar images obtained by the Mini Radio Frequency instrument onboard the Lunar Reconnaissance Orbiter to interpret the anomalous radar scattering observed in some lunar craters. We compare the radar signatures of the crater floors to those of the regions external to the crater rim and show that there is a systematic difference between the radar albedo trends of the two regions. Using numerical simulations to compute radar scattering properties of rock and ice particles, we demonstrate that the difference is caused partly by the near‐surface bulk volume density or the underlying fine‐grained regolith and partly by the shape and size distributions of centimeter‐to‐decimeter‐scale rubble. We show that while the size distribution of wavelength‐scale particles plays the major role in the observed radar albedos, if the size distribution is fixed, the particle shapes can play a greater role than the composition; therefore, the icy material is indistinguishable from silicate‐rich material unless the abundance of ice in the particles plays a major role in the shape of the particles.

A study of a two-dimensional scanned lunar image for Advanced Technology Microwave Sounder (ATMS) geometric calibration

Abstract. The NOAA-20 satellite was successfully launched on 18 November 2017. It carries five key instruments, including the Advanced Technology Microwave Sounder (ATMS). On 31 January 2018, the spacecraft performed a pitch-over maneuver operation, during which two-dimensional lunar scan observations were collected. In this study, a technique has been developed by which the ATMS on-orbit geometric calibration accuracy can be validated based on this lunar scan dataset. The fully calibrated data are fitted to the antenna pattern coordinates via a Gaussian function. The deviation in the center of the fit function from the origin of the frame is taken to be the boresight pointing error of the instrument. This deviation is further transformed to the Euler angle roll and pitch defined in the spacecraft coordinate system. The estimated ATMS boresight pointing Euler angle roll (pitch) is 0.05∘ (0.22∘) at K band, −0.07∘ (0.25∘) at Ka band, 0.02∘ (0.24∘) at V band, -0.07∘ (-0.08∘) at W band, and -0.04∘ (0.02∘) at G band. The results are validated by comparing them with those derived from the coastline inflection point method, showing a good correlation. For the sounding channels where the coastline method is inapplicable, the lunar scan method is still capable of delivering reasonable estimations of their geometric calibration errors.

High‐Resolution Terrain Analysis for Lander Safety Landing and Rover Path Planning Based on Lunar Reconnaissance Orbiter Narrow Angle Camera Images: A Case Study of China's Chang'e‐4 Probe

AbstractChina's Chang'e‐4 (CE‐4) probe will explore the South Pole‐Aitken basin in late 2018. Its preselected landing area is located on the southeastern floor of the Von Kármán crater. Landing experience of China's Chang'e‐3 probe may not be applied to CE‐4 mission directly because the topography of lunar farside is more rugged. Moreover, due to scale dependence and smooth effects, the previous topographic studies derived from digital elevation model data with lower resolution cannot represent the meter‐scale topographic features. Because of low time and space complexities in lunar images, image segmentation algorithm is especially suitable for recognizing lunar features. We divided the narrow angle camera (NAC) mosaic image into three parts: dark area, bright area, and flat area, based on a double‐threshold Otsu method. The first two parts corresponded to the undulating areas (positive and negative terrains). And then we calculated the flat area percentage (Fap) of the previous successful lunar landing missions (including Chang'e‐3, Apollo, Surveyor, and Luna series) and obtained the Fap threshold (&gt;0.6) for lunar safe landing. According to Fap map (~1.5 m per pixel) of CE‐4 preselected landing area, the divided square grids with a size of 0.01° can be classified into safe grids (Fap &gt; 0.6) and unsafe grids (Fap ≤ 0.6). The CE‐4 preselected landing areas can be greatly reduced to five potential landing areas. In the last, we proposed a route planning method, which took both the distance and security into account, for CE‐4 rover to dynamically generate a safe and short route between current grid and target grid.

Aqua MODIS Electronic Crosstalk Survey: Mid-Wave Infrared Bands

The Moderate Resolution Imaging Spectroradiometer (MODIS) on board NASA’s Aqua polar-orbiting satellite has long been known to be subjected to electronic crosstalk. Its signatures are clearly visible in images of the lunar disk by various bands, which are routinely obtained during scheduled roll maneuvers. Electronic crosstalk can potentially impact Level 1B products, causing image artifacts such as striping and radiometric bias. However, a comprehensive effort in mapping the sending/receiving bands and detectors, deriving the crosstalk coefficients, and assessing the impact of the crosstalk contamination on the Level 1B product for Aqua’s mid-wave IR bands (3.75– 4.52 $\mu \text{m}$ ) had been lacking. In this work, we surveyed lunar images by the Aqua MODIS bands that are connected to electronic output 2 of the SWIR/MWIR FPA, identifying all detectors affected by electronic crosstalk contamination and determined which bands and detectors are sending the contaminating signal. By assuming a linear model to describe the contamination, we derived linear crosstalk coefficients for the bands/detectors concerned from lunar images and used these to generate corrected Earth Level 1B images for the mid-wave IR bands and assessed the impact of the electronic crosstalk on the Level 1B imagery.