Narrow Angle Camera Images Research Articles

Time evolution of dust deposits in the Hapi region of comet 67P/Churyumov-Gerasimenko

Aims. We provide a measurement of the seasonal evolution of the dust deposit erosion and accretion in the Hapi region of comet 67P/Churyumov-Gerasimenko with a vertical accuracy of 0.2–0.9 m. Methods. We used OSIRIS Narrow Angle Camera images with a spatial scale of lower than 1.30 m px−1 and developed a tool to monitor the time evolution of 22 boulder heights with respect to the surrounding dust deposit. The tool is based on the measurement of the shadow length projected by the boulder on the surrounding pebble deposit. Assuming the position of the boulders does not change during the observational period, boulder height variations provide an indication of how the thickness of the surrounding dust layer varies over time through erosion and accretion phenomena. Results. We measured an erosion of the dust deposit of 1.7 ± 0.2 m during the inbound orbit until 12 December, 2014. This value nearly balances the fallout from the southern hemisphere during perihelion cometary activity. During the perihelion phase, the dust deposit then increased by 1.4 ± 0.8 m. This is interpreted as a direct measurement of the fallout thickness. By comparing the erosion rate and dust volume loss rate at the Hapi region measured in the coma, the fallout represents ~96% in volume of the ejecta. The amount of the eroded pristine material from the southern hemisphere, together with its subsequent transport and fallout on the nucleus, led us to discuss the pristine water ice abundance in comet 67P. We determine that the refractory-to-ice mass ratio ranges from 6 to 110 in the perihelion-eroded pristine nucleus, providing a pristine ice mass fraction of (8 ± 7)% in mass.

Boulder Distributions Around Young, Small Lunar Impact Craters and Implications for Regolith Production Rates and Landing Site Safety

AbstractWe use Lunar Reconnaissance Orbiter Camera Narrow Angle Camera images to characterize boulder populations around six small (<1 km), young (<200 Ma) impact craters near spacecraft landing sites. The Narrow Angle Camera boulder counts are used to analyze how boulder distributions vary around craters of different sizes and ages. These comparisons inform how various properties affect the distance to which boulders are ejected and the size and density of boulders produced by an impact event. The counts show that boulder population densities decrease with crater age, with few boulders remaining at craters older than a few hundred million years, consistent with results of other studies of boulder degradation rates on the Moon. Variations in boulder distributions around younger craters may provide information regarding impact conditions; South Ray crater has a larger population of small boulders than the larger North Ray crater, which could be explained by variations in impact velocity. Large craters generally excavate more boulders than smaller craters, and the size of the largest boulder ejected is related to crater size by a power‐law function. Larger boulders occur closer to the crater rim (within 2–4 crater radii), whereas smaller boulders occur at all distances. The density of boulders is greater near the crater rim and decreases with increasing radial distance; this data can aid in establishing safe landing zones for future missions. Analyzing boulder distributions across craters of varying ages allows us to test models of boulder breakdown rates, with implications for understanding the Moon's regolith production rate.

Quantitative analysis of isolated boulder fields on comet 67P/Churyumov-Gerasimenko

Aims.We provide a detailed quantitative analysis of isolated boulder fields situated in three different regions of comet 67P/Churyumov-Gerasimenko: Imhotep, Hapi, and Hatmehit. This is done to supply a useful method for analyzing the morphology of the boulders and to characterize the regions themselves.Methods.We used OSIRIS Narrow Angle Camera images with a spatial scale smaller than 2 m px−1and analyzed the size-frequency distribution and the cumulative fractional area per boulder population. In addition, we correlated shape parameters, such as circularity and solidity, with both the spatial and the size-frequency distribution of the three populations.Results.We identified 11 811 boulders in the Imhotep, Hapi, and Hatmehit regions. We found that the Hatmehit and Imhotep areas show power indices in the range of −2.3/−2.7. These values could represent a transition between gravitational events caused by thermal weathering and sublimation, and material formed during collapses that has undergone sublimation. The Hapi area is characterized by a lower power index (−1.2/−1.7), suggesting that those boulders have a different origin. They can be the result of material formed during gravitational events and collapses that has undergone continuous fragmentation. We calculated the cumulative fractional area (CFA) in order to investigate how the area is covered by boulders as a function of their sizes. The Hatmehit and Imhotep regions show a CFA that is well fit by a power law. In contrast, the Hapi area does not show the same trend. We analyzed the fractal distributions, finding that the populations seem to be fractal at all dimensions, except for the Hapi distribution, which shows a possible fractal behavior for small dimensions only. Finally, the average values of the shape parameters reveal solid and roundish boulders in all populations we studied.

Spectrophotometric variegation of the layering in comet 67P/Churyumov-Gerasimenko as seen by OSIRIS

Context.Between August 2014 and September 2016, the ESA space mission Rosetta escorted comet 67P/Churyumov-Gerasimenko (67P) during its perihelion passage. The onboard OSIRIS Narrow Angle Camera (NAC) acquired high-resolution multispectral images of the cometary surface. These datasets allowed a characterization of the spectrophotometric variegation of the layering of the large lobe, correlated with the layer structural elevation.Aims.We perform a spectrophotometric characterization of the outcropping stratification of the small lobe of 67P as a function of its structural elevation, and consequently, a spectrophotometric comparison of the layered outcrops of the two lobes.Methods.We selected two sequences of post-perihelion OSIRIS NAC images (~2.4 au outbound tothe Sun), from which we built up two multispectral images, framing an extended geological section of the onion-like stratification of the small lobe. Then we classified the consolidated areas of the outcropping and the relative coarse deposits that were identified in the multispectral data with a two-class maximum likelihood method. For this, we defined the classes as a function of the structural elevation of the surface.Results.As a result, we identified a brightness variegation of the surface reflectance that is correlated with the structural elevation. The outer class, which is located at higher elevations, appears darker than the inner class. This fits previously obtained results for the large lobe. The reflectance values of the nucleus of 67P tend to decrease with increasing structural elevation.Conclusions.The observed spectrophotometric variegation can be due to a different texture as well as to a different content of volatiles and refractories. We suggest that the outer outcrops appear darker because they have been exposed longer, and the inner outcrops appear brighter because the surface has been more effectively rejuvenated. We interpret this variegation as the result of an evolutionary process.

High-Resolution Large-Area Digital Orthophoto Map Generation Using LROC NAC Images

The Chang'e-5 mission of China is planned to be launched in 2019 to the landing area near Mons Rümker located in Oceanus Procellarum. Aiming to generate a high-resolution and high-quality digital orthophoto map (DOM) of the planned landing area for supporting the mission and various scientific analyses, this study developed a systematic and effective method for large-area seamless DOM production. The mapping results of the Chang'e-5 landing area using over 700 Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images are presented. The resultant seamless DOM has a resolution of 1.5 m, covers a large area of 20° in longitude and 4° in latitude, and is tied to SLDEM2015. The results demonstrate that the proposed method can reduce the geometric inconsistencies among the LROC NAC images to the subpixel level and the positional errors with respect to the reference digital elevation model to about one grid cell size.

Automated Detection of Lunar Rockfalls Using a Convolutional Neural Network

This paper implements a novel approach to automatically detect and classify rockfalls in Lunar Reconnaissance Orbiter narrow angle camera (NAC) images using a single-stage dense object detector (RetinaNet). The convolutional neural network has been trained with a data set of 2932 original rockfall images. In order to avoid overfitting, the initial training data set has been augmented during training using random image rotation, scaling, and flipping. Testing images have been labelled by human operators and have been used for RetinaNet performance evaluation. Testing shows that RetinaNet is capable to reach recall values between 0.98 and 0.39, precision values between 1 and 0.25, and average precisions ranging from 0.89 to 0.69, depending on the used confidence threshold and intersection-over-union values. Mean processing time of a single NAC image in RetinaNet is around 10 s using a GeForce GTX 1080 Ti and GeForce Titan Xp, which is in orders of magnitudes faster than a human operator. The processing speed allows to efficiently exploit the currently available NAC data stack with more than 1 million images in a reasonable timeframe. The combination of speed and detection performance can be used to produce lunar rockfall distribution maps on large spatial scales for utilization by the scientific and engineering community.

Analysis of Lunar Boulder Tracks: Implications for Trafficability of Pyroclastic Deposits

AbstractIn a new era of lunar exploration, pyroclastic deposits have been identified as valuable targets for resource utilization and scientific inquiry. Little is understood about the geomechanical properties and the trafficability of the surface material in these areas, which is essential for successful mission planning and execution. Past incidents with rovers highlight the importance of reliable information about surface properties for future, particularly robotic, lunar mission concepts. Characteristics of 149 boulder tracks are measured in Lunar Reconnaissance Orbiter Narrow Angle Camera images and used to derive the bearing capacity of pyroclastic deposits and, for comparison, mare and highland regions from the surface down to ~5‐m depth, as a measure of trafficability. Results are compared and complemented with bearing capacity values calculated from physical property data collected in situ during Apollo, Surveyor, and Lunokhod missions. Qualitative observations of tracks show no region‐dependent differences, further suggesting similar geomechanical properties in the regions. Generally, bearing capacity increases with depth and decreases with higher slope gradients, independent of the type of region. At depths of 0.19 to 5 m, pyroclastic materials have bearing capacities equal or higher than those of mare and highland material and, thus, may be equally trafficable at surface level. Calculated bearing capacities based on orbital observations are consistent with values derived using in situ data. Bearing capacity values are used to estimate wheel sinkage of rover concepts in pyroclastic deposits. This study's findings can be used in the context of traverse planning, rover design, and in situ extraction of lunar resources.

High-precision co-registration of orbiter imagery and digital elevation model constrained by both geometric and photometric information

The alignment of images to a reference digital elevation model (DEM) has many applications, especially in planetary exploration. In this paper, we propose a novel high-precision co-registration method for pixel-based matching between an image and a reference DEM to rectify the ever-increasing number of orbiter images to DEMs in a unified reference frame automatically. First, the DEM is converted to a simulated image using a hillshading technique based on a photometric model and the illumination conditions of the image. Then, an initial matching between the simulated and input images is performed based on affine scale-invariant feature transform (ASIFT). The rational function model (RFM) of the image is established and used as a geometric constraint. Then, with tie points (TPs) generated by the initial ASIFT matching, the RFM geometric model of the image is refined, and the gross errors in the TP set are iteratively eliminated. Finally, a high-precision co-registration by pixel-based Least-Squares (LS) image matching is performed using the refined geometric model. Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) and SLDEM2015 (a combined product of Lunar Reconnaissance Orbiter Laser Altimeter (LOLA) and a DEM generated by the Japanese Selenological and Engineering Explorer (SELENE) terrain camera) images are used in our experiment. Results using 17 NAC images at different latitudes demonstrate that the proposed co-registration method is effective and can attain an accuracy of 18.3 pixels in the image space and 25.17 m (0.5 pixel of the reference DEM) in the object space. The method offers an automatic and high-precision matching of LRO NAC images to SLDEM2015. It is also applicable to the co-registration of other orbital images to a reference DEM.

Analysis of Rock Abundance on Lunar Surface From Orbital and Descent Images Using Automatic Rock Detection

AbstractInformation on the distribution and abundance of rocks on the lunar surface is essential for understanding the characteristics of lunar regolith and for selecting suitable landing sites for lunar exploration missions. This paper first presents a novel automatic rock detection approach based on the gradient differences in illumination direction. Multiple‐source images covering different regions of the lunar surface are then used for rock detection and rock abundance analysis, including the Chang'E‐3 descent images (0.02–0.17 m/pixel) around the landing area, the Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera images (0.3–1.1 m/pixel) at the landing sites of the Chang'E‐3, Luna 17, and Luna 23, and the LRO Narrow Angle Camera image mosaic (1.5 m/pixel) in the Oceanus Procellarum area. A rock abundance model using an exponential form is derived from the results of the abovementioned analysis to describe the overall cumulative fractional area of rocks versus their diameters. The rock detection results and the derived rock abundance estimated by the proposed model are compared with the ground measurements obtained using the rover images of the Chang'E‐3 landing site and the LRO Diviner Radiometer‐derived rock abundance. A comparison analysis indicates that the derived rock abundance model can feasibly represent the rock abundance in various situations on local and large scales. In general, a remarkable consistency is observed between our results and the results obtained using the ground measurements at the Chang'E‐3 landing site and the orbit measurements from the Diviner radiometer, while our rock detection results and rock abundance model exhibit better performance in presenting detailed information in local areas. Further analyses on rock abundance and the crater morphology and other crater characteristics in the Oceanus Procellarum area indicate that it is feasible to use rock abundance information to estimate the surface maturity.

Block adjustment and coupled epipolar rectification of LROC NAC images for precision lunar topographic mapping

The narrow-angle camera (NAC) of the lunar reconnaissance orbiter camera (LROC) uses a pair of closely attached pushbroom sensors to obtain a large swath of coverage while providing high-resolution imaging. However, the two image sensors do not share the same lenses and cannot be modelled geometrically with a single physical model. The irregular image network leads to difficulties in conducting the block adjustment to remove inconsistencies between the NAC images in both intra- and inter-track cases. In addition, the special image network requires two to four stereo models, each with an irregular overlapping region of varying size. The stereo configuration of NAC images also creates severe problems for the state-of-the-art image matching methods. With the aim of using NAC stereo pairs for precision 3D topographic mapping, this paper presents a novel approach to the block adjustment and coupled epipolar rectification of NAC stereo images. This approach removes the internal inconsistencies in a single block adjustment and merges the image pair in the disparity space, thus requiring estimation of only one stereo model. Semi-global matching is used to generate a disparity map for the stereo pair; each correspondence is transformed back to the source image, and 3D points are derived via photogrammetric space intersection. The experimental results reveal that the proposed approach is able to reduce the gaps and inconsistencies caused by the inaccurate boresight offsets between the two NAC cameras and the irregular overlapping regions and to finally generate precise and consistent 3D topographic models from the NAC stereo images.

Effects of illumination differences on photometric stereo shape-and-albedo-from-shading for precision lunar surface reconstruction

Photoclinometric surface reconstruction techniques such as Shape-from-Shading (SfS) and Shape-and-Albedo-from-Shading (SAfS) retrieve topographic information of a surface on the basis of the reflectance information embedded in the image intensity of each pixel. SfS or SAfS techniques have been utilized to generate pixel-resolution digital elevation models (DEMs) of the Moon and other planetary bodies. Photometric stereo SAfS analyzes images under multiple illumination conditions to improve the robustness of reconstruction. In this case, the directional difference in illumination between the images is likely to affect the quality of the reconstruction result. In this study, we quantitatively investigate the effects of illumination differences on photometric stereo SAfS. Firstly, an algorithm for photometric stereo SAfS is developed, and then, an error model is derived to analyze the relationships between the azimuthal and zenith angles of illumination of the images and the reconstruction qualities. The developed algorithm and error model were verified with high-resolution images collected by the Narrow Angle Camera (NAC) of the Lunar Reconnaissance Orbiter Camera (LROC). Experimental analyses reveal that (1) the resulting error in photometric stereo SAfS depends on both the azimuthal and the zenith angles of illumination as well as the general intensity of the images and (2) the predictions from the proposed error model are consistent with the actual slope errors obtained by photometric stereo SAfS using the LROC NAC images. The proposed error model enriches the theory of photometric stereo SAfS and is of significance for optimized lunar surface reconstruction based on SAfS techniques.

Rock size-frequency distributions analysis at lunar landing sites based on remote sensing and in-situ imagery

Rock populations can supply fundamental geological information about origin and evolution of a planet. In this paper, we used Lunar Reconnaissance Orbiter (LRO) narrow-angle camera (NAC) images to identify rocks at the lunar landing sites (including Chang'e 3 (CE-3), Apollo and Surveyor series). The diameter and area of each identified rock were measured to generate distributions of rock cumulative fractional area and size-frequency on a log-log plot. The two distributions both represented the same shallow slopes at smaller diameters followed by steeper slopes at larger diameters. A reasonable explanation for the lower slopes may be the resolution and space weathering effects. By excluding the smaller diameters, rock populations derived from NAC images showed approximately linear relationships and could be fitted well by power laws. In the last, the entire rock populations derived from both NAC and in-situ imagery could be described by one power function at the lunar landing sites except the CE-3 and Apollo 11 landing sites. This may be because that the process of a large rock breaking down to small rocks even fine particles can be modeled by fractal theories. Thus, rock populations on lunar surfaces can be extrapolated along the curves of rock populations derived from NAC images to smaller diameters. In the future, we can apply rock populations from remote sensing images to estimate the number of rocks with smaller diameters to select the appropriate landing sites for the CE-4 and CE-5 missions.

PRECISION 3D SURFACE RECONSTRUCTION FROM LRO NAC IMAGES USING SEMI-GLOBAL MATCHING WITH COUPLED EPIPOLAR RECTIFICATION

Abstract. The Narrow-Angle Camera (NAC) on board the Lunar Reconnaissance Orbiter (LRO) comprises of a pair of closely attached high-resolution push-broom sensors, in order to improve the swath coverage. However, the two image sensors do not share the same lenses and cannot be modelled geometrically using a single physical model. Thus, previous works on dense matching of stereo pairs of NAC images would generally create two to four stereo models, each with an irregular and overlapping region of varying size. Semi-Global Matching (SGM) is a well-known dense matching method and has been widely used for image-based 3D surface reconstruction. SGM is a global matching algorithm relying on global inference in a larger context rather than individual pixels to establish stable correspondences. The stereo configuration of LRO NAC images causes severe problem for image matching methods such as SGM, which emphasizes global matching strategy. Aiming at using SGM for image matching of LRO NAC stereo pairs for precision 3D surface reconstruction, this paper presents a coupled epipolar rectification methods for LRO NAC stereo images, which merges the image pair in the disparity space and in this way, only one stereo model will be estimated. For a stereo pair (four) of NAC images, the method starts with the boresight calibration by finding correspondence in the small overlapping stripe between each pair of NAC images and bundle adjustment of the stereo pair, in order to clean the vertical disparities. Then, the dominate direction of the images are estimated by project the center of the coverage area to the reference image and back-projected to the bounding box plane determined by the image orientation parameters iteratively. The dominate direction will determine an affine model, by which the pair of NAC images are warped onto the object space with a given ground resolution and in the meantime, a mask is produced indicating the owner of each pixel. SGM is then used to generate a disparity map for the stereo pair and each correspondence is transformed back to the owner and 3D points are derived through photogrammetric space intersection. Experimental results reveal that the proposed method is able to reduce gaps and inconsistencies caused by the inaccurate boresight offsets between the two NAC cameras and the irregular overlapping regions, and finally generate precise and consistent 3D surface models from the NAC stereo images automatically.

ELEMENTAL AND TOPOGRAPHIC MAPPING OF LAVA FLOWSTRUCTURES IN MARE SERENITATIS ON THE MOON

Abstract. The detection of lunar lava flows based on local morphology highly depends on the available images. The thickness of lava flows, however, has been studied by many researchers and lunar lava flows are shown to be as thick as 200 m. Lunar lava flows are supposed to be concentrated on the northwestern lunar nearside. In this study we present elemental abundance maps, a petrological map and a digital terrain model (DTM) of a lava flow structure in northern Mare Serenitatis at (18.0° E, 32.4° N) and two possible volcanic vents at (11.2° E, 24.6° N) and (13.5° E, 37.5° N), respectively. Our abundance maps of the refractory elements Ca, Mg and our petrological map were obtained based on hyperspectral image data of the Moon Mineralogy Mapper (M3) instrument. Our DTM was constructed using GLD100 data in combination with a shape from shading based method to M3 and Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) image data. The obtained NAC-based DEM has a very high effective resolution of about 1–2 m which comes close to the resolution of the utilized NAC images without requiring intricate processing of NAC stereo image pairs. As revealed by our elemental maps and DEM, the examined lava flow structure occurs on a boundary between basalts consisting of low-Ca/high-Mg pyroxene and high-Ca/low-Mg pyroxene, respectively. The total thickness of the lava flow is about 100 m, which is a relatively large value, but according to our DEM the lava flow may also be composed of two or more layers.

Geopositioning precision analysis of multiple image triangulation using LROC NAC lunar images

With continuing data acquisition from lunar orbiters, many areas of the lunar surface have been observed multiple times under different viewing conditions. This raises an issue regarding how to select the best stereo sets and achieve the highest 3D geopositioning precision in such areas. This paper presents a comprehensive analysis of the geopositioning precision of multiple image triangulation using Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images. Seven and nine LROC NAC images are used, respectively, for the Apollo-11 and Chang’e-3 landing sites. The photogrammetric methods are developed based on a rigorous camera sensor model and rational polynomial model. Experiments with different combinations of dual images are performed for comparisons at both sites. The results demonstrate that the geopositioning precision, especially the height precision, is improved as the convergence angle increases from near 0°–50°. More importantly, we find that as the convergence angle of a stereo pair increases, the image matching precision decreases approximately linearly, which makes the geopositioning less precise. We also find that the shadow-tip distance and the aspect ratio have roughly linear effect on degrading matching quality. So these two factors also need to be considered when selecting image pairs for stereo mapping. The geopositioning precision is mainly controlled by the convergence angle when it is less than about 10° while the image matching error plays a more critical role when the convergence angle is greater than 10°. Experiments with multiple images indicate that utilizing more images produces higher precision than almost all dual-image models; meanwhile, using fewer images can produce better precision than using all available images together. A progressive selection method is proposed to find the best image combination for maximum precision and effectiveness.

GEOPOSITIONING PRECISION ANALYSIS OF MULTIPLE IMAGE TRIANGULATION USING LRO NAC LUNAR IMAGES

Abstract. This paper presents an empirical analysis of the geopositioning precision of multiple image triangulation using Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images at the Chang’e-3(CE-3) landing site. Nine LROC NAC images are selected for comparative analysis of geopositioning precision. Rigorous sensor models of the images are established based on collinearity equations with interior and exterior orientation elements retrieved from the corresponding SPICE kernels. Rational polynomial coefficients (RPCs) of each image are derived by least squares fitting using vast number of virtual control points generated according to rigorous sensor models. Experiments of different combinations of images are performed for comparisons. The results demonstrate that the plane coordinates can achieve a precision of 0.54 m to 2.54 m, with a height precision of 0.71 m to 8.16 m when only two images are used for three-dimensional triangulation. There is a general trend that the geopositioning precision, especially the height precision, is improved with the convergent angle of the two images increasing from several degrees to about 50°. However, the image matching precision should also be taken into consideration when choosing image pairs for triangulation. The precisions of using all the 9 images are 0.60 m, 0.50 m, 1.23 m in along-track, cross-track, and height directions, which are better than most combinations of two or more images. However, triangulation with selected fewer images could produce better precision than that using all the images.

GEOPOSITIONING PRECISION ANALYSIS OF MULTIPLE IMAGE TRIANGULATION USING LRO NAC LUNAR IMAGES

This paper presents an empirical analysis of the geopositioning precision of multiple image triangulation using Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images at the Chang’e-3(CE-3) landing site. Nine LROC NAC images are selected for comparative analysis of geopositioning precision. Rigorous sensor models of the images are established based on collinearity equations with interior and exterior orientation elements retrieved from the corresponding SPICE kernels. Rational polynomial coefficients (RPCs) of each image are derived by least squares fitting using vast number of virtual control points generated according to rigorous sensor models. Experiments of different combinations of images are performed for comparisons. The results demonstrate that the plane coordinates can achieve a precision of 0.54 m to 2.54 m, with a height precision of 0.71 m to 8.16 m when only two images are used for three-dimensional triangulation. There is a general trend that the geopositioning precision, especially the height precision, is improved with the convergent angle of the two images increasing from several degrees to about 50°. However, the image matching precision should also be taken into consideration when choosing image pairs for triangulation. The precisions of using all the 9 images are 0.60 m, 0.50 m, 1.23 m in along-track, cross-track, and height directions, which are better than most combinations of two or more images. However, triangulation with selected fewer images could produce better precision than that using all the images.

Cartography of the Luna-21 landing site and Lunokhod-2 traverse area based on Lunar Reconnaissance Orbiter Camera images and surface archive TV-panoramas

The Lunar Reconnaissance Orbiter Camera (LROC) system consists of a Wide Angle Camera (WAC) and Narrow Angle Camera (NAC). NAC images (∼0.5 to 1.7m/pixel) reveal details of the Luna-21 landing site and Lunokhod-2 traverse area. We derived a Digital Elevation Model (DEM) and an orthomosaic for the study region using photogrammetric stereo processing techniques with NAC images. The DEM and mosaic allowed us to analyze the topography and morphology of the landing site area and to map the Lunokhod-2 rover route. The total range of topographic elevation along the traverse was found to be less than 144m; and the rover encountered slopes of up to 20°. With the orthomosaic tied to the lunar reference frame, we derived coordinates of the Lunokhod-2 landing module and overnight stop points. We identified the exact rover route by following its tracks and determined its total length as 39.16km, more than was estimated during the mission (37km), which until recently was a distance record for planetary robotic rovers held for more than 40 years.

Coordinates of anthropogenic features on the Moon

High-resolution images from the Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) reveal the landing locations of recent and historic spacecraft and associated impact sites across the lunar surface. Using multiple images of each site acquired between 2009 and 2015, an improved Lunar Reconnaissance Orbiter (LRO) ephemeris, and a temperature-dependent camera orientation model, we derived accurate coordinates (<12m) for each soft-landed spacecraft, rover, deployed scientific payload, and spacecraft impact crater that we have identified. Accurate coordinates enhance the scientific interpretations of data returned by the surface instruments and of returned samples of the Apollo and Luna sites. In addition, knowledge of the sizes and positions of craters formed as the result of impacting spacecraft provides key benchmarks into the relationship between energy and crater size, as well as calibration points for reanalyzing seismic measurements acquired during the Apollo program. We identified the impact craters for the three spacecraft that impacted the surface during the LRO mission by comparing before and after NAC images.

Photometry of dust grains of comet 67P and connection with nucleus regions

Multiple pairs of high-resolution images of the dust coma of comet 67P/Churyumov-Gerasimenko have been collected by OSIRIS onboard Rosetta allowing extraction and analysis of dust grain tracks. We developed a quasi automatic method to recognize and to extract dust tracks in the Osiris images providing size, FWHM and photometric data. The dust tracks characterized by a low signal-to-noise ratio were checked manually. We performed the photometric analysis of 70 dust grain tracks observed on two different Narrow Angle Camera images in the two filters F24 and F28, centered at lambda = 480.7 nm and at lambda = 743.7 nm, respectively, deriving the color and the reddening of each one. We then extracted several images of the nucleus observed with the same filters and with the same phase angle to be compared with the dust grain reddening. Most of the dust grain reddening is very similar to the nucleus values, confirming they come from the surface or subsurface layer. The histogram of the dust grain reddening has a secondary peak at negative values and shows some grains with values higher than the nucleus, suggesting a different composition from the surface grains. One hypothesis comes from the negative values point at the presence of hydrated minerals in the comet.