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Introduction: Study of near-Earth objects (NEOs) is crucial to better understand the origin, formation and the evolution of the solar system. In particular, compositional, morphological and orbital characterisation of NEOs sheds light on the delivery of water and organics [1,2,3] to the prebiotic Earth, while ironically, some NEOs could be potential hazards for life on Earth [4]. In this context, we apply the G-mode multivariate statistical clustering method [5,6,7] on the orbital parameters of the currently available NEOs population, to probe potential associations with their spectral classification [8,9,10]. Data and Methods: G-mode method leads to an automatic statistical clustering of a sample containing N objects (NEOs in this case), described by M variables with the only control imposed by the user being the confidence level q1, expressed in terms of σ. The objects that cannot be associated to a cluster are separated and considered as outliers. We apply G-mode multivariate statistical clustering analysis to variables defining NEOs to determine clustering of objects. Our sample consists of 14132 NEOs, filtered based on their orbital uncertainty. Our input parameters to the G-mode method are twofold. First, in approach 1 (A1) we used three variables and their uncertainties as inputs: inclination (i), eccentricity (e) and semi-major axis (a) of the orbit. In approach 2 (A2) we used six inputs by including the argument of perihelion (ω), Tisserand parameter with respect to Jupiter (TJ) and the absolute magnitude (H) and their respective uncertainties in addition to those used in A1. Results: In A1, we obtained only one cluster at q1=3σ (accurate classification probability of 99.7%), which meant that the NEOs in this cluster are homogeneous in terms of the three orbital elements used. As we gradually lowered the value of q1, hence the confidence level, we noticed that more clusters got seeded and populated. We report in Table 1, mean parameter values with the median absolute deviation for 8 clusters obtained at q1=1.78σ. In addition to reporting the statistics of obtained clusters, we have also reported the outlier group of NEOs in the row indexed by 0. Among the reported clusters, cluster 1 (C1) corresponds to the background population of NEOs as their statistics are comparable to those of all hitherto discovered NEOs. C2 represents NEOs with relatively moderate inclination. C3, despite having relatively small number of NEOs, is constrained by well-behaved low-inclined, quasi-circular Earth-like orbits owing to their very low median absolute deviations. The very low mean H implies that these NEOs are relatively smaller with a distribution peak in the range of 5-15 meters of diameter. C5, C6 and C7 are of particular interest, for they could be associated with Jupiter-family cometary nuclei (2 < TJ < 3) as per their mean TJ. As such, the objects in these three clusters could potentially be extinct cometary nuclei. These clusters also have relatively higher eccentricities, akin to cometary orbits. We have checked available taxonomic classifications of NEOs [11,12,13] in the literature to get an insight into the composition of the objects. Although taxonomic classifications are not available for the majority of members in the clusters, we find that (i) C5 contains 3 C-types, 2 D-types and 0 S-types (ii) C6 contains 3 D-types and 4 S-types (iii) C7 contains 2 B-types, 3 C-types, 2 D-types and 1 S-type. Therefore we argue that C5 and C7 can be associated to primitive carbonaceous compositions while C6 can be associated to both carbonaceous and silicate-dominated compositions. To get more insights about the obtained G-mode clusters and further test these results, we applied a dynamic model to find their potential escape regions in the main belt [14]. This dynamical model, the Granvik model hereafter, traces with scrutiny the escape paths of objects from the main-belt to near-Earth space and the model accounts for the Yarkovsky effect [15]. Given the orbital elements and absolute magnitude of an NEO, it resolves a probability distribution function, built up of seven discrete values for seven escape regions. The results obtained with the Granvik model are shown in Fig. 1 for the clusters obtained for the G-mode run at q1=1.78σ in A1. Fig. 1. Probability distributions for the G-mode clusters obtained at 1.78σ for A1 to emanate from any of the seven escape regions. These results imply that most of the clusters have higher probability to emanate via ν6 secular resonance, known to be the most dominant escape path from the main-belt to the near-Earth space [16]. We observe that C5 and C7 have significant probabilities to emanate from outer-belt sources such as 2:1 mean motion resonance of Jupiter and JFCs. Thus, our dynamic modelling reinforces and corroborates existing results, pointing towards a primitive origin for the NEOs in these two clusters. Similiary, we will present the results of A2 and discuss their implications. Acknowledgements: We acknowledge the financial support from Agenzia Spaziale Italiana (ASI, contract No. 2017-37-H.0 CUP F82F17000630005) and funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 870403. References: [1] Marty, B., Guillaume, A. et al. 2016, Earth and Planetary Science Letters, Volume 441,Pages 91-102 [2] Altwegg, K, Balsiger, H, Bar-Nun, A. et al. 2015, Science, Vol. 347,6220,1261952 [3] Ehrenfreund, P. & Sephton 2006, Faraday Discuss., The Royal Society of Chemistry,133,277-288 [4]Perna, D., Barucci M.A., Fulchignoni M. 2013, Astronomy and Astrophysics Review,Vol.21,65 [5] Barucci, M.A., Capria, M.T., Coradini, A. et al. 1987,Icarus,72,304 [6] Gavrishin, A.I., et al. 1992, Earth, Moon and Planets,59,141-152 [7] Barucci, M.A., Belskaya, I., Fulchignoni, M. et al. 2005,AJ130,1291 [8] Bus, S.J., & Binzel, R.P. 2002, Icarus,158,146 [9] DeMeo, F.E., Binzel, R. P., Slivan, S.M. & Bus, S. J. 2009,Icarus,202,160-180 [10] DeMeo, F.E., Alexander, C.M.O., Walsh, K.J.et al. 2015, Asteroids IV,13-41 [11] Perna, D., Barucci,M.A. et al. 2018, Planetary and Space Science,157,82-95 [12] Devogèle, M., Moskovitz, N. et al. 2019, The Astronomical Journal, American Astronomical Society,158,196 [13] Ieva, S., Dotto, E. et al. 2020,A&A,644,A23 [14] Granvik, M., Morbidelli, A., Jedicke, R., et al. 2018,Icarus,312,181 [15] Vokrouhlický, D., Bottke, W. F., Chesley, S.R., Scheeres, D.J., & Statler, T.S. 2015, in Asteroids IV,509–531 [16] Bottke, W.F., Morbidelli,A., Jedicke,R., et al. 2002,Icarus,156,399

Introduction: In late September 2022 the NASA mission DART will perform the first test of the kinetic impactor technique conceived to deflect an asteroid en route to Earth. With a mass of 650 kg and an impact velocity of about 6.6 km/s, DART is expected to change the binary orbital period of Dimorphos, the 160-m moon of Didymos Near-Earth Asteroid (NEA), by about 10 min, an effect that can be easily measured by ground-based telescopes [1] [2]. LICIACube: LICIACube (Light Italian Cubesat for Imaging of Asteroids) is the first purely Italian spacecraft to be operated in deep space. It is a 6U cubesat platform developed by the Argotec company and managed by the Italian Space Agengy (ASI) with the aim to contribute in the NASA DART Planetary Defence objective and to perform autonomous science at the asteroid [3]. LICIACube has been launched together with DART on November 2021: after a 10-months interplanetary cruise it will be released 10 days before the foreseen DART impact on Dimorphos and it will be guided along its fly-by trajectory with a closest approach (CA) of around 55 km from the Dimorphos’ surface (Fig. 1). Figure 1 – The nominal LICIACube mission LICIACube is equipped with two different payloads named LEIA (Liciacube Explorer Imaging for Asteroid) and LUKE (Liciacube Unit Key Explorer) (Fig. 2). High-resolution images, obtained by LEIA at the CA (up to 1.5 m/px) will allow us to study the surface morphology of Dimorphos and the presence of boulders/large blocks on its surface. The LUKE data (up to 8 m/px at CA, with a RGB filter system) will give us also the opportunity to investigate the composition of Dimorphos throughout spectrophotometric analyses. It will then be possible to map the surface composition of the object and to derive the surface heterogeneity at the observed scale. After imaging the DART impact, during the fly-by the two instruments will allow us to investigate the nature of the target, explore the difference between the impact and non-impact regions, and to study the nature and the evolution of the produced plume, in order to deeply investigate the composition and the structure of the material composing a small double NEA. Figure 2 – LICIACube and its payload After the Dimorphos fly-by, LICIACube will download the obtained images directly to Earth: the LICIACube Ground Segment has a complex architecture based on the Argotec Mission Control Centre, antennas of the NASA Deep Space Network and data archiving and processing, managed at the ASI Space Science Data Center. Acknowledgements: The LICIACube team acknowledges financial support from Agenzia Spaziale Italiana (ASI, contract No. 2019-31-HH.0 CUP F84I190012600). References: [1] Rivkin A.S. et al., (2021) PSJ, in press. [2] Cheng A. F., et al. (2018) PSS, 157, 104. [3] Dotto E., et al. (2021) PSS 199, 105185.

Introduction The ESA Rosetta mission orbited the 67P/Churyumov-Gerasimenko comet (hereafter 67P) for two years and its results are providing important clues to understand activity processes on comets. The goal of the ISSI International Team “Characterization of 67P cometary activity” is two-fold: Retrieval of the activity of different regions of 67P’s surface during different time periods. Identification of the main drivers and the effects of cometary activity, via revealing the link between cometary activity and illumination/local time, dust morphology and composition, and surface geomorphology. Goal #1 has been reached by tracing the motion of dust particles detected in the coma back to the nucleus surface. Goal #2 accomplishment is in progress by means of data fusion of different instruments onboard the Rosetta spacecraft. Traceback The Grain Impact Analyser and Dust Accumulator (GIADA) [1] measured speed and momentum of fluffy and compact dust particles. We assumed radial motion, constant dust acceleration up to a 11 km altitude and constant speed above that height, to retrieve the source region of each dust particle detected in the coma [2]. We obtained that fluffy and compact dust distributions correlate on the surface, but not in the coma due to the different speeds of the two dust categories. Dust ejection is also correlated with solar illumination. Fluffy particles are more abundant in rough terrains [3], according to models which predict that they are embedded within pebbles [4]. Traceback is under study also with a different approach, based on retrieving ejection probability maps of detected dust particles [5]. Data Fusion GIADA vs VIRTIS. We related dust ejection rates of different surface regions, as retrieved by GIADA, and spectral indicators of water ice exposure measured by the Visible InfraRed Thermal Imaging Spectrometer (VIRTIS) of Rosetta, such as the shortward shift of the 3.2 mm absorption band center and infrared spectral slope flattening [2]. The observed correlation between these parameters (Figure 1) indicates that ejection of dust comes from water ice-rich regions. Figure 1. Observed correlation between number of fluffy particles ejected from each 67P surface region and observed infrared slope flattening. Each symbol identifies a different geomorphological region of 67P. GIADA vs MIDAS. The Micro-Imaging Dust Analysis System (MIDAS) detected and measured physical properties of micron-sized particles. In principle, it provides complementary information with respect to GIADA, which detected mm-sized particles. We retrieved the number of parent particles hitting the MIDAS targets by applying two different methods [7,8]. Independently of the used approach, we obtained that the dust flux ratio between the two instruments is temporally constant. This suggests that the small particles detected by MIDAS are fragments of larger particles, as those detected by GIADA. The combination of MIDAS data and our traceback algorithm revealed that the physical properties (size, density, flatness) of compact dust are homogeneous across 67P’s surface (Figure 2). Indicators of dust pristinity were defined [8] and suggested that pristinity is correlated with size (being small particles more pristine) but not with the ejecting region evolution degree. Figure 2. Flatness distribution of dust particles detected on different MIDAS target (each target corresponds to a defined exposition period). Distributions are very similar. GIADA vs ROSINA. ROSINA-COPS (Rosetta Orbiter Spectrometer for Ion and Neutral Analysis - COmetary Pressure Sensor) detected icy particles as pressure peaks [9]. The GIADA-ROSINA data fusion allows us to associate icy and dust particles and to retrieve the icy particle source regions. Currently, a moderate correlation between icy and dust fluffy dust particles was found. The work is in progress. Conclusions and future perspectives . We found that fluffy dust particles are more abundant on rough terrains, in agreement with their lower evolution degree and to comet formation models. Physical properties of compact dust are similar across the comet surface. The relation between dust and icy particles is under study. Future activities include: Analysis of the COSIMA mass spectrometer data [10], which observed dust composition variations. COSIMA-GIADA data fusion will allow understanding if they are related to different surface terrains. Analysis of OSIRIS images, which show bright patches on the comet surface, corresponding to frost enrichments and having different composition and morphology [11]. OSIRIS images combined with GIADA and ROSINA data will help in characterizing these peculiar regions. Laboratory activity aimed at simulating and interpreting the different photometric behavior of rough and smooth terrains [12] at the dust scale References [1] Della Corte, V. et al. (2014), Journal of Astronomical Instrumentation, 3, 1, 1350011-110; [2] Longobardo, A. et al. (2019), MNRAS, 483, 2, 2165-2176; [3] Longobardo, A. et al. (2020), MNRAS, 496, 1, 125-137; [4] Fulle, M. and Blum, J. (2017), MNRAS, 492, 2, S39-S44; [5] Ivanovski, S.L. et al. (2017), EPSC, 708; [6] Bentley, M.S. et al. (2016), Nature, 537, 7618, 73-75; [7] Longobardo, A. et al. (2020), EPSC, 1044; [8] Kim, M. et al. (2022), EGU abstract; [9] Pestoni, B. et al. (2022), EPSC, this session; [10] Hilchenback, M. et al. (2019), EPSC, 900; [11] Dehapriya, J.D.P. et al. (2018), EPSC, 1166; [12] Longobardo, A. et al. (2017), MNRAS, 469, 2, S346-S356. Acknowledgements This research was supported by the Italian Space Agency (ASI) within the ASI-INAF agreement I/032/05/0 and by the International Space Science Institute (ISSI) through the ISSI International Team “Characterization of cometary activity of 67P/Churyumov-Gerasimenko comet”. M.K. and T.M. acknowledge funding by ESA project "Primitiveness of cometary dust collected by MIDAS on-board Rosetta" (Contract No. 4000129476).

Context. At present, near-Earth objects (NEOs) are being discovered at an ever-increasing rate. However, their physical characterisation is still significantly lagging behind. In particular, the taxonomic classification of newly discovered NEOs is of great importance with regard to improving our understanding of the population of NEOs. Aims. In this context, our goal is to probe potential links between orbital properties of NEOs and their composition. We investigate whether we can make a reasonable guess about the taxonomic class of an NEO upon its discovery with a decent orbital accuracy. Methods. We used a G-mode multivariate statistical clustering method to find homogeneous clusters in a dataset composed of orbital elements of NEOs. We adopted two approaches, using two sets of variables as inputs to the G-mode method. In each approach, we analysed the available taxonomic distribution of resulting clusters to find potential correlations with several unique parameters that distinctively characterise NEOs. We then applied a dynamical model on the same clusters to trace their escape regions. Results. Approach 1 (A1) led us to obtain NEO clusters that can be linked to a primitive composition. This result was further strengthened by the dynamical model, which mapped outer-belt sources as escape regions for these clusters. We remark on the finding of a cluster akin to S-type NEOs in highly eccentric orbits during the same approach (A1). Two clusters, one with small NEOs in terrestriallike orbits and one with relatively high inclinations, were found to be common to both approaches. Approach 2 (A2) revealed three clusters that are only separable by their arguments of perihelion. Taken altogether, they make up the majority of known Atira asteroids. Conclusions. For an NEO whose orbit is relatively well determined, we propose a model to determine whether the taxonomy of an NEO is siliceous or primitive if the orbital elements of the NEO fall within the presented combinations of inclination, eccentricity, and semi-major axis ranges.

Introduction The study of near-Earth objects (NEOs) is crucial to better understand the origin, formation and the evolution of the solar system. In particular, compositional, morphological and orbital characterisation of NEOs sheds light on the delivery of water and organics [1,2,3] to the prebiotic Earth, while ironically, some NEOs could be potential hazards for life on Earth [4], as it has been witnessed in the past during impacts. Furthermore, these objects are also of interest for the future of humankind, for they could be useful as vital resources during interplanetary travel. Given this context, we apply the G-mode multivariate statistical clustering method [5,6,7] on the orbital parameters of the currently available NEOs population, to probe potential associations with their spectral classification [8,9,10]. Data and methods We apply the G-Mode multivariate statistical clustering analysis to selected orbital elements of NEOs to determine any dynamical clustering of objects. Once the clusters of objects are found, we proceed to investigate whether they have any correlations with spectral classes. The G-mode method leads to an automatic statistical clustering of a sample containing N objects (NEOs in this case), described by M variables (orbital elements) with the only control imposed by the user being the confidence level q1, expressed in terms of σ. Our sample consists of 10669 NEOs belonging to the dynamical groups Atiras, Atens, Apollos and Amors, available from the Minor Planet Center, filtered based on their orbital uncertainty (excluding those with an uncertainty parameter > 4). Our input parameters to the G-mode method are twofold. First, we use three variables: inclination (i), eccentricity (e) and semi-major axis (a) of the orbit as these are the main three parameters that define an orbit around the Sun. Secondly, we include three pseudo-parameters: mean orbital intersection distance with respect to the Earth (eMOID), perihelion distance (q) and aphelion distance (Q) of the orbit, in addition to the aforementioned three parameters, thus using six variables. Preliminary results Using i, e and a of the NEOs in our sample as inputs for G-mode, we obtain three clusters of NEOs at q1=1.9σ (with an accurate classification probability of 94.26%). The mean parameter values of each cluster with the median absolute deviation are given in Table 1. We have also reported some other parameters of interest, which include, Tisserand parameter with respect to Jupiter (TJ) and the absolute magnitude H. At this criterion, the vast majority of objects are clustered in the cluster #1. The cluster #2 with only 20 objects, appears interesting, as it is constrained by low-inclined, quasi-circular Earth-like orbits. The objects of the final cluster #3 are constrained by their relatively larger inclinations. We next used six variables: i, e, a, eMOID, q and Q as inputs for G-mode, while still holding q1 fixed at 1.9σ, in which case six clusters are found as reported in Table 2. Among the reported clusters, clusters #3,4 and 6 are of particular interest, for they could be associated with Jupiter-family cometary nuclei (2 < TJ < 3) as per their Tisserand parameter with respect to Jupiter. As such, the objects in these three clusters could potentially be extinct cometary nuclei. Interestingly, these clusters also have relatively higher eccentricities. We have checked available taxonomic classifications of NEOs [11,12,13] in the literature to get an insight into the composition of the objects found in our G-Mode clusters. Although taxonomic classifications are not available for the majority of members in the clusters, we find that (i) cluster #3 contains 4 C-type objects, (ii) cluster #4 contains 1 C-type, 2 D-type, 1 L-type, 5 S-type and 1 X-type objects, (iii) cluster #5 contains 1 B-type, 1 C-type, 1 T-type and 1 X-type objects. Apart from the S-type objects, the others usually have dark and red spectra indicative of primitive origin, which does not reject a cometary composition. We will augment this on-going study with more data and final results will be presented and discussed. Acknowledgements We acknowledge the financial support from Agenzia Spaziale Italiana (ASI, contract No. 2017-37-H.0 CUP F82F17000630005). We also acknowledge funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 870403. References [1] Marty, B., Guillaume, A. et al. 2016, Earth and Planetary Science Letters, Volume 441, Pages 91-102 [2] Altwegg, K, Balsiger, H, Bar-Nun, A. et al. 2015, Science, Vol. 347, Issue 6220, 1261952 [3] Ehrenfreund, P. & Sephton 2006, Faraday Discuss., The Royal Society of Chemistry, 133, 277-288 [4]Perna, D., Barucci M. A., Fulchignoni M. 2013, Astronomy and Astrophysics Review, Vol. 21,65 [5] Barucci, M.A., Capria, M.T., Coradini, A. et al. 1987, Icarus 72, 304 [6] Gavrishin, A. I., et al. 1992, Earth, Moon and Planets, 59, 141-152 [7] Barucci, M.A., Belskaya, I., Fulchignoni, M. et al. 2005, AJ 130, 1291 [8] Bus, S. J., & Binzel, R.P. 2002, Icarus 158, 146 [9] DeMeo, F. E., Binzel, R. P., Slivan, S. M. & Bus, S. J. 2009, Icarus, 202, 160-180 [10] DeMeo, F. E., Alexander, C. M. O., Walsh, K. J.et al. 2015, Asteroids IV, 13-41 [11] Perna, D., Barucci, M.A. et al. 2018, Planetary and Space Science, 157, 82-95 [12]Devogèle, M., Moskovitz, N. et al. 2019, The Astronomical Journal, American Astronomical Society, 158, 196 [13] Ieva, S., Dotto, E. et al. 2020, A&A, 644, A23

1. Introduction The JAXA Hayabusa2 mission probed the surface of the C-type asteroid (162173) Ryugu both with two touchdown operations to collect samples and return them to Earth, and with remote sensing instruments to characterize it at global scale. Among the payload of the spacecraft, the Near InfraRed Spectrometer (NIRS3) [1] is a point-spectrometer which acquired spectra in the 1.8-3.2 µm range of the asteroid surface to analyse its composition and detect possible heterogeneities. The surface of Ryugu has been shown to be uniformly dark (reflectance factor of 0.017 at 2.0 µm), slightly red-sloped and hydrated due to the presence of a weak, narrow absorption band at 2.72 µm attributed to Mg-phyllosilicates [2]. However, recent studies [3,4] using independent methods of analyses identified minor heterogeneities in the composition on Ryugu. 2. Data and methods Here we continue and expand such studies by selecting NIRS3 datasets that complement the investigated regions of the surface of Ryugu and/or improve the used spatial resolution. The dates corresponding to the datasets retained are the following (sorted by chronological order): July 19th 2018, October 30th 2018, February 28th 2019, July 25th 2019, July 26th 2019, July 27th 2019, October 8th 2019 and October 24th 2019. The coverage of each dataset on Ryugu is displayed in Figure 1. The data used for the analyses have been thermally corrected [2] and photometrically corrected [5]. The selected datasets are analysed using the G-mode multivariate statistical approach, using the same technique as in [3]. From a sample of N objects, each expressed by M variables, the code classifies each object in an homogeneous group with no other intervention from the user than the choice of the confidence level (labeled q and expressed in term of σ). The errors on each variable are taken into account in the classification. Further details on the method are available in [3,6]. 3. Preliminary results Preliminary results are shown from the analysis of the October 24th 2019 dataset only, which has the highest spatial resolution among the datasets we selected (7.66-9.67 m/footprint) and which covers the majority (~10°-~80°N) of the Northern hemisphere of Ryugu. Applying the G-mode with a confidence level of 2σ, and only on twenty-four selected wavelengths representative of the asteroid spectral properties, as in [3], we obtain four spectral groups. The mean spectra of each cluster are shown in Figure 2. The distribution of the four groups at the surface of Ryugu is presented in Figure 3. Group #1 contains almost 85% of the spectra, thus corresponding to the average spectral properties of Ryugu. Groups #2 to #4 can be attributed to the compositional heterogeneities. The mean spectra (Figure 2) are mainly separated according to their spectral slope between 2.05 and 2.61 µm. Groups #2 and #4 are the reddest (highest spectral slope), while group #3 is bluer (lower slope) than group #1. We also noted a slight variation for the 2.72 µm absorption band by computing its depth, groups #2 and #4 having the strongest band and group #3 the weakest. The distribution of the four groups on Ryugu (Figure 3) highlights interesting trends. Groups #2 and #4 seem to be concentrated around large craters (e.g. Cendrillon) and large depressions, such as the one located between 230° and 300° in longitude. On the contrary, group #3 appears inside this depression and in the region gathering large boulders between 200° and 230° in longitude. 4. Conclusion and perspectives We continue and expand previous clustering analyses of NIRS3 data by applying the G-mode algorithm to new datasets, which improve the spatial resolution and/or surface coverage of Ryugu. The preliminary results obtained for the Northern hemisphere of Ryugu are in overall good agreement with the previous findings for the equatorial region [3], confirming the presence of small heterogeneities on the surface. Moreover, they suggest that the material surrounding craters and depressions could present a redder spectral behaviour and a deeper band at 2.7 µm. The G-mode will be applied to all of the selected datasets (Figure 1). Selected regions of interest will also be investigated, notably the second Hayabusa2 touch-down region on which was dropped the Small Carry-on Impactor (SCI) to collect fresh material under the weathered surface [7], by analysing and comparing spectra of the area before and after the impact. Acknowledgements We thank the Haybusa2 JAXA team for their efforts in making the mission successful. Hayabusa2 was developed and built under the leadership of JAXA, with contributions from the DLR and the CNES, and in collaboration with NASA, Nagoya University, University of Tokyo, National Astronomical Observatory of Japan, Aizu University, Kobe University, and other universities, institutes, and companies in Japan. We would also wish to thank all the engineers who contributed to the success of the Hayabusa2 mission, especially T. Masuda, S. Yasuda, K. Matsushima, and T. Ohshima. We acknowledge financial support from ASI contract No. 2018-27-HH.0 “Partecipazione alla fase E della Missione Hayabusa2”. We also acknowledge funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 870403. ED and JDPD thanks the financial support of the Agenzia Spaziale Italiana (ASI, contract No. 2017-37-H.0 CUP F82F17000630005). MA Barucci and M Fulchignoni acknowledge financial support by CNES. References [1] Iwata, T, et al.: NIRS3: The Near Infrared Spectrometer on Hayabusa2, Space Sci. Rev., 208, 317-337, 2017.[2] Kitazato, K, et al.: The surface composition of asteroid 162173 Ryugu from Hayabusa2 near-infrared spectroscopy, Science, 364, 272-275, 2019.[3] Barucci, M. A., et al.: Multivariable statistical analysis of spectrophotometry and spectra of (162173) Ryugu as observed by JAXA Hayabusa2 mission, A&A, 629, 2019.[4] Matsuoka, M, et al.: Clustering analysis of NIRS3 infrared spectral data of Ryugu, 51st LPSC, LPI Contribution No. 2326, 2020.[5] Matsuoka, M, et al. (in preparation)[6] Gavrishin, A. I., et al.: Multivariate classification methods in planetary sciences, Earth, Moon and Planets, 59, 141-152, 1992.[7] Arakawa, M, et al.: An artificial impact on the asteroid (162173) Ryugu formed a crater in the gravity-dominated regime, Science, 368, 67-71, 2020.

We searched for an optimized protocol for mapping observations from a point spectrometer onto a shape model composed of triangular facets, in the context of NASA's asteroid sample return mission, OSIRIS‐REx (Origins, Spectral Interpretation, Resource Identification, and Security‐Regolith Explorer). Our study was conducted before the spacecraft arrived at the mission target asteroid (101955) Bennu, and we used observational sequence plans of the OSIRIS‐REx Visible and InfraRed Spectrometer (OVIRS). We explored six methods of mapping data to shape model facets, using three spatial resolutions. We attempted to boost map fidelity by increasing the observational coverage of the surface. We find that increasing shape model resolution improves mapping quality. However, once the shape model's mean facet edge length is smaller than two‐fifths of the diameter of the instrument's field of view (FOV), the increase in quality tapers off. The six mapping methods can be broken into two categories: facets that (1) select or (2) combine (average) data from observations. The quality differences between similar averaging methods (clipped average, weighted average, etc.) are insignificant. Selecting the nearest observation to a facet best preserves an enclosed outcrop's shape and signal, but averaging spots are more conservative against errors in photometric modeling. A completely enclosed outcrop border expands into the surrounding region by 0.8–1.5 radii of the instrument's FOV. Regions smaller than the instrument's FOV are present in resulting maps; however, their signal strength is reduced as a function of their size relative to the instrument FOV.

Introduction OVIRS [1, 2] acquired visible to near-infrared spectra of asteroid Bennu’s surface showing an asymmetric absorption band centered at 2.74 ± 0.01 μm [3], attributed to the presence of hydrated phyllosilicates. This feature is widespread across Bennu’s surface. Such an absorption band has been detected in some carbonaceous chondrite meteorites [4, 5].In this study, we report the results from two distinct methods to estimate the hydration of Bennu’s surface. We calculated the normalized optical path length (NOPL) as well as the effective single particle absorption thickness (ESPAT) [6, 7, 8] on Bennu’s hydration band and on the selected meteorite spectra. For both methods, we compare meteorite results with their H2O/OH– H content, to estimate a H2O/OH– H content of Bennu’s average surface. Carbonaceous chondrite meteorite H2O/OH– H contents are derived from laboratory studies [9, 10]. Data Analysis Bennu spectra. Analysed spectra were acquired by OVIRS during Equatorial Station 3 (EQ3) of the Detailed Survey mission phase, on May 9, 2019, at 12:30 pm local solar time [11]. The reflectance spectra have been calibrated and photometrically corrected to an incidence angle of 0°, emission angle of 30°, and phase angle of 30°, using a McEwen photometrical model [12].Meteorite spectra. We used three sets of meteorite absolute reflectance spectra, from [4,5], [8], and [13]. For each set, powdered meteorite sample spectra were measured under vacuum (asteroid-like conditions).We selected over 40 meteorites for which bulk H values have been independently measured [9, 10]. In the case of Orgueil, Bells, and Tagish Lake, several samples were analysed and several H contents were ultimately derived [9, 14], all of which were used. Methods Normalized Optical Path Length (NOPL). The NOPL parameter was calculated as described in [6, 7, 8] on each meteorite spectrum, each individual Bennu reflectance spectrum, and the global average spectrum of Bennu. A linear continuum was fitted from 2.67 to 3.3 μm. The wavelength, at which the NOPL parameter is calculated, is the mean band minimum position for the EQ3 data set at 2.73 μm. Methods used to locate the band minimum are described in [3].Effective Single Particle Absorption Thickness (ESPAT). The ESPAT parameter was calculated following the method of [6, 7, 8]. Absolute reflectance spectra of meteorites and Bennu’s surface were first converted into single-scattering albedo spectra [6, 7, 8]. A linear continuum was then fitted from 2.67 to 3.3 μm and the ESPAT parameter is calculated at 2.73 μm as well. Our analyses do not include the organic absorption bands, present longwards of ~3.3 μm [11, 15]. Thus, we compare NOPL and ESPAT results with the hydrogen content of H2O/OH– groups in hydrated phyllosilicates only, measured for the selected meteorites [9, 10]. Results Figure 1 shows the NOPL parameter variations across Bennu’s surface using EQ3 spectra.Figure 1: Map of NOPL values computed at 2.73 μm for each EQ3 spectrum of Bennu.We find a linear correlation (Figure 2) between the NOPL parameter calculated at 2.73 μm on meteorite spectra and the meteorite H2O/OH– H content.Using this linear correlation, for the NOPL calculated on Bennu’s EQ3 average spectrum, we estimate a H2O/OH– H content for Bennu’s average surface of 0.54 ± 0.11 wt.%. Figure 2: Linear correlation between NOPL calculated at 2.73 μm and H2O/OH– H content of the seven selected meteorites (in colored points), and for average Bennu (blue circle).As with the NOPL parameter, we also find a linear correlation between the ESPAT parameter calculated at 2.73 μm on meteorite spectra and the meteorite H2O/OH– H content. We therefore estimate a H2O/OH– H content for Bennu’s average surface of 0.49 ± 0.13 wt.%, using Bennu’s EQ3 mean ESPAT value and the latter correlation. Discussion and ConclusionThe H2O/OH– H content for Bennu’s average surface obtained using NOPL parameters is consistent with the range obtained with the ESPAT parameter. Both methods are based on estimating global H content (in H2O/OH– groups of hydrated phyllosilicates) by analogy with meteorite data. The values of H2O/OH– H content of Bennu’s average surface we obtained are 0.54 ± 0.11 and 0.49 ± 0.13 wt.% using the NOPL parameter and the ESPAT parameter, respectively. From our results (Figure 2), Bennu’s average surface is most similar to heated CMs and Tagish Lake. Both estimated H2O/OH– H content ranges of Bennu’s average surface are more consistent with those of CM meteorites (0.46–1.36 wt%), Tagish Lake (0.50–0.69 wt.%), CR meteorites (0.30–1.20 wt.%), and CO meteorites (0.49–0.52 wt.%) [3, 9]. The gaussian modeling of the hydration band will complete those results. AcknowledgementsThis material is based on work supported by NASA under Contract NNM10AA11C issued through the New Frontiers Program. AP, MAB, FM, SF, PH and JDPD acknowledge funding support by CNES. INAF participation was supported by Italian Space Agency grant agreement n. 2017-37-H.0. We are grateful to the entire OSIRIS-REx Team for making the encounter with Bennu possible. References[1] Lauretta D. S. et al. (2017) Space Sci. Rev. 212, 925-984. [2] Reuter D. C. et al. (2018) Space Sci. Rev. 214, 54. [3] Hamilton V. E. et al. (2019) Nat. Astron. 3, 332. [4] Takir D. et al. (2013) Meteorit. Planet. Sci. 48, 1618–1637. [5] Takir D. et al. (2019) Icarus 333, 243–251. [6] Milliken R. E. et Mustard J. F. (2005) JGR, 110, E12001. [7] Milliken R. E. et al. (2007) JGR, 112, E08S07. [8] Garenne A. et al. (2016) Icarus, 264, 172-183. [9] Alexander C.M.O’D. et al. (2012) Science, 337, 721-723. [10] Alexander C.M.O’D. et al. (2013) Geochim. Cosmochim. Acta, 123, 244-260. [11] Simon et al. (in revision) Science. [12] Zou X.-D. et al., this meeting. [13] Potin S. et al. (2020) Icarus, 348, 113826. [14] Gilmour C. M. et al. (2019) Meteorit. Planet. Sci. 54, 1951–1972. [15] Kaplan et al. (2020) LPSC LI, 1050.

1. IntroductionOrigins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) is a NASA New Frontiers mission to return a sample of near-Earth asteroid (101955) Bennu. The OSIRIS-REx spacecraft is equipped with a suite of scientific instruments [1], including the OSIRIS-REx Camera Suite (OCAMS) and the OSIRIS-REx Visible and InfraRed Spectrometer (OVIRS), among others. OCAMS’s high-spatial-resolution images of Bennu’s surface facilitate the identification of regions of interest, characterization of surface morphology, and mapping of relative surface albedo [2]. OVIRS is a point spectrometer that measures surface composition [3]. The OVIRS footprint during the Reconnaissance phase of the mission [1] had an observational field of view with diameters between 5 to 9 m.We search for and distinguish organics and carbonates on the surface of Bennu by studying the shape of the 3.4-micron feature, as observed by the OVIRS spectrometer during reconnaissance of candidate sampling sites [4]. Aliphatic organics have vibrational stretching bands at 3.4 microns, and the CO32- anion in carbonate minerals has an overtone of a fundamental asymmetric vibrational stretch, also at 3.4 microns. Organics on asteroids are hypothesized to be related to the organic materials delivered to Earth during the early bombardment phase of Earth’s development [5]. Carbonates record evidence of aqueous processes on Bennu [6], and together the organics and carbonates provide evidence for Bennu’s alteration history.We present the results of a search for Bennu spectral matches to specific laboratory carbonate spectra and meteoritic aliphatic organic spectra, in the wavelength range from 3.2 to 3.6 microns. The carbonate spectra were obtained from the RELAB facility at Brown University [7], and the insoluble organic material (IOM) spectra were obtained from [8]. For the carbonates, we test ~10 representative spectra each of calcite, dolomite, and magnesite. For the organic IOM, we test spectra such as Tagish Lake, Cold Bokkeveld, Mighei, Murchison, and Orgueil.2 Data collection and preparation2.1 Spectrum preparation To prepare laboratory and OVIRS spectra for band-match testing, we first divide every spectrum by a continuum, defined as a second order polynomial. The parabola is constrained using reflectance values at the wavelengths 2.95, 3.24, 3.6 microns. We then “stretch” the band by normalizing each spectrum such that the band minimum occurs at 0.0 and the maximum occurs at 1.0. Thus, we are only comparing the band shapes, as all other quantitative information has been removed by the continuum normalization and the band stretching. 2.2 K-S parameter testWe apply a Kolmogorov-Smirnov (K-S) parameter test to find which laboratory spectra best fit the OVIRS spectra. We compare each laboratory spectrum to the entire OVIRS data set. The K-S parameter is an evaluation of the maximum discrepancy between two cumulative distribution functions (Figure 1). That is, we calculate the cumulative sum of the laboratory and OVIRS spectra and find the points of maximum discrepancy. The smaller the discrepancy, the better the fit. 3 Results Figure 1 shows an example match between an OVIRS spectrum from Bennu and a laboratory spectrum of calcite. Because the K-S parameter has a very low value (We will present maps of where carbonate and organic material is detected on Bennu and discuss our search for associations or correlations with boulders or other surface properties.AcknowledgementsThis material is based upon work supported by NASA under Contract NNM10AA11C issued through the New Frontiers Program. INAF participation was supported by Italian Space Agency grant agreement n. 2017-37-H.0. We are grateful to the entire OSIRIS-REx Team for making the encounter with Bennu possible.References[1] Lauretta, D.S. et al. (2017). OSIRIS-REx: Sample Return from Asteroid (101955) Bennu. Space Sci. Rev. 212, 925–984.[2] Rizk, B. et al. OCAMS: the OSIRIS-REx camera suite. Space Sci Rev (2018) 214:26 https://doi.org/10.1007/s11214-017-0460-7[3] Reuter, D.C. et al. (2018). The OSIRIS-REx Visible and InfraRed Spectrometer (OVIRS): Spectral Maps of the Asteroid Bennu. Space Sci. Rev. 214, 54.[4] V. E. Hamilton. VNIR-TIR spectroscopy of (101955) Bennu. This conference.[5] Anders, Edward. Pre-biotic organic matter from comets and asteroids. Nature 342.6247 (1989): 255-257.[6] Kaplan, H. H., et al. Evidence of Organics and Carbonates on (101955) Bennu. LPI 2326 (2020): 1050.[7] Pieters, C.M., et al. Reflectance Experiment Laboratory (RELAB) Description and User's Manual. NASA Technical Reports Server. (2004). Document ID, 20040129713[8] Kaplan, H.H., et al. Reflectance spectroscopy of insoluble organic matter (IOM) and carbonaceous meteorites. Meteorit Planet Sci, 54 (2019): 1051-1068. doi:10.1111/maps.13264

Introduction: The OSIRIS-REx mission has revealed a dark, boulder-rich, apparently dust-poor surface of the B-type asteroid (101955) Bennu [1], therefore a challenge for bi-directional reflectance (rF) modeling. With an estimated geometric albedo of 4.5% [2], Bennu is darker than many comets, and its reflectance distribution is dominated by single-scattering processes. The general approach to model a dark asteroid’s bi-directional reflectance distribution is to apply the standard Hapke IMSA model and its shadowing function [3]. However, this can imprecisely describe the roughness slopes for rocky surfaces [4]. Assuming that surfaces are fully diffuse can negate a specular forward-scattering contribution from crystalline components in the regolith [7]. To achieve a more complete photometric modeling of Bennu’s scattering curve, we rely on the radiative transfer semi-numerical model of Van Ginneken et al. [8,9]. Observations: MapCam is an optical imager [10] on-board the OSIRIS-REx spacecraft, equipped with four broadband color filters (60-90 nm wide) centered at 473 (b'), 550 (v'), 698 (w') and 847 (x') nm. We analyzed images acquired during the Equatorial Station (EQ), a campaign of the Detailed Survey mission phase [11], over a full rotation of (101955) Bennu at a nadir spatial resolution of ~33 cm/px. EQ comprehended seven phase angle configurations α =[7.5° ,30° ,45° ,90° ,130°] . We analyzed the pixel subtended by the mission’s candidate sample collection sites, for which highly precise, laser altimeter-based digital terrain models (DTMs) were available [12,13]. These four candidate sites were called Sandpiper (latitude=-47°; longitude=322°), Osprey (11°; 88°), Nightingale ( 56°; 43°), and Kingfisher (11°; 56°). The varied latitude and longitudes provided the range of observational conditions required for our analysis. Methodology: The methodology consists of the following steps: a) NAIF SPICE kernels [14] and the DTMs are ingested into a ray-tracing code for rendering shadowed images. This allows us to discount for the effects of macroscopic shadows, leaving only the sub-facet texture to be modeled. These ancillary images provide the incidence, emergence, phase & azimuth for every facet. b) We apply Van Ginneken’s model to every facet. Occlusion and shadowing as well as the retro-reflection among the reliefs are taken into account. The model has two major components: the analytical expression for the specular reflection; and the numerically-integrated diffusive reflection. At total, the model has three free parameters: ρ (single-scattering albedo), σ (RMS roughness slope), and g (specular-to-diffuse ratio), plus the three more related to the scattering phase function (bi-lobe Henyey-Greenstein function: c, b1, and b2) c) Inverse problem: We run the Monte Carlo Markov Chain to sample the multi-parametric space in order to reconstruct a posteriori probability distribution of solutions for every free parameter, i.e., (ρ, σ, g, b1, b2, c), from which the statistics for every solution are estimated. Results: The MCMC technique reveals some interesting aspects of Bennu's surface (Fig. 1): while the RMS roughness slope of 27+1-5 is in line with what has been obtained for other asteroids using Hapke shadowing function, we are puzzled by the indication of a non-zero specular reflection ratio from the surface (2.6+1−0.8 %). The specular reflection hints at a possible mono-crystalline component. As for the diffuse rough component, the analysis of the photometric correction of OCAMS images taken at varied phase angles (α) indicates a more complex scenario. Up to α = 90°, the photometric correction is vastly improved by mixing two different solutions for roughness (one with low RMS σ and another with global RMS σ), a bi-modality already perceived from the MCMC a posteriori distributions. We have shown that most of Bennu's brightness variation can be explained by tuning the roughness slope statistical distribution. Finally, we report a back-scatter phase function for the phase angle range between 7.5°, and 130°, without any expressive spectral trend in the visible range. The MCMC inversion hints at a possible second forward-scatter lobe of at least ~0.2 width. This leads to two possible solutions for the asymmetric factor (ξ (1) = −0.360 ± 0.030 and ξ(2) = −0.444 ± 0.020). We also report a dark global approximate single-scattering albedo at 550 nm from the collective analysis of all site candidates of 4.64+0.08-0.09 % . The single-scattering MapCam four-band colors show a similar spectral trend to the global average OVIRS EQ3 spectrum. The four sites together provide a general description of Bennu's colors. Fig. 1. Parametric solutions after the MCMC technique for all sample sites together, and the scattering phase function (bottom row) for each MapCam filters. References: [1] Lauretta, D. et al. Met.. & Plan. Scie., 50, Issue 4, 834-849, 2015. [2] DellaGiustina, D.N. et al., Nat. Astron. 3, 241-351, 2019. [3] Hapke, B. Icarus 59, 41-59,1984. [4] Shkuratov et al., JQSRT 113, 18, 2431-2456, 2012. [5] Davidsson, B. et al. Icarus 201, 335–357, 2009. [6] Labarre, S. et al. Icarus 290, 63-80, 2017. [7] Bowell, E., et al. Asteroid II, Univ. of Ariz. Press, 1989. [8] Van Ginneken, B. et al. AO 37, 130-139, 1998. [9] Goguen, J. et al. Icarus 208, 548–557, 2010. [10] Rizk, B. et al.. Space Sci. Rev. 214, 26, 2018. [11] DellaGiustina, D.N. et al., ESS 5, 929, 2018. [12] Daly, M. G. et al., SSR 212, 899, 2017. [13] Barnouin, O. S. et al., PLANSS 180, 104764, 2020. [14] Acton, C. H.. PLANSS 44.1 (1996): 65-70. [15] Hapke, B. Cambridge Univ. Press, 2ed., 2012.

The complex history of Bennu's surface The near-Earth asteroid (101955) Bennu is a carbon-rich body with a rubble pile structure, formed from debris ejected by an impact on a larger parent asteroid. The Origins, Spectral Interpretation, Resource Identification, Security, Regolith Explorer (OSIRIS-REx) spacecraft is designed to collect a sample of Bennu's surface and return it to Earth. After arriving at Bennu, OSIRIS-REx performed a detailed survey of the asteroid and reconnaissance of potential sites for sample collection. Three papers present results from those mission phases. DellaGiustina et al. mapped the optical color and albedo of Bennu's surface and established how they relate to boulders and impact craters, finding complex evolution caused by space weathering processes. Simon et al. analyzed near-infrared spectra, finding evidence for organic and carbonate materials that are widely distributed across the surface but are most concentrated on individual boulders. Kaplan et al. examined more detailed data collected on the primary sample site, called Nightingale. They identified bright veins with a distinct infrared spectrum in some boulders, which they interpreted as being carbonates formed by aqueous alteration on the parent asteroid. Together, these results constrain Bennu's evolution and provide context for the sample collected in October 2020. Science , this issue p. eabc3660 , p. eabc3522 , p. eabc3557

Introduction In early December 2018, NASA’S Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) [1] spacecraft arrived at the Near-Earth asteroid (101955) Bennu, [2,3] with the objective of globally characterizing the asteroid and returning a sample to Earth in 2023. Given this context, we probe the spectral nature of craters on Bennu, using spectral data acquired by the OSIRIS-REx Visible and InfraRed Spectrometer (OVIRS) [4]. 2. Data and methods We selected 46 craters from the crater catalogue of Bennu [5], depending on the availability of spectral data. The spectral data are calibrated as detailed in [6,7] and follow the photometric correction of [8], which results in reflectance factor (REFF) spectra corrected to the geometry of i=30°, e=0°, α =30°. We then derive an average spectrum of a crater from all the spectra whose footprints fall in its interior. From this average spectrum, we compute the following four spectral parameters to characterize the spectral properties of each crater. 1) Depth of the absorption band at 2.7 μm 2) Position of the 2.7-μm band minimum 3) Normalized spectral slope from 0.55 to 2.0 μm 4) Photometrically corrected REFF at 0.55 μm For comparison with the crater spectra, we derive an average global spectrum from the Equatorial Station 3 (EQ3) data set [1] (acquired at phase angle α ∼ 8°), which has an almost complete spatial coverage of Bennu. 3. Results and Discussion Detection of a shortward shift of the 2.7-μm absorption band minimum The minimum position of the 2.7-μm absorption band in some craters shifts towards wavelengths shortward of 2.74 μm, the measured band position in Bennu’s global average spectrum [9]. This absorption band is associated with hydrated phyllosilicates, resulting from aqueous alteration of Bennu in the past. The minimum position of this band is related to Mg/Fe ratio of the phyllosilicates [10,11], which depends on the extent of the alteration. This minimum position is therefore an indication of the alteration the material experienced. We measure this shift to be up to 25 nm. The presence of such a shift of this band can be translated into the presence of fresher and/or less altered material inside the craters, in the context of space weathering for C-complex asteroids [12, 13]. Anti-correlation between spectral slopes and REFF suggests the presence of fine grains The relation between spectral slopes and REFF varies across craters. Particularly, it varies even among different scans of the same crater. To better understand this variation, Pearson’s correlation coefficient (r) was estimated. We considered a series of spectra acquired as the spectrometer scans from the rim of a crater, across its center, and towards the rim again. The REFF and spectral slope of each spectrum of this scan were then compared using r. We find an anti-correlation between REFF and spectral slopes (increasing spectral slopes versus decreasing REFF) within some craters (Fig. 1). Laboratory experiments conducted on carbonaceous chondrite meteorites have shown that redder slopes are associated with finer grains [14]. We then checked image data of the corresponding footprints and found the presence of unresolved material at cm to sub-cm scales[LDS-(1] . As such, we suggest that the observed anti-correlation is an indication of the presence of fine grains inside craters. Fig. 1. Top (a): Crater ID 3 (Osprey) without and with footprints of an OVIRS scan. The rightmost graph shows the spectral slopes and REFF variation across the crater as the spectrometer scans through the crater, as seen on the rendering shown to its left. The x-axis represents the spectrum number of the scan and error bars are also given for the uncertainty of each parameter of a spectrum. r is evaluated at -0.84 for these two parameters, indicating a strong anti-correlation. Values of the global average spectrum are also given for comparison. Bottom (b): Similarly, a view of the crater ID 1 without and with the rendering of another OVIRS scan, where r is -0.79. . Spectral heterogeneity detected in the largest equatorial crater on Bennu We observe spectral heterogeneity in one of the oldest geological features on Bennu, the large equatorial crater located at -8°, 269° measuring 187 m in diameter [15]. We attribute this heterogeneity to mass movement [16]. We propose that such local spectral heterogeneities could be used as a tracer of mass movement across Bennu. Smaller craters are brighter, with deeper hydration and redder spectral slopes By examining the spectral parameters of all the 46 craters, we independently confirm the results of [13] that smaller (presumably younger) craters are redder and brighter. In addition, the OVIRS data indicate they have deeper 2.7-μm bands (Fig. 2). Comparing global average spectral values of Bennu and crater frequency distributions as a function of the chosen spectral parameters, we find that, given the time, craters will evolve to assume the global average spectral properties of Bennu. Fig. 2 Variations of normalized spectral slope, REFF and 2.7 μm band depth with the crater diameter are given in a, b, and c panels respectively. Variation of REFF with 2.7-μm band depth is plotted in the panel d. The sizes of data points are scaled to corresponding crater sizes and crater IDs are embedded next to respective data points. References [1] Lauretta, D. S. et al. 2017, Space Science Reviews, 212, 925. [2] DeMeo, F. E. et al. 2009, Icarus, 202, 160. [3] Clark, B. E et al. 2011, Icarus, 216, 462. [4] Reuter D. C. et al. 2017, Space Sci. Rev. 214, 54. [5] Bierhaus, E. et al. 2019, in EPSC–DPS2019–1134. [6] Simon, A. A. et al. 2018, Remote Sensing, vol. 10, issue 9, p. 1486 [7] Simon et al. (submitted) [8] Zou et al. (submitted). [9] Hamilton, V. E. et al. 2019, Nature Astronomy, [10] Farmer, V. C. 1974, in The Infrared Spectra of Minerals [11] Beck, P. et al. 2010, Geochimica et Cosmochimica Acta, 74, 4881. [12] Lantz, C. et al. 2017, Icarus, 285, 43. [13] DellaGiustina et al. – this conference [14] Cloutis, E. A. et al. 2018, Icarus, 305, 203. [15] Walsh, K. J. et al. 2019, Nature Geoscience. [16] Jawin et al. (submitted).

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 (similar to 2.4 au outbound to the 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.© ESO 2019, We are grateful to Andrea Longobardo for suggestions and corrections that improved our paper. OSIRIS was built by a consortium of the Max-Planck-Institut fur Sonnensystemforschung, Gottingen, Germany, CISAS - University of Padova, Italy, the Laboratoire d'Astrophysique de Marseille, France, the Instituto de Astrofisica de Andalucia, CSIC, Granada, Spain, the Research and Scientific Support Department of the European Space Agency, Noordwijk, The Netherlands, the Instituto Nacional de Tecnica Aeroespacial, Madrid, Spain, the Universidad Politechnica de Madrid, Spain, the Department of Physics and Astronomy of Uppsala University, Sweden, and the Institut fur Datentechnik und Kommunikationsnetze der Technischen Universitat Braunschweig, Germany. The support of the national funding agencies of Germany (DLR), France (CNES), Italy (ASI), Spain (MEC), Sweden (SNSB), and the ESA Technical Directorate is gratefully acknowledged.

This thesis is based on the spectrophotometric properties of the comet 67P/Churyumov-Gerasimenko, using the OSIRIS instrument of Rosetta space mission. Composed of two scientific cameras to observe the nucleus and the coma of the comet, OSIRIS images are acquired with multiple filters, that span the near-UV to near-IR wavelength range. They were used to study the spectrophotometric curves of the exposed bright features that appeared on the surface of the cometary nucleus, leading to a comparative study, that was carried out in collaboration with the VIRTIS spectro-imager aboard Rosetta, that demonstrated, that these exposures are related to H2O ice, using its absorption band located at 2 microns. The thesis further details a spectrophotometric study of the Khonsu region in the southern latitudes of the comet, where the seasonal variation of the spectral slope of different types of terrains is explored. Finally, the results of an extended survey of exposed bright features are presented. More than 50 individual features are presented under four morphologies along with an albedo calculation, suggesting that different activity sources are responsible for their appearance on the nucleus.; Cette thèse s'inscrit dans le cadre de la mission spatiale Rosetta et porte sur les propriétés spectrophotométriques de la comète 67P/Churyumov-Gerasimenko à l’aide de l’instrument OSIRIS. Cet instrument est composé de deux caméras pour les observations du noyau et de la coma de la comète. Elles permettent d’acquérir des images avec des filtres qui opèrent dans la gamme du proche UV au proche IR. Dans un premier temps, j'ai analysé les courbes spectrophotométriques des taches claires qui sont apparues sur le noyau de la comète. Une étude comparative de celles-ci grâce aux données du spectro-imageur VIRTIS a ainsi permis de constater que les taches claires sont liées à la glace de H2O. Dans un second temps, j’ai entrepris une étude spectrophotométrique de la région Khonsu, qui a mis en évidence les variations saisonnières de la pente spectrale de différents terrains. Par la suite, j’ai élargi mon analyse des taches à tout le noyau de la comète. J’ai détecté plus de 50 taches claires dues à la présence de glace de H2O et j’ai produit une carte pour repérer leurs emplacements sur le noyau, afin d’étudier plus en détail leur répartition et leur évolution au cours de temps. Ceci m’a permis d’identifier quatre types de taches regroupés en fonction de leur morphologie et de constater qu'elles sont dues à différentes sources d'activité cométaire.

The ROSETTA mission is the cornerstone mission of the European Space Agency devoted to the study of the minor bodies of the Solar System. Its primary objective is to perform an extensive study of the comet 67P/Churyumov-Gerasimenko (hereafter 67P/CG). Launched on the 2nd of March 2004, the spacecraft overflew the asteroids 2837 Steins in 2008 and 21 Lutetia in 2010. Since its encounter with 67P/CG in July 2014, the spacecraft has been escorting the nucleus thus allowing to study it with cameras, spectrometers, dust analysers and radio science experiments. The spacecraft will continue its escort at least until December 2015. We present the results on the photometric properties of the nucleus derived from disk-averaged and disk-resolved images of the OSIRIS instrument acquired in 2014-2015 including the close fly-by data acquired on the 14th of February 2015.