Europlanet Science Congress 2020
Virtual meeting
21 September – 9 October 2020
Europlanet Science Congress 2020
Virtual meeting
21 September – 9 October 2020

Oral presentations and abstracts


Electromagnetic scattering phenomena play a key role in determining the properties of Solar System surfaces based on observations using different techniques and in a variety of wavelengths ranging from the ultraviolet to the radio. This session will promote a general advancement in the exploitation of observational and experimental techniques to characterize radiative transfer in complex particulate media. Abstracts are solicited on progresses in numerical methods to extract relevant information from imagery, photometry, polarimetry and spectroscopy in solid phase, reference laboratory databases, photometric modeling, interpreting features on planetary surfaces, mixing/unmixing methods… Software and web service applications are welcome.

Conveners: Stéphane Erard, Maria Gritsevich, Karri Muinonen, Antti Penttilä, Frédéric Schmidt

Session assets

Session summary

Spectroscopy and Bennu
Pedro Henrique Hasselmann, Sonia Fornasier, Maria Antonietta Barucci, Alice Praet, Beth Ellen Clark, Jian-Yang Li, Dathon Golish, Daniella N. DellaGiustina, Prasanna Deshapriya, Xiao-Duan Zou, Mike G. Daly, Olivier S. Barnouin, Amy A. Simon, and Dante S. Lauretta

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.


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[2] DellaGiustina, D.N. et al., Nat. Astron. 3, 241-351, 2019.

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[15] Hapke, B. Cambridge Univ. Press, 2ed., 2012.

How to cite: Hasselmann, P. H., Fornasier, S., Barucci, M. A., Praet, A., Clark, B. E., Li, J.-Y., Golish, D., N. DellaGiustina, D., Deshapriya, P., Zou, X.-D., G. Daly, M., S. Barnouin, O., A. Simon, A., and S. Lauretta, D.: Modeling first-order scattering processes from OSIRIS-REx color images of the rough surface of asteroid (101955) Bennu, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-122,, 2020.

Alice Praet, Antonella Barucci, Hannah Kaplan, Frédéric Merlin, Beth Clark, Amy Simon, Victoria Hamilton, Joshua Emery, Ellen Howell, Lucy Lim, Xiao-Duan Zou, Dennis Reuter, Salvatore Ferrone, Prasanna Deshapriya, Sonia Fornasier, Pedro Hasselmann, Giovanni Poggiali, John Brucato, Driss Takir, and Dante Lauretta

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/OHH content, to estimate a H2O/OHH content of Bennu’s average surface. Carbonaceous chondrite meteorite H2O/OHH contents are derived from laboratory studies [9, 10].


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.


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/OHgroups in hydrated phyllosilicates only, measured for the selected meteorites [9, 10].


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/OHH 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/OHH 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 Conclusion

The 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.



This 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.



[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.

How to cite: Praet, A., Barucci, A., Kaplan, H., Merlin, F., Clark, B., Simon, A., Hamilton, V., Emery, J., Howell, E., Lim, L., Zou, X.-D., Reuter, D., Ferrone, S., Deshapriya, P., Fornasier, S., Hasselmann, P., Poggiali, G., Brucato, J., Takir, D., and Lauretta, D.: Hydration variations of Bennu’s surface: comparison of different methods. , Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-136,, 2020.

Xiao-Duan Zou, Jian-Yang Li, Beth Clark, Dathon Golish, Salvatore Ferrone, Amy Simon, Dennis Reuter, Deborah Domingue, Hannah Kaplan, Maria Barucci, Sonia Fornasier, Alice Praet, Pedro Hasselmann, Carina Bennett, Edward Cloutis, Eri Tatsumi, Daniella DelllaGiustina, and Dante Lauretta


NASA’s OSIRIS-REx (Origins, Spectral Interpretations, Resource Identification, and Security–Regolith Explorer) asteroid sample return mission (Lauretta et al., 2017) began operating in proximity to near-Earth asteroid (101955) Bennu in December 2018. Here we present an analysis of the global photometry of Bennu from measurements by the OSIRIS-REx Visible and InfraRed Spectrometer (OVIRS; Reuter et al., 2018). This instrument is a point spectrometer with a wedged filter design. OVIRS is used for the spectral characterization of the surface of Bennu, with a field of view of 4 mrad and an effective spectral range from 0.4 to 4.3 μm. Our work focuses on OVIRS data acquired from December 9, 2018, to September 26, 2019.


This study comprises the global observation data from Preliminary Survey and the two sub-phases of Detailed Survey, Baseball Diamond (BBD) and Equatorial Stations (EQ) (campaigns described in Lauretta et al., 2017). We use a total of 299,702 calibrated spots. More details about the data selection and calibration are introduced by Zou et al. (submitted).

3.Photometric analyses

We model the scattering properties of the surface of Bennu using the Lommel-Seeliger, Minnaert, McEwen, and Akimov photometric models. The best-fit model is a McEwen model with an exponential phase function and an exponential polynomial partition function. We use this model to correct the OVIRS spectra of Bennu to a standard reference viewing and illumination geometry at visible to infrared wavelengths for the purposes of global spectral mapping (Figure 1). We derive a bolometric Bond albedo map in which Bennu’s surface values range from 0.021 to 0.027. We find a phase reddening effect of 1.4±0.3 × 10−4 μm−1deg−1 across the wavelength range 0.48 to 2.5 μm, and our model is effective at removing this phase reddening.

We compare our OVIRS results to Golish et al. (2020)’s report on the global photometry of Bennu, based on imaging data from the OSIRIS-REx Camera Suite (OCAMS; Rizk et al., 2018). We also compare the results to ground observation and other minor planets including Ryugu.

Acknowledgements: This material is based upon work supported by NASA under Contract NNM10AA11C issued through the New Frontiers Program. We are grateful to the entire OSIRIS-REx Team for making the encounter with Bennu possible and the exploration highly successful. X.-D. Zou and J.-Y. Li also acknowledge partial support from the Solar System Exploration Research Virtual Institute 2016 (SSERVI16) Cooperative Agreement (Grant NNH16ZDA001N), SSERVI-TREX to the Planetary Science Institute. M. A. Barucci acknowledges funding support from CNES. 


Bennett, C.A., et al. 2020. A high-resolution global basemap of (101955) Bennu. Icarus. doi: 10.1016/j.icarus.2020.113690.

Ernst et al., 2018, The Small Body Mapping Tool (SBMT) for Accessing, Visualizing, and Analyzing Spacecraft Data in Three Dimensions, LPSC 49, abstract no. 1043.

Golish, D.R., et al. 2020. Disk-resolved photometric modeling and properties of asteroid (101955) Bennu. Icarus, doi:10.1016/j.icarus.2020.113724.

Lauretta, D.S., et al. 2017. OSIRIS-REx: sample return from asteroid (101955) Bennu. Space Science Reviews 212(1-2):925-984.

Reuter, D.C., et al. 2018. The OSIRIS-REx Visible and InfraRed Spectrometer (OVIRS): spectral maps of the asteroid Bennu. Space Science Reviews 214(2):54.

Rizk, B., et al. 2018. OCAMS: the OSIRIS-REx Camera Suite. Space Science Reviews 214(1):26.

Zou et al. (submitted). Photometry of asteroid (101955) Bennu with OVIRS on OSIRIS-REx. Icarus.

Figure 1. A global 3D facet-based map of the photometrically corrected (to 30°, 0°, 30°) OVIRS spots at a wavelength of 0.55 μm. The data are overlain on the OCAMS imaging basemap (Bennett et al., 2020), as viewed in the Small Body Mapping Tool (Ernst et al. 2018). Input spectra were obtained during Detailed Survey EQ3.

How to cite: Zou, X.-D., Li, J.-Y., Clark, B., Golish, D., Ferrone, S., Simon, A., Reuter, D., Domingue, D., Kaplan, H., Barucci, M., Fornasier, S., Praet, A., Hasselmann, P., Bennett, C., Cloutis, E., Tatsumi, E., DelllaGiustina, D., and Lauretta, D.: The Global Average Disk-Resolved Photometric Properties of (101955) Bennu, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-146,, 2020.

Sandra Potin, Sylvain Douté, Benoit Kugler, Florence Forbes, Pierre Beck, and Bernard Schmitt

Introduction: Reflectance spectroscopy is commonly used to retrieve chemical and physical properties of the Solar System bodies. However, the reflectance spectrum of a surface depends not only on its composition, but also on several parameters, including the viewing geometry [1]. Unlike laboratory measurements where the composition and texture of the sample and the geometry of measurement are fixed and controlled, observations of planetary bodies integrate spatial heterogeneities and changes of observation geometries due to both the shape and the topography of the surface. Here we compare two spectral photometric models to reproduce laboratory measurements of the Bidirectional Reflectance Distribution Functions (BRDFs) of a sample. We then employ the resulting models to calculate phase curves of the dwarf planet Vesta at different wavelengths and simulate spectral image cubes of its surface acquired with virtual telescopes.

Laboratory measurements: Bidirectional reflectance spectroscopy of a fine powder of howardite is acquired using the spectro-gonio radiometer SHADOWS [2], using the geometrical configurations presented in [1].

Inversion models: Inverting photometric models consists in estimating the best values of their parameters to reproduce the BRDFs sampled in the laboratory. It is then possible to generate the reflectance spectra that would have been measured under any geometrical configuration needed for the planetary simulation. We consider two photometric models: the Hapke model based on physical principles and a modified version of the Ross-Thick Li-Sparse model [3]. The model is able to recreate BRDFs of many natural surfaces and was recently modified by [4] to increase its performances. We use the following RTLSR form:


where the K terms play the roles of Lambertian (iso), volumetric (vol), geometric (geo), and forward scattering (fwd) components respectively. Spectral weights fiso , fvol , fgeo, and ffwd of the four components are determined by the surface reflectance properties. Note that the volumetric kernel contains a simplified treatment of the opposition effect with fixed width and amplitude as this effect is poorly constrained by our measurements. As for the inversion of the models, we consider a Bayesian framework using either a sampling approach based on Markov Chain Monte Carlo [5] or an inverse regression approach based on a preliminary learning step [6,7].

Results and comparison of the models: Both models, Hapke and RTLSR, accurately recreate the spectral features observed on the measurements (fig. 1)