Introduction: The physical properties of a particulate surface, like roughness, grain size, shape and transparency affect how it reflects the incoming light. This concept is used in planetary photometry to infer the surface properties of a celestial object from multiple observations taken from different directions and solar illumination (Hapke et al. 2012). Models linking the observed surface brightness with parameters related to physical properties of the surface have been established. The estimation of such parameters is referred as photometric modelling (Domingue et al., 2016). On Mercury, this technique has been employed to construct monochrome and color global mosaics, but it was never applied to investigate local surface features (Domingue et al., 2016). Therefore, the photometric modelling of Mercury’s surface features represents a novel and useful tool to investigate their nature. In addition, the identification of high-performance photometric models of any given surface material over multiple wavelengths enables to accurately predict the amount of reflected sunlight that will be observed through remote cameras and spectrometers.
In this abstract, we first describe our modelling approach, discuss its improvement with respect to current available photometric models of Mercury, and present a few science cases in which it has been applied. Then, we will also show how this methodology is being applied for the calibration of SIMBIO-SYS observations that will be acquired during the Mercury Orbit Insertion (MOI) phase of the mission.
Methodology: we first analyze the Tyagaraja and Canova craters hollows (i.e., tens meters to several km-sized shallow, irregular, flat‐floored depressions characterized by bright interiors and haloes, Blewett et al., 2011), which are covered by multiple overlapping 8 filter MDIS/WAC (Hawkins et al., 2007) images with resolution higher than 665 m/px and phase angles from 30° to > 100°. Over this region, we construct a latitude-longitude sampling grid with 665 m spacing. For each point we retrieve the surface reflectance and the solar illumination and observation angles using the 3D information of the global USGS DTM and the spacecraft and Sun position information within the observation SPICE kernels. This dataset is fitted with the Hapke and Kaasalainen-Shkuratov photometric models and estimates of their parameter are obtained for each point of the grid (see for example Fig 1C).
Results
Modelling performance: Our results suggest that photometric models derived from the inversion of multiple, overlapping observations are more accurate, especially for bright targets, rather than global photometric models of Mercury (Fig 1A,B). Overall, we estimate a modelling accuracy of better than 10% at 3σ, comparable with the radiometric noise level of the observations.
Hollows results: Our results suggest that hollows are more backscattering than the floor of the crater in which they form. This is consistent with hollows being made of a material rich in holes and/or vescicles, in agreement with a formation by devolatilization. In addition, we find that they are smoother than the crater floor, consistently with the emplacement of a fine particles halo during hollow growth.
