Mercury Spectrophotometric Modeling Using MESSENGER Data
Mercury is covered by a regolith that affects how light is scattered from the planet’s surface. To deduce the physical properties of Mercury’s regolith, we use spectrophotometry from the Mercury Dual Imaging System instrument of NASA’s MErcury Surface, Space ENvironment, GEochemistry and Ranging mis...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2024-01-01
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| Series: | The Planetary Science Journal |
| Subjects: | |
| Online Access: | https://doi.org/10.3847/PSJ/ad8b9f |
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| Summary: | Mercury is covered by a regolith that affects how light is scattered from the planet’s surface. To deduce the physical properties of Mercury’s regolith, we use spectrophotometry from the Mercury Dual Imaging System instrument of NASA’s MErcury Surface, Space ENvironment, GEochemistry and Ranging mission. The data come in eight colors in wavelengths of 433.2–996.2 nm, with phase angles of 20°–125°. A theoretical particulate-medium model is used to interpret the observed reflectance. The model includes a shadowing correction that depends on three geometry parameters of the regolith, allowing for the retrieval of the physical regolith structure from the spectrophotometry. The most important parameter is the packing density v , while the other two parameters describe the regolith’s roughness as a fractional Brownian motion surface: the Hurst exponent H in the horizontal and the amplitude σ in the vertical direction. The numerical implementation of the model includes a set of discrete parameter values, which we extend by using trilinear interpolation: 0.15–0.55 for v , 0.20–0.80 for H , and 0.00–0.10 for σ . We optimize the model parameters in the least-squares sense using the Nelder–Mead simplex method followed by Markov Chain Monte Carlo (MCMC) sampling. Our results indicate that Mercury’s regolith is densely packed ( v = 0.547 ± 0.004) with moderate horizontal variations ( H = 0.606 ± 0.009) and large height variations ( σ = 0.0998 ± 0.0003). The MCMC solution allows us to predict the spectrophotometry for differing viewing geometries. Future work includes improving the implementation of the model by increasing the packing density values. |
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| ISSN: | 2632-3338 |