Radiative-Transfer Modeling of Spectra of Planetary Regoliths Using Cluster-Based Dense Packing Modifications

In remote sensing of planetary bodies, the development of analysis techniques that lead to quantitative interpretations of data sets has relatively been deficient compared to the wealth of acquired data, especially in the case of regoliths with particle sizes on the order of the probing wavelength. Radiative transfer theory has often been applied to the study of densely packed particulate media like planetary regoliths, but with difficulty; here we continue to improve theoretical modeling of spectra of densely packed particulate media. We use the superposition T-matrix method to compute the scattering properties of an elementary volume entering the radiative transfer equation by modeling it as a cluster of particles and thereby capture the near-field effects important for dense packing. Then, these scattering parameters are modified with the static structure factor correction to suppress the irrelevant far-field diffraction peak rendered by the T-matrix procedure. Using the corrected single-scattering parameters, reflectance (and emissivity) is computed via the invariant-imbedding solution to the scalar radiative transfer equation. We modeled the emissivity spectrum of the 3.3 μm particle size fraction of enstatite, representing a common regolith component, in the midinfrared (~5–50 μm). The use of the static structure factor correction coupled with the superposition T-matrix method produced better agreement with the corresponding laboratory spectrum than the sole use of the T-matrix method, particularly for volume scattering wavelengths (transparency features). This work demonstrates the importance of proper treatment of the packing effects when modeling semi-infinite densely packed particulate media using finite, cluster-based light scattering models. Plain Language Summary Currently, remote sensing measurements from spacecraft and ground-based observatories are the main means to understand the characteristics of various solar system objects. Remote sensing data can be complex and difficult to interpret, yet their correct interpretation is critical in making scientific findings. Surfaces of many solar system objects are covered with regolith —soil-like material made of fine particles of ices, minerals, and rock fragments. Remote sensing data from such surfaces pose a challenge to accurate interpretations and require improved analysis techniques. Our work takes some of the initial steps in addressing this problem by capturing and modeling one of the fundamental physical processes of remote sensing, known as light scattering. We present a light scattering model that has been tailored, to a reasonable extent, to meet the conditions of planetary regoliths. Our model places particular emphasis on accurately representing the packing (how condensed) of the regolith particles. This leads to more accurate results than previous models, within limits of the scope of our method. Our method contributes to the unfolding development of ever-improving light scattering models for accurate remote sensing data analyses.