Two Simulated Spectral Databases of Lunar Regolith: Method, Validation, and Application

Zhe Zhao,Hong-Yuan Huo,Guangyuan Wei,Ping Zhou

doi:10.3390/rs14020277

Abstract

Our simulated lunar regolith spectra database, based on the Hapke AMSA radiative transfer model (RTM), is a large supplement to the limited number of lunar spectra data. By analyzing the multiple solutions and applicable scopes of the Hapke model by means of Newton interpolation and the least square optimization method, an improved method was found for the simulation of spectra, but it remained challenging to use to invert mineral abundance. Then, we simulated the spectra, mineral abundance, particle size and maturity of 57 mare and highland samples of the Lunar Soil Characterization Consortium (LSCC) in size groups of 10 µm, 10–20 µm and 20–45 µm. The simulated and measured spectra fit well with each other, with correlation coefficients greater than 0.99 and root mean square errors at a magnitude of 10-3. The parameters of mineral abundance, particle size and maturity are highly consistent with the measured values. Having confirmed the reliability of our simulation method, we analyzed the mechanism, reliability and applicability of the “spectral characteristic angle parameter” proposed by Lucey using the simulated spectral data of lunar regolith. Lucey’s method is only suitable for macro analysis of the entire moon, and the error is large when it is used for areas with high abundance of forsterite or ilmenite. In the spectral simulation of lunar regolith, olivine was subdivided into forsterite and fayalite, and the two end-members were mixed to approximately estimate the effect of the chemical composition of olivine on the spectra, which has been confirmed to be feasible.

Highlights

Remote sensing is an important tool for the exploration and study of the Earth and other planets, providing information about the composition and physical structure of the observed target surfaces
The spectral features of Apollo and Luna samples are the result of the combined effects of mineral composition, abundance, space weathering, particle size and viewing geometries, making it difficult to understand how the spectral features are affected by each factor
Denevi et al (2008) pointed out that changes in the chemical composition of mineral endmembers have a great influence on the spectrum, which is more sensitive than mineral abundance

Summary

Introduction

Remote sensing is an important tool for the exploration and study of the Earth and other planets, providing information about the composition and physical structure of the observed target surfaces. The mineral composition of the lunar surface, identified by remotely sensed multispectral and hyperspectral data, provides evidence for the ‘magma ocean’. The mineral abundance and chemical composition, which can be retrieved by hyperspectral data more accurately than multispectral data, has played the main role in establishing the layer structure of the lunar upper crust (Lucey et al, 2014) [9]. The spectral features of Apollo and Luna samples are the result of the combined effects of mineral composition, abundance, space weathering, particle size and viewing geometries (the zenith and azimuth angle of sun and sensor), making it difficult to understand how the spectral features are affected by each factor

Methods

Findings

Discussion

Conclusion