Visible and near-infrared spectral results of Chang’E-5 surficial and subsurface soils
Yunzhao Wu, Yinguang Chai, Yu Lu, Xuejun Chen, Wenyu Wang, Jin Qiu
Abstract
Aims . Studies on high-resolution and high-precision laboratory reflectance spectra of the Moon have historically been restricted to the analysis of old Apollo samples (>3.0 Ga). In contrast, studies of young lunar soils have exclusively relied on the analysis of remote sensing spectra. In this study, we present the results of a laboratory spectral investigation of young lunar soils (~2.0 Ga) obtained by the Chang’E-5 (CE-5) mission. Methods . We analyzed surficial and subsurface soils collected through scooped and drilled sampling methods. The laboratory reflectance spectra of the CE-5 soils were compared with those of Apollo soils and orbital spectra. Two methods were employed for maturity inversion. The relationship between the UV-vis color and TiO 2 content of young basalts was also investigated. Results . The CE-5 samples exhibit much fresher spectral features, including higher reflectance, deeper absorption depths, and a smaller visible and near-infrared continuum slope (VNCS), compared to pristine regolith. The subsurface soils sampled from a depth of approximately 10 cm exhibit a slightly fresher spectral feature compared to the surficial soils. Our comparison revealed a rapid rate of space weathering at the lunar surface compared to the vertical overturn. Compared to older iron-rich soils, the CE-5 soils have a larger reflectance but similar UV-vis ratios. The UV-vis ratio alone could not accurately predict the TiO 2 content of all mare basalts. The CE-5 samples provide a new ground truth for estimating the TiO 2 content of young lunar basalts, which have the largest uncertainty in TiO 2 content, as estimated from spectral parameters. We find that the samples returned by the CE-5 mission represent disturbed soils and that they exhibit significantly fresher characteristics compared to pristine regolith, a fact that should be kept in mind when using samples as ground truth for remote sensing research.