New Insights Into Lithology Distribution Across the Moon

Abstract

Lithology distribution across the Moon is pivotal for understanding lunar evolution. However, so far, the distribution of lunar rock suites is still uncertain; as a result, many related core issues on lunar evolution have long been in dispute. This work reports on a new lithology distribution map across the Moon and discusses some critical issues of the lunar evolutionary process. The oxide abundances derived from Chang'E‐1 Interference Imaging Spectrometer imagery and the Th contents inferred by Lunar Prospector Gamma Ray and Neutron Spectrometer data are employed to generate the lithological map by using the decision tree C5.0 algorithm. The following conclusions are inferred from this new map. (1) Magnesian suite is widely distributed across the Feldspathic Highlands Terrane and in the periphery of the South Pole‐Aitken Terrane. Thus, the viewpoints have been validated that the early magnesian magmatism may be a global phenomenon and that KREEP basalt is not necessary for the petrogenesis of Mg‐rich rocks. Moreover, the regions of Dryden, Chaffee S, Theophilus, and Moscoviense are confirmed as magnesian suite exposures. (2) The observation that the Feldspathic Highlands Terrane has a higher Mg/(Mg + Fe) value than the maria is related to the flood of the Mg suite across the Feldspathic Highlands Terrane. (3) The specific exposed locations of the alkali suite across the Moon have long been unsolved, and this work discloses that the alkali suite prevails in the outskirts of the Procellarum KREEP Terrane, the center of the South Pole‐Aitken Terrane, and some isolated locales. (4) Focusing on distinguishing mare basalts from other mafic rocks, seven geochemical indices are proposed to determine the potential exposures of mare basalts across the Moon. (5) In Mare Insularum, a series of KREEP volcanisms may have occurred and lasted longer than the mare volcanism.

Lunar Cryptomare: New Insights Into the Balmer‐Kapteyn Region

“…The mantle rocks mainly refer to mare basalts and related pyroclastic deposits Petro, 2011;Taylor et al, 1991;Warren, 1993;Wieczorek et al, 2006). The lithology classification model proposed in Wang and Zhao (2017) is employed to identify the lithology distribution across the B-K region. Lunar regolith also has lithologic characteristics, and the materials in each lunar surface unit are often the mixing of various rocks and soils; therefore, it is assumed that the lithology of the lunar surface can be described by the dominant pristine rock type in each lunar surface unit.…”

“…Validated by the lunar rock samples, the lithology classification model has an overall classifying accuracy of 97.32% for the five rock suites, and possesses the classifying precisions of 100%, 92.86%, 96.3%, 100%, and 97.8% for FAS, magnesian suite, alkali suite, KREEP basalts, and mare basalts, respectively. Readers may refer to Wang and Zhao (2017) for the specific description of the lithology classification model, including the selection basis and the contribution values to rock suite recognition of the above seven geochemical indices, the identifying criteria for each rock suite, the specific lunar rock samples corresponding to each identifying criterion, and the confidence evaluation of the lithology classification model. To validate the generalization ability of the lithology classification model, 10 times tenfold cross validations (Geisser, 1993;Goldstein, 2005) were conducted, and the 10 times validation accuracies are 85.9%, 86.7%, 88.6%, 84.6%, 86.6%, 85.8%, 87.2%, 85.2%, 84.5%, and 86%, respectively.…”

“…With regard to the magnesian suite, the gabbronorite 67667,3 has a FeO concentration of 17.1 wt% (Warren & Wasson, 1979;Wieczorek et al, 2006). Readers may refer to Wang and Zhao (2017) for the further discussion on the above two methods of mare basalt identification. As to KREEP (KREEP is an acronym for the lunar materials with abundant potassium, rare-earth elements and phosphorus.)…”

“…Validated by the 119 returned lunar rock samples from the Apollo and Luna missions and by the 30 lunar meteorite samples, the recognition accuracy of mare basalts is 97.8% (Wang & Zhao, 2017; see section 2.2). First, Lunar Reconnaissance Orbiter (LRO) LRO Camera (LROC) Wide Angle Camera (WAC) Normalized Reflectance images (643 nm) without shadows (WACNS) are employed to identify DHC.…”

“…Therefore, whether the criteria of high-Ca pyroxene and high FeO contents can distinguish mare basalts from other mafic materials still need further study. Readers may refer to Wang and Zhao (2017) for the further discussion on the above two methods of mare basalt identification. This work, focusing on the two current limitations, takes two improvements to refine the identification of cryptomaria.…”