Application of Machine Learning Techniques to Distinguish between Mare, Cryptomare, and Light Plains in Central Lunar South Pole-Aitken Basin

被引:0
|
作者
Chuang, Frank C. [1 ]
Richardson, Matthew D. [1 ]
Whitten, Jennifer L. [2 ]
Moriarty, Daniel P. [3 ,4 ,5 ]
Domingue, Deborah L. [1 ,4 ]
机构
[1] Planetary Sci Inst, Tucson, AZ 85719 USA
[2] Smithsonian Inst, Ctr Earth & Planetary Studies, Natl Air & Space Museum, Washington, DC 20560 USA
[3] NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA
[4] Univ Maryland, College Pk, MD 20742 USA
[5] NASA, Ctr Res & Explorat Space Sci & Technol 2, Goddard Space Flight Ctr, Greenbelt, MD USA
来源
PLANETARY SCIENCE JOURNAL | 2025年 / 6卷 / 02期
关键词
ERUPTION CONDITIONS; SURFACE; DIFFERENTIATION; MINERALOGY; VOLCANISM; MODEL; CRUST;
D O I
10.3847/PSJ/ada4a6
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
We apply machine learning techniques to identify and map resurfacing units in the central South Pole-Aitken (SPA) basin using three Lunar Reconnaissance Orbiter (LRO) mission data sets: 321/415 nm and 566/689 nm band reflectance ratios from Hapke photometrically standardized albedo maps and a Terrain Ruggedness Index map using the Wilson et al. method. Other data were considered, but albedo and topography data were key in distinguishing between maria, cryptomaria, and light plains. A two-step image classification approach was applied to the data sets, an unsupervised K-Means algorithm followed by a supervised Maximum Likelihood Classification (MLC) algorithm. K-Means identified four units, one associated with dark smooth maria, two not associated with any particular features, and a fourth associated with edge effects. To further discriminate between the two nonassociated units, the K-Means unit map and an LRO morphologic basemap were used to select multiple training areas for three defined units in the MLC algorithm: mare, cryptomare, and cryptomare/light plains. From the training area values, the MLC unit map showed a distinction between the two prior indistinguishable K-Means units. Our results show (1) that the cryptomare from the MLC algorithm is in good agreement with cryptomaria mapped by J. L. Whitten & J. W. Head, (2) that the presence of scattered maria within large patches of cryptomaria indicates possible incomplete and/or uneven ejecta deposits or sheet flows covering cryptomare surfaces, and (3) a 79% increase in the total extent of cryptomaria compared to that by J. L. Whitten & J. W. Head for the same given study area in central SPA.
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页数:12
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