期刊
REMOTE SENSING
卷 12, 期 20, 页码 -出版社
MDPI
DOI: 10.3390/rs12203350
关键词
He-3; retention; moon; regolith; remote sensing; space weathering; machine learning; spatial analysis; modeling; multi-sensor
类别
资金
- Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands
The Moon has a large potential for space exploration and mining valuable resources. In particular, He-3 provides rich sources of non-radioactive fusion fuel to fulfill cislunar and Earth's energy demands, if found economically feasible. The present study focuses on developing advanced techniques to prospect He-3 resources on the Moon from multi-sensor remote sensing perspectives. It characterizes optical changes in regolith materials due to space weathering as a new retention parameter and introduces a novel machine learning inversion model for retrieving the physical properties of the regolith. Our analysis suggests that the reddening of the soil predominantly governs the retention, along with attenuated mafic band depths. Moreover, semi-variograms show that the spatial variability of He-3 is aligned with the episodic weathering events at different timescales. We also observed that pyroclastic regoliths with high dielectric constant and increased surface scattering mechanisms exhibited a He-3 abundant region. For ejecta cover, the retention was weakly associated with the dielectric contrast and a circular polarization ratio (CPR), mainly because of the He-3-deficient nature of the regolith. Furthermore, cross-variograms revealed inherent cyclicity attributed to the sequential process of weathering effects. Our study provides new insights into the physical nature and near-surface alterations of lunar regoliths that influence the spatial distribution and retention of solar wind implanted He-3.
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