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In the near future, permanent human settlements on the Moon will become increasingly realistic. It is very likely that the Moon will serve as a transit point for deep space exploration (e.g., to Mars). The key to human presence on the Moon is the ability to erect the necessary structures and habitats using locally available materials, such as lunar soil. This study explores the feasibility of using terrestrial laser scanning technology as a measurement method for civil engineering applications on the Moon. Three lunar soil simulants representing highland regions (LHS-1, AGK-2010, CHENOBI) and three lunar soil simulants representing mare regions (LMS-1, JSC-1A, OPRL2N) were used in this study. Measurements were performed using three terrestrial laser scanners (Z+F IMAGER 5016, FARO Focus3D, and Leica ScanStation C10). The research programme focused on the radiometric analysis of datasets from the measurement of lunar soil simulants. The advantages and limitations of terrestrial laser scanning technology for possible lunar applications are discussed. Modifications of terrestrial laser scanners that are necessary to enable their use on the Moon are suggested.
lunar soil simulant; terrestrial laser scanning; Moon; <i>intensity</i>; spectrometer, Article
lunar soil simulant; terrestrial laser scanning; Moon; <i>intensity</i>; spectrometer, Article
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 7 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |