Timing and characteristics of the latest mare eruption on the Moon

With the cancellation of the Apollo program after Apollo 17 returned from the Moon in 1972, the focus of NASA switched to other areas of the Solar System. Study of the Moon did continue through analysis of the returned samples and remotely sensed data sets (both orbital and surface), as well as through Earth-based telescopic studies. In the 1990s, new orbital data were obtained from several missions (fly-by and orbital), the first being Galileo that allowed the lunar farside to be mapped, followed by global mapping by the Clementine and Lunar Prospector missions. Interest in the Moon started to increase at the beginning of the 21st century as other nations focused their space exploration programs on the Moon. The speech by President Bush in January 2004 put the Moon back into the critical exploration path for NASA, paving the way for humans to return to the lunar surface by 2020. This return will be critical for developing technologies and protocols for the eventual human exploration of other parts of the solar system. At the time of writing (June 2008), the SELENE/Kaguya mission (Japan and Chang’e-1 (China) are orbiting the Moon, with Chandrayaan-1 (India) and Lunar Reconnaissance Orbiter (USA) being scheduled to launch later in 2008. The past (and present) exploration of the Moon begs the question ‘‘what’s left to be done?’’ With the renewed focus on the Moon, now that it is on the pathway for the exploration of Mars (and beyond) a similar question has been raised – what should the astronauts do on the Moon? The publication of the New Views of the Moon book [Jolliff et al., 2006. New Views of the Moon, Reviews in Mineralogy, vol. 60. American Mineralogical Society, 721pp] highlighted a number of important scientific questions that remain unanswered as well as posing many more on the basis of the currently available data. These questions resonated in three Lunar Exploration Analysis Group (LEAG) reports pertinent to this discussion, which were also published (on line) during 2006 (http://www.lpi.usra.edu/leag), and in the National Research Council of the National Academies [2007. The Scientific Context for Exploration of the Moon. National Academies Press, Washington, DC, 112pp] report entitled ‘‘The Scientific Context for Exploration of the Moon’’. This paper synthesizes these recent studies, along with those from the 1980s and 1990s, to emphasize the lunar science questions that remain unanswered. In addition, it summarizes the missions already flown to the Moon along with those that are planned in order to give the reader an idea of exactly what lunar science has been and will be conducted in the hope that it will inspire proposals for missions to address the outstanding science questions. r 2008 Elsevier GmbH. All rights reserved.

/pdf/the-moon-35-years-after-apollo-what-s-left-to-learn-foaasc1vbs.pdf

The Moon 35 years after Apollo: What's left to learn?

[1] Partial least squares (PLS) and principal component regression (PCR) are applied to lunar highland and mare soil data characterized by the Lunar Soil Characterization Consortium (LSCC) for prediction of abundance of lunar soil chemistry and minerals. The goal of this study is to develop a tool for predicting the abundance of chemical and mineral constituents of lunar soils from reflectance data. To determine the best model, the optimal number of PLS components is selected through the cross-validation. The results obtained from PLS and PCR using mean centered and normalized data are compared. The comparison indicates that using mean centered and normalized data has an insignificant effect on estimates of the soil chemical and mineral abundance. Both PLS and PCR perform well in predicting chemical abundance based on prediction errors. For most of minerals considered, one of PLS models always gives the best estimate of mineral abundances. PLS is preferred over PCR in estimation of lunar soil chemical mineral abundances because the first model uses fewer components than the second model. It is concluded that PLS has potential to be applied to lunar hyperspectral imagery (M3 mission) for compositional predictions.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2005JE002598

Partial least squares modeling to quantify lunar soil composition with hyperspectral reflectance measurements

Mineralogy of Mare Serenitatis on the near side of the Moon based on Chandrayaan-1 Moon Mineralogy Mapper (M3) observations

Many of the world's powerful and wealthy nations, including China, have devoted both large amounts of funding and considerable promotion to lunar research and exploration. The launch of Chinese Chang'e-1 satellite and the construction of the scientific observation data platform created a favourable opportunity for research into the lunar geometrical, physical and chemical environment. Based on this background, a Wide Area Network (WAN) based virtual lunar environment was constructed for observation data sharing and further exploration. The systematic architecture and framework were introduced and then strategies of mass data (e.g. lunar digital elevation model, lunar digital orthophoto map and typical thematic lunar data) organisation, integration, management and scheduling were then set up to achieve the 3D visualisation of typical lunar geomorphic features. Furthermore, the integration method of 3D lunar data and the process model of impact craters were studied; thus, the whole lunar and celest...

Construction of a virtual lunar environment platform

Clementine UV/VIS multi-spectral data were used to map mare deposits in the eastern lunar nearside region (Mare Tranquillitatis, Mare Fecunditatis, Mare Serenitatis, Mare Crisium, Mare Nectaris) to understand the volcanic history of this region. An array of Clementine and Clementine-derived data were used to classify mare basalts; these include: 750 nm albedo, UV/VIS ratio, 1 ?m absorption signatures, and Clementine derived FeO and TiO2 contents. We have successfully identified several new geological units and have determined their spectral characteristics. For example, the relatively younger low-Ti basalts were recognized in the eastern part of Mare Tranquillitatis. The central low-Ti basalts in Mare Serenitatis, which had been classed as mISP, were divided into 2 groups. In Mare Nectaris, 2 types of mare basalts were identified, while only 1 group was recognized in the previous study. The stratigraphy constructed from the spectral analysis indicates that the mare deposits tend to become younger in the northern maria, including Serenitatis and Crisium, and older in the southern maria, including Tranquillitatis, Fecunditatis, and Nectaris. According to the relationship between the titanium contents of the mare units and their stratigraphy, the titanium content decreases with time in the early stage but increases toward the end of volcanism in the Serenitatis and Crisium region, while it increases with time but finally decreases in the Tranquillitatis and Fecunditatis region. In connection with the distribution of mare basalts, a large amount of high-Ti mare basalts are found in Mare Tranquillitatis, especially in the western part, while other maria are covered by low-Ti basalts. The iron contents show a similar distribution to that of titanium.

/pdf/lunar-mare-volcanism-in-the-eastern-nearside-region-derived-4qntpkvasy.pdf

Lunar mare volcanism in the eastern nearside region derived from Clementine UV/VIS data

Scientific exploration of lunar surface using a rover in Japanese future lunar mission

https://www.jstage.jst.go.jp/article/rssj1981/20/4/20_4_372/_pdf

Geologic Mapping of the Lunar Maria by Clementine UVVIS Data

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Lunar mare volcanism in the eastern nearside region derived from Clementine UV/VIS data

Scientific exploration of lunar surface using a rover in Japanese future lunar mission

Geologic Mapping of the Lunar Maria by Clementine UVVIS Data