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Planetary mapping has progressively evolved due to the increasing availability of high-quality data and advancements in analytical techniques applied to both surface and subsurface features. In particular, the enhanced spatial resolution and broader coverage provided by cameras and spectrometers aboard orbiting spacecraft around planetary bodies, now enable the production of more detailed geostratigraphic maps. Which maps go beyond the traditional planetary approach, with mineralogical data contributing significantly to the development of more comprehensive final products. Proclus crater is a fresh crater, 28 km in diameter, located on the northwest rim of the Crisium basin, where crystalline plagioclase, as well as pyroxenes and olivine, have been detected. Here, preliminarily, the geomorphological map showed the different surface textures and lineaments of the crater, and a spectral unit map highlighted the different spectral units present in the area. The spectral unit map has been produced by using supervised classification, where the spectral endmembers were extracted by the mean of an automatic tool. The mineralogical interpretation retrieved from spectral endmembers supports the definition of six main spectral units and, moreover, indicates how two of them could be divided into subunits. Those subunits show the systematic variation in plagioclase, low-Ca and high-Ca pyroxene, and their relative abundances. Finally, the geostratigraphic maps associate compositional heterogeneity with different units of the crater, suggesting that this crater was originally characterized by lithologies rich in plagioclase, but mixed with variable low amounts of mafic phases. Since Proclus is a relatively small crater and the units better exposing the mineral’s original heterogeneity are principally distributed in the walls, the spectral units seem to suggest the presence of magma traps during the plagioclase floating during the lunar primary crust formation and constitute heterogeneous terrains within the Highland.

Spectral indexes are tools widely used to analyze the composition of planetary surfaces. Many indexes have been formulated over the years to map the lunar surface, but there is no unified database for them. In this work we describe an Open‐Source Python package called MoonIndex, that recreates 38 indexes compiled from the literature, using data from the Moon Mineralogy Mapper (M3). The processing started with the filtering of the data cubes to reduce the noise, the continuum of the spectrum was then removed using a convex hull or a second‐and‐first‐order fit method. Later, the indexes were calculated, following as possible the original formulations. The results on spectral indexes calculated before the continuum removal were similar to those of the original formulations. Conversely, the results obtained for spectral indexes calculated after the continual removal were not always coherent. Some indexes, like the band depth, are especially sensitive to the removal method, as well as the derived band areas and asymmetries. We also recreated RGB composite maps, our results highlight the compositional patterns in a similar way as the ones in the literature, even if the color ramps can differ. The products of MoonIndex are open, ready for interpretation, versatile, consistent, and cross‐comparable. Plain Language Summary Spectral indexes are parameters defined from the characteristics of reflectance spectra, and they are useful to investigate the spectral properties of a surface and to retrieve mineralogical properties of a planetary body. They can reveal the presence of specific minerals in rocks, indicate mineralogical variations from different units, highlight physical properties of a surface, or show the effect of the exposure to the space environment. For the Moon, several spectral indexes have been formulated over time using data from many spacecraft, but no unified database is available. In this work, we created an open‐source Python package called MoonIndex, which recreates 38 indexes to study the lunar surface. The indexes were collected from the literature, and our results achieved various levels of fidelity. Some of the indexes we calculated exactly reproduce those found in the literature, while in other cases, index calculations differ due to processing constraints or due to missing information in the original formulations, such as the continuum removal method used, or the band operations conducted to create the indexes. MoonIndex is a reliable and versatile tool to approach the compositional analysis of the lunar surface. Key Points MoonIndex is an open‐source tool that successfully recreates spectral indexes for the Moon taken from the literature The continuum‐removal method has a major impact in the resulting indexes, so its selection should be considered when interpreting the data The indexes obtained with MoonIndex are consistent whit the results of previous authors, which usually used licensed software

Geological maps of Earth typically incorporate field observations of rock lithology, structure, composition, and more. In contrast, conventional planetary geological maps are often made using primarily qualitative morphostratigraphic remote sensing observations of planetary surfaces. However, it is possible to define independent quantitative spectral units (SUs) of planetary surfaces, which potentially contain information about surface composition, grain size, and space weathering exposure. Here, we demonstrate a generic method to combine independently derived geomorphic and SUs, using the Rachmaninoff basin, Mercury, as an example to create a new geostratigraphic map. From this geostratigraphic map, we can infer some compositional differences within geomorphic units, which clarifies and elaborates on the geological evolution of the region. Plain Language Summary Geological maps of rocks on Earth include information about what landforms the rocks exhibit, what they are made from, their orientation, and more. Many such details require ground observations, but these are generally not available for planetary geological maps, which rely on spacecraft data. Spacecraft images can be used to map planetary surface textures (geomorphology), but they can also be used to measure surfaces' responses to light (reflectance or emission spectra), which contain information about what the surface rocks are made from, their physical properties (e.g., grain size, roughness, porosity), and how long they have been exposed at the surface. We have combined earlier, independent geomorphic and spectral maps of the Rachmaninoff impact basin on Mercury to create a new “geostratigraphic” map that is more like a geological map that could be made of Earth. The new map highlights places that in the original geomorphic map would have been mapped all as a single unit, but are divisible based on spectral variations, attributable to differences in what the rocks are made from. This allows us to reconstruct a more detailed geological history of the region. Our method can be applied to other regions on Mercury and to other planetary surfaces. Key Points We combine independent morphostratigraphic and spectral units of Rachmaninoff basin to create geostratigraphic units Geostratigraphic units can distinguish volcanic plains and impact melt in contact with each other Geostratigraphic units imply a wider distribution of (LRM‐composition) impact melt than previously recognized

We provide the first visible near-infrared (VNIR) reflectance spectroscopy characterization of a sample from the lunar feldspathic breccia NWA 13859. The sample is a 2 mm thick slab with an approximate area of 35 ± 2 cm2. We characterized the spectroscopic variability by choosing and analyzing representative spots throughout the sample. Our results show a distinct spectral contribution from orthopyroxene, which, according to a preliminary mineralogical characterization, should be a minor phase in the sample. In a second step, we measured several spectra along a transect between a clast and the matrix. In order to oversample the signal, the points analyzed along the sample were partly superimposed to each other (80% areal superposition). The same approach was extended to a grid of points covering an area of about 8.6 cm2, with the goal of obtaining a spatial resolution of the spectral parameters higher than the instrument’s spot size. Using this strategy, we obtained 2D maps of spectral parameters, which allowed us to infer the major mineralogical composition of the sample.

The presence of minerals formed under the occurrence of liquid water during the first billion years on Mars was a key discovery, but there is still a large number of open issues that make the study of these mineral deposits a main focus of remote sensing and laboratory studies. Moreover, even though there is extensive research related to the study of the spectral behavior of mixtures, we still lack a full understanding of the problem. The main goal of this work is the analysis of the detection limits of hydrated and carbonate phases within mixtures with basaltic-like fine regolith in the spectral region 1.0–5.5 µm (1818–10,000 cm−1). We selected two different basalt samples and mixed them with two carbonate phases: a dolomite and a calcite. Spectral features have been investigated isolating the main carbonate absorption features and overtones; deriving trends of spectral parameters such as band depth, band area, full-width-half-maximum; percentage and grain size variations. The results obtained in this work show how the presence of a basaltic component can strongly influence the appearance of the hydrated and carbonate features showing different trends and intensities depending on the grain size and percentage of the carbonate components.

Spectral indexes are tools widely used to analyze the composition of planetary surfaces. Many indexes have been formulated over the years to map the lunar surface, but there is no unified database for them. In this work we describe an Open‐Source Python package called MoonIndex , that recreates 38 indexes compiled from the literature, using data from the Moon Mineralogy Mapper (M 3 ). The processing started with the filtering of the data cubes to reduce the noise, the continuum of the spectrum was then removed using a convex hull or a second‐and‐first‐order fit method. Later, the indexes were calculated, following as possible the original formulations. The results on spectral indexes calculated before the continuum removal were similar to those of the original formulations. Conversely, the results obtained for spectral indexes calculated after the continual removal were not always coherent. Some indexes, like the band depth, are especially sensitive to the removal method, as well as the derived band areas and asymmetries. We also recreated RGB composite maps, our results highlight the compositional patterns in a similar way as the ones in the literature, even if the color ramps can differ. The products of MoonIndex are open, ready for interpretation, versatile, consistent, and cross‐comparable. Spectral indexes are parameters defined from the characteristics of reflectance spectra, and they are useful to investigate the spectral properties of a surface and to retrieve mineralogical properties of a planetary body. They can reveal the presence of specific minerals in rocks, indicate mineralogical variations from different units, highlight physical properties of a surface, or show the effect of the exposure to the space environment. For the Moon, several spectral indexes have been formulated over time using data from many spacecraft, but no unified database is available. In this work, we created an open‐source Python package called MoonIndex , which recreates 38 indexes to study the lunar surface. The indexes were collected from the literature, and our results achieved various levels of fidelity. Some of the indexes we calculated exactly reproduce those found in the literature, while in other cases, index calculations differ due to processing constraints or due to missing information in the original formulations, such as the continuum removal method used, or the band operations conducted to create the indexes. MoonIndex is a reliable and versatile tool to approach the compositional analysis of the lunar surface. MoonIndex is an open‐source tool that successfully recreates spectral indexes for the Moon taken from the literature The continuum‐removal method has a major impact in the resulting indexes, so its selection should be considered when interpreting the data The indexes obtained with MoonIndex are consistent whit the results of previous authors, which usually used licensed software

Exploration of Mercury will continue in the near future with ESA/JAXA’s BepiColombo mission, which will increase the number and the type of datasets, and it will take advantage of the results from NASA’s MESSENGER (MErcury Surface, Space ENviroment, GEochemistry and Ranging) mission. One of the main discoveries from MESSENGER was the finding of a relatively high abundance of volatiles, and in particular of sulphur, on the surface. This discovery correlates well with the morphological evidence of pyroclastic activity and with features attributable to degassing processes like the hollows. BepiColombo will return compositional results from different spectral ranges and instruments, and, in particular, among them the first results from the orbit of emissivity in the thermal infrared. Here, we investigate the results from the emissivity spectra of different samples between a binary mixture of a volcanic regolith-like for Mercury and oldhamite (CaS). The acquisitions are taken at different temperatures in order to highlight potential shifts due to both mineral variation and temperature dependence on these materials that potentially could be present in hollows. Different absorption features are present for the two endmembers, making it possible to distinguish the oldhamite with respect to the regolith bulk analogue. We show how, in the mixtures, the Christiansen feature is strongly driven by the oldhamite, whereas the Reststrahlen minima are mainly dominated by mafic composition. The spectral contrast is strongly reduced in the mixtures with respect to the endmembers. The variations of spectral features are strong enough to be measured via MERTIS, and the spectral variations are stronger in relation to the mineralogy with respect to temperature dependence.

Mercury’s peculiar orbit around the Sun (3:2 spin–orbit resonance) and lack of atmosphere result in one the widest temperature ranges experienced at the surface of a planetary body in the solar system. Temperature variations affect the physical and, therefore, spectral properties of minerals to varying degrees; thus, it is crucial to study them in the context of the upcoming arrival of the BepiColombo spacecraft in Mercury orbit in the fall of 2025. In this work, we heated and cooled analog materials (plagioclase and volcanic glasses) at temperatures representative of the hermean surface. With our experimental setup, we could measure near-infrared (1.0–3.5 μm) and thermal infrared (2.0–14.3 μm) reflectance spectra of our analogs at various temperatures during a heating (25–400 ∘C) or cooling cycle (−125–25 ∘C), allowing us to follow the evolution of the spectral properties of minerals. We also collected reflectance spectra in the visible domain (0.47–14.3 μm) before and after heating. In the visible spectra, we identified irreversible changes in the spectral slope (reddening) and the reflectance (darkening or brightening) that are possibly associated with oxidation, whereas the temperature had reversible effects (e.g., band shifts of from ten to a hundred nanometers towards greater wavelengths) on the infrared spectral features of our samples. These reversible changes are likely caused by the crystal lattice dilatation during heating. Finally, we took advantage of the water and ice present on/in our samples to study the different components of the absorption band at 3.0 μm when varying temperatures, which may be useful as a complement to future observations of the north pole of Mercury. The wavelength ranges covered by our measurements are of interest for the SIMBIO-SYS and MERTIS instruments, which will map the mineralogy of Mercury’s surface from spring 2026, and for which we selected useful spectral parameters that are proxies of surface temperature variations.

The Laguna Blanca basin is a rhomb-shaped basin located at the SE margin of the Puna plateau in the southern Central Andes (Catamarca, Argentina). An interactive analysis using remote sensing and field mapping enabled us to produce a geo-structural map at a 1:350,000 scale. Satellite images from multispectral sensors (ASTER and Landsat 7 ETM+) and medium resolution Digital Elevation Models (SRTM and ASTER GDEM) were used in order to recognize the structures and main lithologies, which were validated in the field and through laboratory tests (e.g. spectral analysis). The final result is a geo-structural map of the Laguna Blanca basin with a new geological unit subdivision, highlighting its tectonic origin, which appears to be related to a releasing stepover along N-S sinistral strike-slip master faults.

The research project ‘Moon Mapping’ has been established in 2014 between the Italian and Chinese Governments to promote cooperation and exchange between undergraduate students from both countries. The operational phase of the project started in early 2015, and will end in 2017, for a total length of three years. The main aim is to train new scholars to be able to work on different kinds of remotely-sensed data collected over the Moon surface by the Chinese space missions Chang’E-1/2. The project coordination has been assigned to the Italian Space Agency for the Italian side and to the Center of Space Exploration, China Ministry of Education, for the Chinese side. Several Chinese universities and Italian national research institutes and universities have been officially involved in this project. Six main research topics have been identified: (1) map of the solar wind ion; (2) geomorphological map of the Moon; (3) data preprocessing of Chang’E-1 mission; (4) map of element distribution; (5) establishment of 3D digital visualization system; and (6) compilation and publication of a tutorial on joint lunar mapping.