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International audience; Virtual Reality (VR, with headsets) and Augmented Reality (AR, using a smartphone or tablet) coupled with 3D photogrammetric reconstructions are increasingly used for science, education and outreach applications. These techniques are not new [e. g. 1, 2], but they are becoming progressively more widespread thanks to the release in 2016 of technologically mature and cost-effective hardware solutions accessible to the general public. In the field of planetology, VR and AR theoretically allow the possibility to simulate field trips to remote places that are otherwise inaccessible to humans. Using high-resolution imaging, coupled with spectral or morphological data gathered by robotic explorers (orbiters, landers, rovers), we can create integrated virtual environments that accurately represent the surface of planetary bodies and allow the cross-comparison of different datasets. These virtual environments provide the possibility to navigate on a global scale using orbital data, and move down to the surface when in situ data are available to visualize and analyze local outcrops. This is particularly the case of the Moon and Mars, where both extensive remote and groundtruth data are available [3, 4, 5]. We are investigating how the information from various sources can be combined in a comprehensive way to display, manipulate, analyze and share both analytical data and results. We have for example integrated visible high-resolution imagery, digital elevation and outcrop models, geomorphological maps and compositional maps derived from spectroscopic measurements on several test sites such as the Copernicus crater and Apollo 17 landing site on the Moon, the Crommelin crater and Kimberley area (Gale crater) on Mars, and the Hokusai quadrangle area on Mercury. The VR and/or AR rendering of simple orbital and/or ground-based 3D models can be performed using a web-based solution such as Sketchfab (e.g. https://sketchfab.com/LPG-3D or https://sketchfab.com/planmap.eu), offering the possibility to visualize, interact, and share medium-resolution 3D versions of these multi-scale data (Fig. 1a and 1b). The use of a more powerful and versatile solution based on a game engine [6] allows the development of more complex solutions, for example dedicated measurement tools (Fig. 1c) or multi-layering capabilities (Fig. 1d). These approaches offer new possibilities in terms of data exploration, analysis, and applications for research and education during "virtual planetary field-trips".

Description of this data set The files named: "Io_mean_spectrum_JM0051.txt", "Io_mean_spectrum_JM0071.txt", "Io_mean_spectrum_JM0091.txt", "Io_mean_spectrum_JM0101.txt", "Io_mean_spectrum_JM0171.txt", "Io_mean_spectrum_JM0181.txt", "Io_mean_spectrum_JM0201.txt", "Io_mean_spectrum_JM0241.txt", "Io_mean_spectrum_JM0261.txt" contain the result of the processing of Juno/JIRAM spectroscopic data of Io acquired respectively during the data sequences: JM0051 (orbit 5), JM0071 (orbit 7), JM0091 (orbit 9), JM0101 (orbit 10), JM0171 (orbit 17), JM0181 (orbit 18), JM0201 (orbit 20), JM0241 (orbit 24), and JM0261 (orbit 26). Each of these files contains the average spectrum of Io in the 2-5 µm range as measured by JIRAM in that particular data sequence / orbit. All of these are ASCII files, where the first column represents the JIRAM wavelength vector expressed in microns (µm) after correction for the odd-even effect, and the second column is the average spectrum of Io expressed in units of calibrated radiance factor (I/F) resulting from that particular data sequence. The files named: "Redundancy_map_band_407um.dat" and "Statistical_weights_map_band_407um.dat" include the processed data related to the redundancy maps and statistical weights shown respectively in panels a and b of Figure 3. In particular, the redundancy map is stored as an unsigned integer, little-endian binary stream of bytes, while the statistical weight map is stored as a single-precision floating-point, little-endian binary stream of bytes. These bidimensional maps are ordered according to the Band Sequential (BSQ) image encoding. These files can be easily opened with the commercial ENVI software, and are accompanied by ASCII header files with same filename and suffix ".hdr". Such header files include details that are needed to properly open and read the ".dat" files without the ENVI software and regardless of the programming language being used. The files named: "WeightedAverage_map_band_407.dat", "WeightedAverage_map_band_437.dat", "WeightedAverage_map_band_279um.dat", and "WeightedAverage_map_band_254um.dat", include the processed data related to the maps shown respectively in panels a, b, c and d of Figure 4. These bidimensional maps are stored as a single-precision floating-point, little-endian binary stream of bytes, ordered according to the Band Sequential (BSQ) image encoding. All of these files can be easily opened with the commercial ENVI software, and are accompanied by ASCII header files with same filename and suffix ".hdr". Such header files include details that are needed to properly open and read the ".dat" files without the ENVI software and regardless of the programming language being used. The files named: "WeightedAverage_map_band_392.dat", "WeightedAverage_map_band_447.dat", "WeightedAverage_map_band_455um.dat", and "WeightedAverage_map_band_462um.dat", include the processed data related to the maps shown respectively in panels a, b, c and d of Figure 5. These bidimensional maps are stored as a single-precision floating-point, little-endian binary stream of bytes, ordered according to the Band Sequential (BSQ) image encoding. All of these files can be easily opened with the commercial ENVI software, and are accompanied by ASCII header files with same filename and suffix ".hdr". Such header files include details that are needed to properly open and read the ".dat" files without the ENVI software and regardless of the programming language being used. The files named: "WeightedAverage_map_band_210.dat", "WeightedAverage_map_band_407.dat", "WeightedAverage_map_band_265um.dat", and "WeightedAverage_map_band_392um.dat", include the processed data related to the maps shown respectively in panels a, b, c and d of Figure 6. These bidimensional maps are stored as a single-precision floating-point, little-endian binary stream of bytes, ordered according to the Band Sequential (BSQ) image encoding. All of these files can be easily opened with the commercial ENVI software, and are accompanied by ASCII header files with same filename and suffix ".hdr". Such header files include details that are needed to properly open and read the ".dat" files without the ENVI software and regardless of the programming language being used. The files named: "WeightedAverage_map_band_335um.dat" and "WeightedAverage_map_band_355um.dat" include the processed data related to the scatterplots shown respectively in panels b and c of Figure 8. These bidimensional maps are stored as a single-precision floating-point, little-endian binary stream of bytes, ordered according to the Band Sequential (BSQ) image encoding. All of these files can be easily opened with the commercial ENVI software, and are accompanied by ASCII header files with same filename and suffix ".hdr". Such header files include details that are needed to properly open and read the ".dat" files without the ENVI software and regardless of the programming language being used., JIRAM is funded by the Italian Space Agency (ASI), ASI-INAF contract 2016-23-H.0. The JIRAM instrument was built by Selex ES, under the leadership of the Italian National Institute for Astrophysics, Institute for Space Astrophysics and Planetology (INAF-IAPS), Rome, Italy. JIRAM is operated by INAF-IAPS, Rome, Italy. Support of the Juno Science and Operations Teams is gratefully acknowledged. Part of this work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA.

Quadrangle Ac-H-10 'Rongo' (Lat 22°S to 22°N, Lon 288°-360°E) shows a fairly homogeneous topography, with the presence of notable elevations such as Ahuna Mons, Liberalia Mons, and part of Samhain and Uhola Catenae. The deepest areas correspond to the Rongo crater region, the areas between Samhain and Uhola catenae, and the region of the quadrangle south of Ahuna Mons. A substantial variability in the 2.7-μm band depth distribution is observed across the Rongo quadrangle, indicating an east-west gradient in the abundance of Mg-phyllosilicates. The NH4-phyllosilicates distribution appears quite homogeneous, except some localized regions, such as crater Haulani's ejecta, the flanks of Ahuna Mons, and crater Begbalel. The two band depths at 2.7 and 3.1 μm display an overall low correlation, suggesting a variable degree of mixing between Mg-phyllosilicates and NH4-phyllosilicates. At the local scale, mineralogical phases other than phyllosilicates are observed. Quadrangle Rongo includes sodium carbonate-rich regions, such as the flanks of Ahuna Mons, the ejecta of Xevioso crater located in the southern edge of Liberalia Mons, and crater Begbalel, which often display a reduction in both the 2.7- and 3.1-μm band depths, associated with an increased band depth at ∼4 μm, related to the presence of Na-rich carbonate phases. This suggests recent hydrothermal activity in this area, due to several episodes of cryovolcanism, or impacts that unveiled a peculiar composition in the shallow subsurface. Alternatively, the crust in this region might show a variable degree of compactness, such that the formation of Na-carbonates is favored only in specific locations (De Sanctis et al., 2016; Ruesch et al., 2016; Zambon et al., 2017). From a geological standpoint, quadrangle Ac-H-10 Rongo shows a correlation between its two main geologic units (Platz et al., 2017) and the distribution of Mg-phyllosilicates, suggesting a link between geology and mineralogy in this area.

Ac-H-6 ‘Haulani’ is one of five quadrangles that cover the equatorial region of the dwarf planet Ceres. This quadrangle is notable for the broad, spectrally distinct ejecta that originate from the crater Haulani, which gives the name to the quadrangle. These ejecta exhibit one of the most negative (‘bluest’) visible to near infrared spectral slope observed across the entire body and have distinct color properties as seen in multispectral composite images. Besides Haulani, here we investigate a broader area that includes other surface features of interest, with an emphasis on mineralogy as inferred from data obtained by Dawn's Visible InfraRed mapping spectrometer (VIR), combined with multispectral image products from the Dawn Framing Camera (FC) so as to enable a clear correlation with specific geologic features. Our analysis shows that crater Haulani stands out compared to other surface features of the quadrangle. Albedo maps obtained in the near infrared range at 1.2 µm and 1.9 µm reveal that the floor and ejecta of Haulani are indeed a patchwork of bright and dark material units. Visible to near-infrared spectral slopes display negative values in crater Haulani's floor and ejecta, highlighting bluish, younger terrains. Diagnostic spectral features centered at ∼2.7 µm and ∼3.1 µm respectively indicate a substantial decrease in the abundances of magnesium-bearing phyllosilicates and ammoniated phyllosilicates in crater Haulani's floor and bright ejecta. Similar, but less prominent, spectral behavior is observed in other geologic features of this quadrangle, while the general trend in quadrangle Ac-H-6 for these two mineral species is to increase from the northwest to the southeast. However, it is worth noting that the correlation between the ∼2.7 µm and ∼3.1 µm spectral parameters is generally strong in the Haulani crater's area, but much weaker elsewhere, which indicates a variable degree of mixing between these two major mineral phases in moving away from the crater. Finally, the region of crater Haulani displays a distinct thermal signature and a local enhancement in calcium and possibly sodium carbonate minerals, which is hardly found in the rest of the quadrangle and is likely the result of intense hydrothermal processes following the impact event. These evidences all together confirm the young age of crater Haulani, as they have not been erased or made elusive by space weathering processes.