Enceladus, Saturn's sixth-largest and one of its innermost moons, is an active icy world. The Cassini mission (2004-2017) discovered water-rich plumes venting from fractures in its South Polar Terrain (SPT), making Enceladus a prime candidate in the search for habitable environments in the Solar System. Understanding its geological environment and thermal evolution requires knowledge of both surface and subsurface properties, which remain poorly constrained by optical and infrared observations alone. Microwave radar observations, on the other hand, are sensitive to subsurface scattering structures and temperatures at depth. Here we present the joint analysis of Cassini RADAR active and passive observations acquired at a wavelength of 2.2-cm during the only targeted-flyby of Enceladus (called E16) dedicated to the RADAR, on November 6, 2011. Using a multi-layer unified backscatter-thermal emission radiative transfer model, we jointly analyze the Synthetic Aperture Radar backscatter (sigma(0)) and brightness temperatures (T-B) measured along the E16 closest-approach swath, in the SPT. The results point to large ice grain radii (>500 mu m) throughout the swath, favoring volume scattering as the dominant scattering mechanism. As a result, most of the radar signal comes from the first few meters below the surface, even though, due to the high transparency of Enceladus' icy subsurface, waves can penetrate much deeper, up to 10-20 m in some areas. Variations in water-ice purity (0-25%) and porosity (60-90%) are inferred between geological terrains, indicating differences in surface maturity and age. Anomalously high T-B values observed over parts of the swath can only be explained by the presence of an ocean at shallow subsurface (2-5 km deep) combined with a thin (1-10 m) regolith and a conductive ice-shell, leading to enhanced heat loss (as high as similar to 900 mWm(-2)). The presence of an ocean at shallow depth is also possible elsewhere on the swath but combined with a thick (similar to 100-500 m) and porous (60-90%) regolith layer acting as an insulating layer, leading to low heat losses (< 300 mWm(-2)) in these areas. Our study also highlights the strong value of co-located radar active and passive observations for constraining the geological and thermal state of the sub-surfaces in the Solar system and provides key information for future radar observations of Enceladus.

The Galilean moons are witnesses to unique physical processes and exhibit active phenomena over a wide range of timescales. They are therefore central targets of upcoming exploration missions, notably Europa through NASA’s Europa Clipper mission and Ganymede through ESA’s JUICE mission. These moons are strongly influenced by the intense electromagnetic environment generated by Jupiter and display strong coupling between their surfaces, exospheres, and the Jovian magnetosphere. The surface morphologies observed appear to result from a competition between external processes, such as space weathering [1] and micrometeorite bombardment, and internal processes, such as the upwelling of deep material [2]. The presence of subsurface water reservoirs may enable material exchange between the interiors of these moons and their external environments. This also reinforces their strong exobiological potential and raises important questions regarding their habitability. An improved understanding of the physicochemical properties of their surfaces is therefore a key step in characterising the endogenic and exogenic processes that have governed the evolution of these moons over geological timescales.The study of surface properties is facilitated by the large volume of data obtained from both ground-based observations and spacecraft missions that have explored the Jovian system. In particular, near-infrared data (1–5 µm) are available at a range of spatial and spectral resolutions. In this study, we focus on observations acquired by JWST/NIRSpec and Galileo/NIMS. Many compounds have already been detected and mapped on these moons [3,4,5], but little is known regarding other properties, such as their grain size and porosity. To robustly estimate the microphysical surface properties, realistic radiative transfer models are required to account for the highly nonlinear scattering interactions occurring within complex surfaces. Here, we present results obtained using the Hapke model [6], considering two distinct cases: (i) a semi-infinite, single-layer granular mixture with a fixed porosity of 50%, and (ii) a two-layer model consisting of a granular medium of variable thickness and porosity overlying a semi-infinite granular substrate. To retrieve volumetric abundances, grain sizes, porosity, and the thickness of the upper layer, we employ a Bayesian inversion approach that has demonstrated its effectiveness in previous surface characterisation studies [7,8].We present results obtained from several distinct observations of Europa’s trailing hemisphere, as well as multiple spectroscopic inversions performed on JWST observations of Europa and Ganymede. The derived results enable the production of maps of surface microphysical properties. [1] Carlson et al., 2005; [2] Pappalardo et al., 1999; [3] Ligier et al., 2016; [4] King et al., 2022; [5] Villanueva et al., 2023; [6] Hapke et al., 2012; [7] Cruz-Mermy et al., 2022; [8] Cruz-Mermy et al., 2025.

Martian gullies are geologically recent landforms that may form either through liquid-water activity and/or through processes involving CO2 ice. We investigated the mechanisms responsible for the formation or modification of these features by focusing on the active site of Sisyphi Cavi (68°S, 1°E), located outside the typical latitude range of gully presence. Using CRISM and OMEGA infrared data, we characterized the composition and physical state of seasonal surface ices to test the relevance of H2O and CO2 ice driven mechanisms. Our analysis shows that H2O ice is not detected as an independent surface deposit, although it may be present as minor inclusions within the CO2 ice layer. In particular, during the final phase of CO2 ice sublimation in late spring, no H2O ice signature is observed. In the area, faint spectral signatures of sulfate salts are observed, but their distribution and amount do not suggest any direct link with gully activity. Available observations during early and mid-spring reveal that CO2 ice is translucent during these times, suggesting that it likely remains in this state through most of the ice season. However, a temporal mismatch between dark spot formation - indicative of CO2 geysers through translucent ice - and gully modification (respectively occurring late winter to early spring, and mid to late spring) exists. This does not suggest a systematic link between both processes. Overall, the available observations provide no evidence that liquid water contributes to present-day gully activity at Sisyphi Cavi, while offering no support either for the hypothesis that gully modifications are mainly driven by the formation of CO2 geysers. Gully modifications at Sisyphi Cavi, observed during the late sublimation stages of CO2 ice, may be rather more appropriately explained by CO2-ice-based fluidization or avalanche processes.

The Máni mission will contribute to the overarching goal of enabling Europeans to explore the Moon by providing high-value and novel information that will assist in mission planning, de-risk landings, and facilitate scientific exploration. This will be achieved through a mapping mission that is designed from its inception to take advantage of recent advances in the field of photoclinometry and photometry.The Máni mission will be the first mission to employ a targeted multi-angular photoclinometric mapping approach to map key regions of interest of the Lunar surface. We aim to acquire the highest resolution orbital images of the Lunar surface, including the Polar regions, across a wide range of viewing geometries. From these images, we will produce detailed maps of the topography and reflectance properties at a resolution like that of the images. Additionally, through photometric analyses, we will provide sub-pixel information on surface properties down to mm-scale. Uniquely, from the probabilistic nature of the novel data processing employed, mission data products will all be accompanied with a measure of their level of confidence. This implies that future missions can select, e.g., landing sites that are not only predicted to comply with their mission requirements but also have a high level of confidence of complying with their requirements, thus lowering risks and increasing chances for mission success.The mission data processing is improved relative to already published work by mission members (1) in its integration of high-resolution imagery with available a priori information like laser altimetry data. It features a computationally efficient and advanced photoclinometric model that accounts for complex illumination and observing geometry. This enables pixel-level resolution in the simultaneous output of both topographic maps and surface reflectance maps. While novel and under ongoing development, the mission data processing approach is validated using available Lunar images.Exploration and scientific goalsBelow, we present a selection of studies that highlight the range of investigations that can be undertaken based on Máni mission data products.Assessing landing and mission sites of importance for human and robotic explorationThe primary focus of the Máni mission is to provide higher-resolution mapping of potential landing sites and locations of interest for exploration. The high-resolution images (as good as 20 cm/px at 50 km altitude) and topographic maps provided by the Máni mission enable unprecedented identification of hazards such as boulders, craters, and slopes that could jeopardize landing success. In particular, the ability to provide not only an accurate high-resolution topography of candidate landing sites but also assess the level of confidence of this presents a novel ability to not only select sites that are predicted to meet mission/lander requirements but sites that do so with a high probability.Sites of importance to future human and robotic exploration imposes demanding requirements on the operational orbit of the mission as many of these, e.g. for the Artemis missions, are situated close to the Lunar South Pole (2–4).Quantifying Earths albedo – a key parameter in climate modelsDetailed mapping of the lunar reflectance properties for two key regions, Grimaldi and Crisium, that has historically been used for Earthshine observations (5, 6) will enhance the value of lunar Earthshine data. It will not only strengthen future earthshine measurements but also enable a transformative reanalysis of archived earthshine data. This will yield more precise global (semi‐hemispheric) albedo estimates and facilitate targeted assessments of polar albedo—a critical parameter given current concerns over ice-cap melt, as well as address the observed decline in terrestrial albedo over a 20-year period.Effects of space weathering on the micro-texture of Lunar regolithWith the Máni mission we can take a new step forward in efforts to characterize and understand the lunar micro-texture. By deliberately targeting geological units from different ages and levels of maturity, we will be able to decipher the processes creating the regolith and estimate the evolution timescale. The Máni mission will augment these studies by mapping photometric properties at a resolution as good as ~20 cm/px. The high resolution provided by the Máni mission will also enable investigation of how other geological processes – e.g., lunar swirls, crater rays and volcanic flow – affect and modify the surface micro-texture. Mission and spacecraftThe Máni mapping methodology requires the acquisition of at least 5, preferentially 10, overlapping high-resolution images of a region of interest covering a range of viewing angles separated by more than 100°. Furthermore, at least two illumination angles, separated by at least 20°, must be captured as part of the images acquired of a region of interest. These requirements imply that at least two overflights, acquiring 5 images during each, of the target area separated in time by at least a full Lunar sideral period are needed to acquire the necessary image-data to map a region of interest.The Máni spacecraft is developed around the single large primary payload of the mission - an optical 300 mm telescope with a panchromatic 2D detector capable of acquiring images of the Lunar surface at a resolution as good or better than 20 cm/pixel at 50 km altitude. A secondary smaller colour imager intended to provide context for the primary images is also included.ReferencesI. Fernandes, K. Mosegaard, Planet. Space Sci. 218, 105514 (2022).E. Peña-Asensio, Á.-S. Neira-Acosta, J. M. Sánchez-Lozano, Acta Astronaut. 226, 469–478 (2025).C. Orgel et al., Planet. Sci. J. 5, 29 (2024).S. J. Boazman et al., Icarus. 421, 116240 (2024).P. R. Goode et al., Geophys. Res. Lett. 48 (2021), doi:10.1029/2021gl094888.P. Thejll, H. Gleisner, C. Flynn, Astron. Astrophys. 573, A131 (2015).

IntroductionWe introduce a novel statistical approach for propagating multifractal 2D fields to finer scales (upscaling a field at higher resolution than actually observed) and inpainting missing data points. The strategy ensures that the new artificially generated data follows the multifractal statistics and thus produces a more realistic field than usual interpolation methods. The method is called MUFFIN (MUltifractal Fast Fourier INterpolation).Multifractal frameworks are used to describe systems that exhibit variability across many scales. Several formalisms and models exist to describe it [1, 2, 3], each with different assumptions, tools and applications. The most common one used in the geophysics is the Universal Multifractal (UM) model [4-9]. Moreover, since geophysical processes are generally non-stationary, an additional fractional integration to the UM is provided. This model is referred as the Fractionally Integrated Flux (FIF) and was used to perform the upscaling.A FIF field has an analytical moment scaling function defined by the knowledge of only three parameters α, C1 and H. The intermittency of a field is controlled by the multifractality exponent α and the sparsity degree C1. The smoothness and non-conservation of the field are described by the Hurst exponent H. MethodsFor the upscaling algorithm, we used the UM continuous method from (chap. 5)[10] to generate a 2D synthetic field with the same multifractal properties (α, C1) as the input field. The input field is converted to a UM field and its size is increased by a factor U. The finer scales of the synthetic field are then grafted to the input field, propagating its cascade to smaller scales. The final product is obtained by reapplying the fractional integration flux to get back a FIF field. The upscaling algorithm relies on the Fast Fourier Transform (FFT) and is therefore computationally efficient. It has no constraints on the field size or upscaling factor, making it robust and easy to use.For the inpainting algorithm, we use a linear combination of 2D synthetic fields (candidates) with the same multifractal properties as the input field. The optimal linear combination of candidates recreate the exact same input field with observed data. Since the candidates do not have missing points, the unobserved points are simply filled with the one from the combined candidates. Both methods are detailed in [11]. ResultsComparison were made upon both synthetic and realistic examples. We present here the results applied on a real dataset. The upscaling and inpainting were performed on the North quadrangle of Mercury (887m/pixel), respectively on the full dataset and on the same dataset with missing points (corresponding to N orbits laser altimeter measurements). In order to validate our method, the ground truth, upscaled and inpainted fields are analyzed and compared with the Mean Haar Fluctuations (MHF) and the Power Spectral Density (PSD).The upscaling and inpainting approaches ensure an interpolated field with relatively small errors [11].For the upscaling, the MHF Relative Root Mean Square (RRMS) and PSD RRMS are always >1% and 17% and 5% and 7% and

Recent laser altimeters are able to not only measure the ranging distance between the spacecraft and the surface but also the full time-of-flight of the photons or pulse shape. This new capabilities allows to measure the intra-footprint properties: surface slope distribution and surface microtexture. Here we simulate and discuss for the first time the effect of surface microtexture, especially for ice covered surface with longer penetration depth. Using the WARPE simulation software, two kind of microtextures are simulated: compact slab and granular. Laser pulse shape for an ideal instrument is simulated using physical properties such as the grain size, material composition, thickness, compacity (filling factor, porosity) rather than radiative properties. The effects of these parameters on the pulse shape are discussed as well in the range that could be possibly be observed with actual BELA measurement. Finally, examples of WARPE's simulated pulse shapes are used as input in the precise simulation chain of the BELA measurement output, to further assess the capability to detect variation in surface microtexture.

Water ice has a microstructure shaped by a complex interplay of coupled multi-physics processes. Among them, ice sintering—also referred to as metamorphism or annealing—transports material from ice grains into their neck region, resulting in changes in the mechanical and thermal properties of the ice. Understanding sintering is essential to investigate the properties and microstructure of ice. While the sintering process of snow on Earth has been extensively studied, there is a scarce amount of information regarding the alteration of ice in planetary surface environments characterized by low temperatures and pressures.Here we present a multiphysics simulation model designed to study the evolution of planetary ice microstructure. Coupled to a heat transfer solver, we have built a new model for the sintering of ice grain with mathematical refinement to the diffusion process. As changes in ice microstructure affect the thermal properties we have expressed the heat conductivity with a formulation that consider microstructure and porosity which enables a two coupling between sintering and heat transfers.Our simulations of Europa's icy surface spanned a million years, allowing us to thoroughly explore the evolution of ice microstructure. Results show that the hottest regions experience significant sintering, even if high temperatures are only reached during a brief portion of the day. This process takes place on timescales shorter than Europa's ice crust age, suggests that these regions should currently have surface ice composed of interconnected grains. Accurately simulating these highly coupled processes, plays a crucial role in accurately determining the microstructure and quantitative composition of Europa's surface, a key objective for upcoming missions such as JUICE and Europa Clipper.

We present a Monte Carlo Ray tracing model called WARPE (Waveform Analysis and Ray Profiling for Exploration) to study the travel-time in turbid plane-parallel media with possible interaction at interfaces. It is an efficient model with a fast computation time guaranteed by ray batch parallelization. This model has been validated for both spatial and time dimension of the radiative transfer using robust reference models. An application to explore the influence of the radiative parameters has been conducted and reveal that optical depth, single scattering albedo, directionality of the medium, refractive index and extinction coefficient have a crucial role on the time-resolved reflectance. This is illustrated by peak features representing the various back and forth travels of the light in the medium for both diffused and unaffected rays. The top reflection at the first interface and the background scattering are described as well. This model shall be used with inversion method in order to interpret real data to improve the understanding of the microphysics of turbid media with interfaces.

The NASA Galileo spacecraft explored the Jupiter system between 1995 and 2003. The spacecraft was equipped with the Near-Infrared Mapping Spectrometer instrument (NIMS), able to probe Jupiter’s atmosphere and the icy moons’ surface composition in the near-infrared with its 17 detectors operating between 0.7 to 5.2 microns [1]. The Galileo NIMS dataset was collected during flybys, which resulted in a series of very diverse data cubes, viewing geometries and spatial resolutions. In addition, depending on the instrument mode used to collect the data, and on the instrument’s own health status, the NIMS infrared spectra were collected with a varying spectral sampling (between 15 and 408 wavelengths), and an evolving absolute wavelength calibration over the course of the mission. Despite its heterogeneity and complexity of use, the Galileo/NIMS dataset is one of the most valuable resource to model and map the surface properties (composition, grain size, roughness, phase function) of Jupiter’s moons, which are the prime targets of the Europa Clipper [2] and ESA JUICE [3] missions in this decade.We converted the Galileo/NIMS calibrated dataset publicly available on the PDS Imaging Node (as g-cubes) into a MySQL relational database, which allows to quickly select and extract radiance factors (I/F), geometry data, and metadata from the entire NIMS data set. The smallest element in the database is a spectrum (i.e. one pixel). Using SQL queries relying on the pixel viewing geometry (incidence, emission, phase, and azimuth) and the geographic pixel location (latitudes and longitudes on a target), phase curves and/or collections of spectra can be easily retrieved. Individual g-cubes data can also be accessed upon request. We used this database framework, together with Bayesian inversion methods and the Hapke model [4,5], to perform detailed compositional studies on Europa’s dark lineaments [6,7], and spectro-photometric modeling of broader regions of interest located in different hemispheres [8]. References[1] Carlson et al., Space Science Reviews, 60, 457-502, 1992.[2] Howell and Pappalardo, Nat Commun 11, 1311, 2020.[3] Grasset et al., Plan Spac Sci 78, 1-21, 2013.[4] Hapke, Icarus 221, 1079-1083, 2012.[5] Hapke, Cambridge University Press, 1993.[6] Cruz Mermy et al., Icarus 394, 115379, 2023.[7] Andrieu et al., EPSC 2022.[8] Belgacem et al., EPSC, 2022.

The quantitative estimation of volumetric abundance of powder mixture is the basis of quantitative remote sensing analysis. Here we propose to analyze a unique laboratory measurements set, with precise composition, grain size, and volumetric abundance. We first propose a method to estimate the optical constant of materials, knowing the pure endmember spectra and their grain size. Then, we propose a method to transfer the measurement uncertainties to the volumetric abundance, based on the Bayesian approach and the full Hapke radiative transfer model. Using this approach, we are able to estimate grain size, volumetric abundance, and surface roughness. The results show that this approach is able to well estimate the correct volumetric abundance with an uncertainty of 23% and grain size with a ratio uncertainty of 3.0, i.e. uncertainties in log10(grain size)=0.48. The numerical cost of the MCMC is quite large (a few minutes per spectra) but still reasonable to treat a hyperspectral image with the gain of robust handling of non-linearities and propagating uncertainty.

In this article, we study the conditions required to maintain a stable ocean on Mars 3 Ga using a new suite of simulations. These simulations couple a 3D Global Climate Model with ocean dynamics and ice sheet flow. The model includes the main processes of the atmosphere/hydrosphere/cryosphere to investigate Mars' ancient climate. The results show that the total water content required to maintain an ocean is similar to 700m, global equivalent layer, half in the ocean, half in the ice sheet. This number seems plausible if a significant amount of water has been absorbed by the ground. This could be in the form of mineral alteration, or in a deep porous reservoir. In addition, the results show that the equilibrium mass flux from the ice sheet adjacent to the northern ocean is similar to 10(15) kg/y with a very low sliding velocity (1 m/y), except for few warm regions in the lowest altitudes that could reach up to 300 m/y. Finally, the global atmosphere/hydrosphere/cryosphere equilibrium should be reached in a few 100 ky. This indicates that the ocean will have a stabilizing feedback on timescales longer than this. An extensive sensitivity study of the ice sheet was performed. This included the effects of a geothermal heat flux, viscosity and basal drag. Finally, we studied the possible effects of planetary obliquity and a reduced ocean extent.

The surface of Europa experiences a competition between thermally-induced crystallization and radiation-induced amorphization processes, leading to changes of its crystalline structure. The non-linear crystallization and temperature-dependent amorphization rates, incorporating ions, electrons and UV doses, are integrated into our multiphysics surface model (MSM) LunaIcy, enabling simulations of these coupled processes on icy moons.Thirty simulations spanning 100000years, covering the full ranges of albedo and latitude values on Europa, explore the competition between crystallization and irradiation. This is the first modeling of depth-dependent crystallinity profiles on icy moons. The results of our simulations are coherent with existing spectroscopic studies of Europa, both methods showing a primarily amorphous phase at the surface, followed by a crystalline phase after the first millimeter depth. Our method provides quantitative insights into how various parameters found on Europa can influence the subsurface crystallinity profiles.Interpolating upon our simulations, we have generated crystallinity maps of Europa showing highly crystalline ice near the equator, amorphous ice at the poles, and a mix of the two at mid-latitudes. Regions/depths with balanced competition between crystallization and amorphization rates are of high interest due to their periodic fluctuations in crystalline fraction. Our interpolated map reveals periodic variations, with seasonal amplitudes reaching up to 35% of crystalline fraction. These variations could be detected through spectroscopy, and we propose a plan to observe them in forthcoming missions.

Europa's surface is one of the most compelling mysteries of the solar system. It displays complex photometric behavior driven by its rich geology and interaction with the Jovian environment. Cryovolcanism across the surface creates frequent resurfacing, which is competing with external plasma and meteorite bombardment. This study revisits data from Galileo's Near-Infrared Mapping Spectrometer to conduct a comprehensive, multiwavelength photometric analysis of selected regions across Europa's surface. Using a Bayesian inversion framework and the Hapke photometric model, we estimate key surface parameters-including single scattering albedo, macroscopic roughness, and phase function properties-across three geologically diverse regions. Results show a significant link between macroscopic roughness and single scattering albedo, where values of theta will sharply change when the single scattering albedo becomes too high (in this study, we found this transition to happen at omega approximate to 0.8). This is caused by multiple scattering that becomes too significant at a certain brightness and results in the illumination of shadows. This effect is potentially leading to systematic underestimation of roughness in traditional photometric modeling focused on the visible wavelengths. In addition, we observe increasing forward scattering at longer wavelengths, suggesting changes in internal scattering properties or composition. These findings highlight the need to account for albedo-driven photometric behavior in future analyses. This work is important to inform planetary data analysis in general but particularly for the planning of remote-sensing observations of the upcoming missions bound to the Jovian system-NASA's Europa Clipper and ESA's JUICE.

The Planetary Surfaces Data and Services Centre (PDSSP) is a geospatial data and services center dedicated to studies and research on planetary surfaces. This facility brings together several French research partners in planetology and aims to federate French expertise to index and promote map related data, derived data and services/tools for planetary surface data. Mainly, the current services as defined by the CNRS/INSU as National Observation Services are PSUP, SSHADE and VESPAThe PDSSP offers a search portal to help disseminate and use high value-added data for planetary surfaces. This includes spectral data, geological maps, high-resolution images and DEM and other useful information for the scientific community and students interested in planetary studies.The Planetary Surfaces Data and Services Centre also contributes to collaboration and interoperability between different thematic projects in the field of planetary surfaces, by providing tools, services and expertise to facilitate information exchange and collaboration between scientists and researchers.The aim of the Planetary Surfaces Data and Services Centre (PDSSP) is to facilitate access to data and contribute to the creation of products and services by adding value to the space data available. The facility will also serve as a mechanism for the planetary science community to share information and better address the challenges of digital technology. It will be part of the national, European and global landscape, working closely with PSUP (Planetary Surface Portal), VESPA (Virtual European Solar and Planetary Access) and SSHADE (Solid Spectroscopy Hosting Architecture of Databases and Expertise).The PDSSP's mission is to bring together existing facilities to serve the planetary science community. It is based on the establishment of a spatial data infrastructure for planetary surfaces, providing access to its data. It aims to provide added value, particularly in terms of data and services in fields where data centers do not exist or need to be developed, and in terms of links with European and international systems. The aim is to strengthen the planetary science community, in synergy with the other structures in the field, by giving it access to the data it needs for its research, in accordance with the access standards.The STAC-PLANET project is the flagship project of the PDSSP in this first phase. STAC-PLANET is based on the implementation of terrestrial standards (from the Open Geospatial Consortium) to planetary surfaces, giving access to this data and also provides interfaces to the VO (Virtual Observatory) enabling VO clients to query and access data through VO protocols. The centre should neither disorganise nor replace existing centres identified as National Observation Services. It must, in synergy with other structures in the field, strengthen the planetary science community by giving it access to the data it needs for its research in the access standards it uses.The first version of the STAC-PLANET project is planed to be released in the end of 2025.PSUP : http://psup.ias.u-psud.fr/ SSHADE : https://www.sshade.eu/ (see also Erard et al., this meeting EPSC-DPS2025-937)VESPA : https://vespa.obspm.frFig. 1 Scheme of the STAC-PLANET in PDSSP architecture

Europa’s surface is one of the youngest in the solar system. The Jovian moon is believed to hide a global liquid water ocean under its icy crust [1] and is exposed to intense space weathering due to the continuous bombardment by electrons and ions from Jupiter’s magnetosphere [2]. To understand the processes governing the evolution of the surface it is necessary to finely characterize the microphysics of the ice (composition via endmember volume abundance, grain size and surface roughness). However, the majority of the previous studies [3,4] do not allow to constrain precisely these parameters. Here we report the use of a radiative transfer model [5] in a Bayesian MCMC inference framework [6,7] to retrieve microphysical properties of Europa's surface using the Galileo Near-Infrared Mapping Spectrometer (NIMS) hyperspectral data [8]. We present the analysis of a calibrated spectrum of a dark lineament from the trailing Anti-jovian hemisphere. The estimated signal-to-noise ratio (SNR) is between 5 and 50, we mainly focus on the 1.0-2.5 µm region for which the SNR is higher with an uncertainty on the absolute calibration up to 10% [8]. A first work has allowed us to test all combinations of 3, 4 and 5 endmembers from a list of 15 relevant compounds [9]. We were able to test over 5,000 combinations and show that some compounds appear necessary to reproduce the observation, such as water ice and sulfuric acid octahydrate, in agreement with previous studies [3,4,10]. However, adding either hydrated sulfates or chlorine salts produces results substantially similar [9]. Here we present a follow-up study in which we focus on the few acceptable combinations identified by our Bayesian inversions and we analyze the results in terms of grain size and surface roughness. We show that the grain size of the mandatory endmembers is well constrained and similar from one combination to another [11]. The macroscopic roughness is however poorly constrained [11], as expected. Thanks to numerical optimizations we are able to invert independently every spectel of a NIMS hyperspectral cube with the bayesian MCMC algorithm. From this result, we present maps of microphysical properties on an entire hyperspectral image of a dark lineament. References: [1] Pappalardo, R. et al. (1999) JGR. [2] Carlson, R. W. et al. (2005) Icar. [3] Ligier, N. Et al. (2016) The Astr. Jour. [4] King, O. Et al. (2022) PSS. [5] Hapke, B. (2012). Cambridge Univ. Press. [6] Cubillos, P. et al. (2016), The Astr. Jour. [7] Braak, C. J. F. (2008), Stat & Comp. [8] Carlson, R. et al. (1992) ed. C. T. Russell. [9] Cruz-Mermy, G. (2022) Icarus. [10] Mishra, I. et al. (2021) Planet. Sci. [11] Cruz-Mermy, G. (2024) In prep.

The Ganymede Laser Altimeter (GALA) on the Jupiter Icy Moons Explorer (JUICE) mission, is in charge of a comprehensive geodetic mapping of Europa, Ganymede, and Callisto on the basis of Laser range measurements. While multiple topographic profiles will be obtained for Europa and Callisto during flybys, GALA will provide a high-resolution global shape model of Ganymede while in orbit around this moon based on at least 600 million range measurements from altitudes of 500 km and 200 km above the surface. By measuring the diurnal tidal deformation of Ganymede, which crucially depends on the decoupling of the outer ice shell from the deeper interior by a liquid water ocean, GALA will obtain evidence for (or against) a subsurface ocean on Ganymede and will provide constraints on the ice shell thickness above the ocean. In combination with other instruments, it will characterize the morphology of surface units on Ganymede, Europa, and Callisto providing not only topography but also measurements of surface roughness on the scale of the laser footprint, i.e. at a scale of about 50 m from 500 km altitude, and albedo values at the laser wavelength of 1064 nm. GALA is a single-beam laser altimeter, operating at a nominal frequency of 30 Hz, with a capability of reaching up to 48 Hz. It uses a Nd:YAG laser to generate pulses with pulse lengths of 5.5 ± 2.5 ns. The return pulse is detected by an Avalanche Photo Diode (APD) with 100 MHz bandwidth and the signal is digitized at a sampling rate of 200 MHz providing range measurements with a sub-sample resolution of 0.1 m. Research institutes and industrial partners from Germany, Japan, Switzerland and Spain collaborated to build the instrument. JUICE, conducted under responsibility of the European Space Agency (ESA), was successfully launched in April 2023 and is scheduled for arrival at the Jupiter system in July 2031. The nominal science mission including multiple close flybys at Europa, Ganymede, and Callisto, as well as the final Ganymede orbit phase will last from 2031 to 2035. In May 2023 GALA has completed its Near-Earth Commissioning, showing full functionality of all units. Here we summarize the scientific objectives, instrument design and implementation, performance, and operational aspects of GALA.

Ices are widespread across the solar system, present on the surfaces of nearly all planets and moons. Icy moons, in particular, are of high interest due to their potential habitability, as they can harbor liquid water oceans beneath their icy crust making them prime targets for the upcoming JUICE (ESA) and Europa Clipper (NASA) missions. While space observations suggest that these surfaces are made of granular water ice, the fine-scale structure — such as the size, shape, and distribution of ice grains — remains poorly understood. This raises the question: What is the current state of the ice microstructure on these surfaces?Various interdependant surface processes interact over large timescales and together alter the microstructure of the icy surfaces. To adress this, we have developed an innovative multiphysics simulation tool, LunaIcy, which integrates the main physics that affect Europa’s ice microstructure and simulates their interactions. This model has already provided valuable insights into Europa's surface, helping to estimate the thermal dynamics, ice cohesiveness/sintering, and crystallinity.Space observations will greatly benefit from such modeling advancements, which will be essential for a better interpretation of data from the upcoming missions. Multiple other applications for different icy bodies are underway, as we expect that the study of planetary surfaces, much like General Circulation Models for climate science, can greatly benefit from such multiphysical approaches.

Cardinality-constrained sparse spectral unmixing can be solved using Branch-and-Bound algorithms, provided that the number of reference endmembers and the cardinality constraint are reasonably small. However, focusing solely on the best solution may not always be the most relevant approach, especially in the presence of high correlation between endmembers: solutions close to the optimal one-in terms of objective function-but with different supports (activated endmembers) may offer better interpretability. We propose a Branch-and-Bound algorithm that returns a given number of supports which are guaranteed to provide the lowest leastsquares errors among all possible ones. The interest of such an approach is illustrated on numerical simulations, where chances for retrieving the ground truth among the few best solutions are shown to increase compared to considering only the optimal one, especially in the noisiest settings. A Python implementation is made available.

Due to its axial tilt of ~25°, Mars has seasons. During its fall and winter, when temperature drops, there exist two depositional mechanisms of atmospheric CO2, that is, precipitation as snowfall and direct surface condensation in the form of frost (Hayne et al., 2012). Up to one third of the atmospheric CO2 exchanges with the polar surface through the seasonal deposition/sublimation process. Therefore, accurate measurements of the evolution of the seasonal polar caps can place crucial constraints on the Martian climate and volatile cycles. Recently, by reprocessing and co-registering the MOLA profiles, Xiao et al. (2022a, 2022b) derived both spatial and temporal thickness variations of the seasonal polar caps at grid elements of 0.5° in latitude and 10° in longitude. However, the MOLA-derived results can suffer from biases related to various processes, for example, pulse saturation due to high albedo of the seasonal deposits, non-Gaussian return pulses due to rough terrain and dynamic seasonal features, incomplete correction for the global temporal bias, and penetration of the laser pulses into the translucent slab ice. Furthermore, MOLA altimetric observations are limited to Mars Year 24 and 25 which prevents the detection of possible interannual variations in the CO2 seasonal transport. In this contribution, we will show how the shadow variations of fallen ice blocks at the bottom of steep scarps of the North Polar Layered Deposits (NPLDs) allow us to infer the thickness evolution of the seasonal deposits (Xiao et al., 2024). For this, we utilize the High Resolution Imaging Science Experiment (HiRISE/MRO) images with a spatial resolution of up to 0.25 m/pixel (McEwen et al., 2007). We successfully conduct an experiment at a steep scarp centered at (85.0°N, 151.5°E). We assume that no, or negligible, snowfall remains on top of the selected ice blocks, the frost ice layer is homogeneous around the ice blocks and their surroundings, and no significant moating is present. These assumptions enable us to separately determine the thickness of the snowfall and frost. We find that maximum thickness of the seasonal deposits at the study scarp in MY31 is 1.63±0.22 m to which snowfall contributes 0.97±0.13 m. Interestingly, our thickness values in the northern spring are up to 0.8 m lower than the existing MOLA results (Smith et al., 2001; Aharonson et al., 2004; Xiao et al., 2022a, 2022b). We attribute these differences mainly to the remaining biases in the MOLA heights. Furthermore, we demonstrate how the long time span of the HiRISE images (2008—2021; Mars Year 29—36) allows us to measure the interannual variations of the deposited CO2. Specifically, we observe that snowfall in the very early spring of Mars Year 36 is 0.36±0.13 m thicker than that in Mars Year 31. Hayne et al. (2012). JGR: Planets, 117(E8).Xiao et al. (2022a). JGR: Planets, 127(7), e2022JE007196.Xiao et al. (2022b). JGR: Planets, 127(10), e2021JE007158.Xiao et al. (2024). JGR: Planets (In Revision).McEwen et al. (2007). JGR: Planets, 112(E5).Smith et al. (2001). Science, 294(5549), 2141-2146.Aharonson et al. (2004). JGR: Planets, 109(E5).