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).

Mars's atmosphere has theoretically been predicted to be strong enough to continuously excite Mars's background-free oscillations, potentially providing an independent means of verifying radial seismic body-wave models of Mars determined from marsquakes and meteorite impacts recorded during the Interior Exploration using Seismic Investigations, Geodesy, and Heat Transport (InSight) mission. To extract the background-free oscillations, we processed and analyzed the continuous seismic data, consisting of 966 Sols (a Sol is equivalent to a Martian day), collected by the Mars InSight mission using both automated and manual deglitching schemes to remove nonseismic disturbances. We then computed 1-Sol-long autocorrelations for the entire data set and stacked these to enhance any normal-mode peaks present in the spectrum. We find that while peaks in the stacked spectrum in the 2-4 mHz frequency band align with predictions based on seismic body-wave models and appear to be consistent across the different processing and stacking methods applied, unambiguous detection of atmosphere-induced free oscillations in the Martian seismic data nevertheless remains difficult. This possibly relates to the limited number of Sols of data that stack coherently and the continued presence of glitch-related signal that affects the seismic data across the normal-mode frequency range (similar to 1-10 mHz). Improved deglitching schemes may allow for clearer detection and identification in the future.

Mapping landforms on the Moon is of great interest and importance for future human settlements and resources exploration. One of the first steps is to map the topography in great detail and resolution. However, data from the Lunar Orbiter Laser Altimeter (LOLA) provide low-resolution elevation maps in comparison to the size of detailed geological features. To improve resolution, we developed a new method to upscale topographic maps to a higher resolution using images from the Lunar Reconnaissance Orbiter Camera (LROC). Our method exploits the relation between topographic gradients and degrees of shading of incoming sunlight. In contrast to earlier published methods, our approach is based on probabilistic, linear inverse theory, and its computational efficiency is very high due to its formulation through the Sylvester Equation. The method operates on multiple images and incorporates albedo variations. A further advantage of the method is that we avoid/reduce the use of arbitrary tuning parameters through a probabilistic formulation where all weighting of data and model parameters is based on prior information about data uncertainties and reasonable bounds on the model. Our results increase the resolution of the topography from -60 m per pixel to 0.9 m per pixel, bringing it to the same pixel resolution as the optical images from LROC, allowing in some cases detection of craters as small as -3 m of diameter. We estimate uncertainties of the topographic model due to noise in the images, and in the low-resolution (LOLA) model.

Inversion of seismic data using information from horizontal wells is often hampered by cumulative well‐location errors. These errors can have a significant influence on the final subsurface model derived from the data. To achieve a proper data integration and arrive at correct uncertainty estimates, we formulate the problem in a fully probabilistic framework and present a numerical approach for improving subsurface imaging using uncertain well‐log data and their uncertain locations as well as uncertain seismic data. The result is improved model error quantification in the seismic inversion process.

Mapping landforms on the Moon is of great interest and importance for future human settlements and resources exploration.One of the first steps is to map the topography and investigate their shape and geometry in great detail and resolution, which would provide the first conditions for assessing their suitability for future on-site analysis.However, data from the Lunar Orbiter Laser Altimeter (LOLA) provide low resolution elevation maps in comparison to the size of detailed geological features.To improve resolution, we developed an inverse method to upscale topographic maps to a higher resolution using photographic data from the Lunar Reconnaissance Orbiter Camera (LROC).The method, which exploits the relation between topographic gradients and degrees of shading of incoming sunlight, shows an improvement from ˜60 metres per pixel to 0.9 metres per pixel, bringing it to the same resolution as the optical images from LROC.Our method can detect craters as small as ˜3 metres of diameter and, if illumination from several angles are available, is potentially a way to remove shades from complex features such as caves.It is also possible to estimate the error of the model due to uncertainties in the albedo.

Earth and Space Science Open Archive This is a preprint and has not been peer reviewed. ESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary.Learn more about preprints preprintOpen AccessYou are viewing the latest version by default [v1]3D Probabilistic Well-log Analysis With Uncertain Location DataAuthorsIrisFernandesKlausMosegaardiDSee all authors Iris FernandesCorresponding Author• Submitting AuthorNiels Bohr institute - University of Copenhagenview email addressThe email was not providedcopy email addressKlaus MosegaardiDNiels Bohr Institute - University of CopenhageniDhttps://orcid.org/0000-0001-5292-5249view email addressThe email was not providedcopy email address

Mapping landforms on the Moon is of great interest and importance for future human settlements and resources exploration. One of the first steps is to map the topography and investigate their shape...

Summary In order to perform seismic inversion and have information about the subsurface, horizontal well-log data is normally used as constraints. These data contain very detailed information on a short scale. However, since the next step in the geo-steering of a borehole always depends on the previous one, the location errors accumulate and, as the drilling acquisition goes further and deeper, the uncertainty of the position and hence the borehole measurements also grows. To image the subsurface and estimate the errors involved in the data analysis process, we perform seismic inversion combining different sources of uncertain measurements, such as uncertain seismic data as well as uncertain well positions and well-log data. This paper presents a new method to incorporate these different sources of uncertainties and on different scales. We simulated various realizations of the subsurface and, taking into account the growing uncertain position of the well location, we could observe the variability that the errors create. As a result, the computed subsurface model and its error estimates are more realistic, and can better guide and optimise future drilling operations.

To improve seismic inversion, we propose to use prior information from empirical estimates of spatial rock property distributions obtained from outcrop training images. Using photographic images of chalk outcrops, we derive empirical distributions of spatial rock property gradients and estimates of spatial correlations. We use this information as a priori information in probabilistic, seismic inversion. Our results are realistic, high-resolution posterior samples of subsurface models, whose variability can be used as an estimate of model uncertainties. Presentation Date: Wednesday, October 17, 2018 Start Time: 8:30:00 AM Location: 206A (Anaheim Convention Center) Presentation Type: Oral

We present here a series of Ground Penetrating Radar (GPR) survey carried out in different areas of the Dardanelos 1 archaeological site in order to generate information about subsurface anomalies associated with archaeological material that could be use in decision making within the environmental licensing process of the Dardanelos Hydroelectric Power Plant, located near of the Aripuan? city, Mato Grosso State, northwest region of Brazil. GPR surveys with 200 MHz antenna were carried out in two blocks aiming to locate archaeological resources and features. The analysis of GPR 2D and 3D results allowed detecting anomalous regions characterized by hyperbolic reflections, shallow elongated continuous targets with high amplitudes, as well as sub-horizontal reflectors. Microwave tomography allowed estimating the geometry of the GPR anomalies sources. Excavations were done by archaeologists at the locations where hyperbolic anomalies were found, revealing interesting structures related to urns in the middle of a rich in organic matter consisting of black and ceramic materials up to about 1 m deep. The first sub-horizontal reflector at approximately 1 m depth is related to the base of the black soil layer rich in organic matter and the second sub-horizontal reflector between 2 and 3 m deep suggests a lithological change or may be related to presence of the water table. The continuous elongated shallow targets observed in the depth slices are related to tree roots in the middle of the archaeological strata. The GPR results guided archaeological excavations, reduced the time and costs involved in research, and contributed to the preservation of Brazilian historical heritage.