Mapping planetary surfaces is an intricate task that forms the basis for many geologic, geomorphologic, and geographic studies of planetary bodies. In this work, we present a method to automate a specific type of planetary mapping, geomorphic mapping, taking machine learning as a basis. Additionally, we introduce a novel dataset, termed DoMars16k, which contains 16,150 samples of fifteen different landforms commonly found on the Martian surface. We use a convolutional neural network to establish a relation between Mars Reconnaissance Orbiter Context Camera images and the landforms of the dataset. Afterwards, we employ a sliding-window approach in conjunction with a Markov Random field smoothing to create maps in a weakly supervised fashion. Finally, we provide encouraging results and carry out automated geomorphological analyses of Jezero crater, the Mars2020 landing site, and Oxia Planum, the prospective ExoMars landing site.

We present a combined reflectance and thermal radiance model for airless planetary bodies. The Hapke model provides the reflected component. The developed thermal model is the first to consistently use rough fractal surfaces, self-scattering, self-heating, and disk-resolved bolometric albedo for entire planets. We validated the model with disk-resolved lunar measurements acquired by the Chinese weather satellite Gaofen-4 at around 3.5–4.1 μm and measurements of the Diviner lunar radiometer at 8.25 μm and 25–41 μm, finding nearly exact agreement. Further, we reprocessed the thermal correction of the global lunar reflectance maps obtained by the Moon Mineralogy Mapper M³and employed the new model to correct excess thermal radiance. The results confirm the diurnal, latitudinal, and compositional variations of lunar hydration reported in previous and recent studies with other instruments. Further, we compared the model to lunar measurements obtained by the Mercury Radiometer and Thermal Infrared Spectrometer (MERTIS) on board BepiColombo during a flyby maneuver on April 9, 2020: the measured and the modeled radiance variations across the disk match. Finally, we adapted the thermal model to Mercury for emissivity calibration of upcoming Mercury flyby measurements and in-orbit operation. Although a physical parameter must be invariant under various observation scenarios, the best lunar surface roughness fits vary between different datasets. We critically discuss possible reasons and conclude that anisotropic emissivity modeling has room for improvement and requires attention in future studies.

Determining which rocky exoplanets have atmospheres, and why, is a key goal for the James Webb Space Telescope. So far, emission observations of individual rocky exoplanets orbiting M stars (M-Earths) have not provided definitive evidence for atmospheres. Here, we synthesize emission data for M-Earths and find a trend in measured brightness temperatures (ratioed to its theoretical maximum value) as a function of instellation. However, the statistical evidence of this trend is dependent on the choice of stellar model, and we consider its identification tentative. We show that this trend can be explained by either the onset of thin/tenuous (<1 bar) CO₂-rich atmospheres on colder worlds, or a population of bare rocks with stronger space weathering and/or coarser regolith on closer-in worlds. Such grain coarsening may be caused by sintering near the melting point of rock or frequent volcanic resurfacing. Furthermore, we highlight considerations when testing rocky planet hypotheses at the population level, including the choice of instrument, stellar modeling, and how brightness temperatures are derived. We also find that fresh (unweathered) fine-grained surfaces can serve as a false positive to the detection of moderate atmospheric heat redistribution through eclipse observations. However, we argue that such surfaces are unlikely given the ubiquity of space weathering in the solar system, the low albedo of solar system airless bodies, and the high stellar wind environments of M-Earths. Emission data from a larger sample of M-Earths will be able to confirm or reject this tentative trend and diagnose its cause through spectral characterization.

We refined our Shape from Shading (SfS) algorithm, which has previously been used to create digital terrain models (DTMs) of the Lunar and Martian surfaces, to generate high-resolution DTMs of Mercury from MESSENGER imagery. To adapt the reconstruction procedure to the specific conditions of Mercury and the available imagery, we introduced two methodic innovations. First, we extended the SfS algorithm to enable the 3D-reconstruction from image mosaics. Because most mosaic tiles were acquired at different times and under various illumination conditions, the brightness of adjacent tiles may vary. Brightness variations that are not fully captured by the reflectance model may yield discontinuities at tile borders. We found that the relaxation of the constraint for a continuous albedo map improves the topographic results of an extensive region removing discontinuities at tile borders. The second innovation enables the generation of accurate DTMs from images with substantial albedo variations, such as hollows. We employed an iterative procedure that initializes the SfS algorithm with the albedo map that was obtained by the previous iteration step. This approach converges and yields a reasonable albedo map and topography. With these approaches, we generated DTMs of several science targets such as the Rachmaninoff basin, Praxiteles crater, fault lines, and several hollows. To evaluate the results, we compared our DTMs with stereo DTMs and laser altimeter data. In contrast to coarse laser altimetry tracks and stereo algorithms, which tend to be affected by interpolation artifacts, SfS can generate DTMs almost at image resolution. The root mean squared errors (RMSE) at our target sites are below the size of the horizontal image resolution. For some targets, we could achieve an effective resolution of less than 10 m/pixel, which is the best resolution of Mercury to date. We critically discuss the limitations of the evaluation methodology.

Digital Elevation Models (DEMs) of planet Mars are crucial for many remote sensing applications and for landing site characterization of rover missions. Shape from Shading (SfS) is known to work well as a complementary method to greatly enhance the quality of photogrammetrically obtained DEMs of planetary surfaces with respect to the effective resolution and the overall accuracy. In this work, we extend our previous lunar shape and albedo from shading framework by embedding the Hapke photometric reflectance model in an atmospheric model such that it is applicable to Mars. Compared to previous approaches, the proposed method is capable of directly estimating the atmospheric parameters from a given scene without the need for external data, and assumes a spatially varying albedo. The DEMs are generated from imagery of the Context Camera (CTX) onboard the Mars Reconnaissance Orbiter (MRO) and are validated for clear and opaque atmospheric conditions. We analyze the necessity of using atmospheric compensation depending on the atmospheric conditions. For low optical depths, the Hapke model without an atmospheric component is still applicable to the Martian surface. For higher optical depths, atmospheric compensation is required to obtain good quality DEMs.

Lunar OH/H₂O has been confirmed and mapped by analyzing the 3 μm absorption band in spectra acquired by the Moon Mineralogy Mapper (M³) instrument. Space weathering leads to accumulation of submicroscopic iron particles in the uppermost layer of the regolith which gradually changes the spectral signature of airless planetary bodies and thus may affect the detection of lunar OH/H₂O. The contribution of this paper is twofold. (1) Our new technique combines Hapke reflectance modeling and ab initio Mie scattering calculations to model the scattering behavior of submicroscopic iron which governs the optical effects due to space weathering. (2) Thermally corrected M³ spectra of mature and immature sample points in mare and highland regions are used to assess the performance of the simulation framework and are analyzed to understand maturity-related changes of the OH/H₂O band depth. We find that the simulation method can convincingly reproduce the spectral changes of maturing lunar soil. It becomes clear that there is only a minor effect on the 3 μm absorption feature. This finding makes the analysis of the lunar OH/H₂O mapping largely invariant with respect to space weathering. In general, the absorption features around 1 and 2 μm are more strongly obstructed than the feature around 3 μm. Further, we discuss agglutination as the main cause for slight deviations found around the 2 μm band and layering/clustering as a likely reason to explain predicted iron particle sizes that are larger than observed.