Quantifying Sub-Meter Surface Heterogeneity on Mars Using Off-Axis Thermal Emission Imaging System (THEMIS) Data

Surface heterogeneities below the spatial resolution of thermal infrared (TIR) instruments result in anisothermality and can produce emissivity spectra with negative slopes toward longer wavelengths. Sloped spectra arise from an incorrect assumption of either a uniform surface temperature or a maximum emissivity during the temperature-emissivity separation of radiance data. Surface roughness and lateral mixing of different sub-pixel surface units result in distinct spectral slopes with magnitudes proportional to the degree of temperature mixing. Routine Off-nadir Targeted Observations (ROTO) of the Thermal Emission Imaging Spectrometer (THEMIS) are used here for the first time to investigate anisothermality below the spatial resolution of THEMIS. The southern flank of Apollinaris Mons and regions within the Medusae Fossae Formation are studied using THEMIS ROTO data acquired just after local sunset. We observe a range of sloped TIR emission spectra dependent on the magnitude of temperature differences within a THEMIS pixel. Spectral slopes and wavelength-dependent brightness temperature differences are forward-modeled for a series of two-component surfaces of varying thermal inertia values. Our results imply that differing relative proportions of rocky and unconsolidated surface units are observed at each ROTO viewing geometry and suggest a local rock abundance six times greater than published results that rely on nadir data. High-resolution visible images of these regions indicate a mixture of surface units from boulders to dunes, providing credence to the model.

Squeezing Data from a Rock: Machine Learning for Martian Science

Data analysis methods have scarcely kept pace with the rapid increase in Earth observations, spurring the development of novel algorithms, storage methods, and computational techniques. For scientists interested in Mars, the problem is always the same: there is simultaneously never enough of the right data and an overwhelming amount of data in total. Finding sufficient data needles in a haystack to test a hypothesis requires hours of manual data screening, and more needles and hay are added constantly. To date, the vast majority of Martian research has been focused on either one-off local/regional studies or on hugely time-consuming manual global studies. Machine learning in its numerous forms can be helpful for future such work. Machine learning has the potential to help map and classify a large variety of both features and properties on the surface of Mars and to aid in the planning and execution of future missions. Here, we outline the current extent of machine learning as applied to Mars, summarize why machine learning should be an important tool for planetary geomorphology in particular, and suggest numerous research avenues and funding priorities for future efforts. We conclude that: (1) moving toward methods that require less human input (i.e., self- or semi-supervised) is an important paradigm shift for Martian applications, (2) new robust methods using generative adversarial networks to generate synthetic high-resolution digital terrain models represent an exciting new avenue for Martian geomorphologists, (3) more effort and money must be directed toward developing standardized datasets and benchmark tests, and (4) the community needs a large-scale, generalized, and programmatically accessible geographic information system (GIS).

Finding Order in Chaos: Quantitative Predictors of Chaos Terrain Morphology on Europa

The mechanisms for chaos terrain formation on Europa have long been a source of debate in the scientific community. There exist numerous theoretical and numerical models for chaos formation, but to date there has been a lack of quantifiable observations that can be used to constrain models and permit comparison to the outputs of these chaos models. Here, we use mapping and statistical analysis to develop a quantitative description of chaos terrain and their observed morphologies. For nine chaos features, we map every block, or region of pre-existing terrain within disrupted matrix. We demonstrate that chaos terrains follow a continuous spectrum of morphologies between two endmembers, platy and knobby. We find that any given chaos terrain's morphology can be quantified by means of the linearized exponential slope of its cumulative block area distribution. This quantitative metric provides a new diagnostic parameter in future studies of chaos terrain formation and comparison.

Soil Thermophysical Properties Near the InSight Lander Derived From 50 Sols of Radiometer Measurements

Measurements from the InSight lander radiometer acquired after landing are used to characterize the thermophysical properties of the Martian soil in Homestead hollow. This data set is unique as it stems from a high measurement cadence fixed platform studying a simple well-characterized surface, and it benefits from the environmental characterization provided by other instruments. We focus on observations acquired before the arrival of a regional dust storm (near Sol 50), on the furthest observed patch of soil (i.e., ∼3.5 m away from the edge of the lander deck) where temperatures are least impacted by the presence of the lander and where the soil has been least disrupted during landing. Diurnal temperature cycles are fit using a homogenous soil configuration with a thermal inertia of 183 ± 25 J m^-2 K^-1 s^-1/2 and an albedo of 0.16, corresponding to very fine to fine sand with the vast majority of particles smaller than 140 μm. A pre-landing assessment leveraging orbital thermal infrared data is consistent with these results, but our analysis of the full diurnal temperature cycle acquired from the ground further indicates that near surface layers with different thermophysical properties must be thin (i.e., typically within the top few mm) and deep layering with different thermophysical properties must be at least below ∼4 cm. The low thermal inertia value indicates limited soil cementation within the upper one or two skin depths (i.e., ∼4-8 cm and more), with cement volumes <<1%, which is challenging to reconcile with visible images of overhangs in pits.

Particle Size-Frequency Distributions of the OSIRIS-REx Candidate Sample Sites on Asteroid (101955) Bennu

We manually mapped particles ranging in longest axis from 0.3 cm to 95 m on (101955) Bennu for the Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) asteroid sample return mission. This enabled the mission to identify candidate sample collection sites and shed light on the processes that have shaped the surface of this rubble-pile asteroid. Building on a global survey of particles, we used higher-resolution data from regional observations to calculate particle size-frequency distributions (PSFDs) and assess the viability of four candidate sites for sample collection (presence of unobstructed particles ≤ 2 cm). The four candidate sites have common characteristics: each is situated within a crater with a relative abundance of sampleable material. Their PSFDs, however, indicate that each site has experienced different geologic processing. The PSFD power-law slopes range from −3.0 ± 0.2 to −2.3 ± 0.1 across the four sites, based on images with a 0.01-m pixel scale. These values are consistent with, or shallower than, the global survey measurements. At one site, Osprey, the particle packing density appears to reach geometric saturation. We evaluate the uncertainty in these measurements and discuss their implications for other remotely sensed and mapped particles, and their importance to OSIRIS-REx sampling operations.

PlaNet: A Neural Network for Detecting Transverse Aeolian Ridges on Mars

Transverse aeolian ridges (TARs) are unusual bedforms on the surface of Mars. TARs are common but sparse on Mars; TAR fields are small, rarely continuous, and scattered, making manual mapping impractical. There have been many efforts to automatically classify the Martian surface, but they have never explicitly located TARs successfully. Here, we present a simple adaptation of the off-the-shelf neural network RetinaNet that is designed to identify the presence of TARs at a 50-m scale. Once trained, the network was able to identify TARs with high precision (92.9%). Our model also shows promising results for applications to other surficial features like ripples and polygonal terrain. In the future, we hope to apply this model more broadly and generate a large database of TAR distributions on Mars.

Assessment of InSight Landing Site Predictions

Comprehensive analysis of remote sensing data used to select the Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) landing site correctly predicted the atmospheric temperature and pressure profile during entry and descent, the safe landing surface, and the geologic setting of the site. The smooth plains upon which the InSight landing site is located were accurately predicted to be generally similar to the Mars Exploration Rover Spirit landing site with relatively low rock abundance, low slopes, and a moderately dusty surface with a 3-10 m impact fragmented regolith over Hesperian to Early Amazonian basaltic lava flows. The deceleration profile and surface pressure encountered by the spacecraft during entry, descent, and landing compared well (within 1σ) of the envelope of modeled temperature profiles and the expected surface pressure. Orbital estimates of thermal inertia are similar to surface radiometer measurements, and materials at the surface are dominated by poorly consolidated sand as expected. Thin coatings of bright atmospheric dust on the surface were as indicated by orbital albedo and dust cover index measurements. Orbital estimates of rock abundance from shadow measurements in high-resolution images and thermal differencing indicated very low rock abundance and surface counts show 1-4% area covered by rocks. Slopes at 100 to 5 m length scale measured from orbital topographic and radar data correctly indicated a surface comparably smooth and flat as the two smoothest landing sites (Opportunity and Phoenix). Thermal inertia and radar data indicated the surface would be load bearing as found.

Field trial of a dual-wavelength fluorescent emission (L.I.F.E.) instrument and the Magma White rover during the MARS2013 Mars analog mission

Abstract We have developed a portable dual-wavelength laser fluorescence spectrometer as part of a multi-instrument optical probe to characterize mineral, organic, and microbial species in extreme environments. Operating at 405 and 532 nm, the instrument was originally designed for use by human explorers to produce a laser-induced fluorescence emission (L.I.F.E.) spectral database of the mineral and organic molecules found in the microbial communities of Earth's cryosphere. Recently, our team had the opportunity to explore the strengths and limitations of the instrument when it was deployed on a remote-controlled Mars analog rover. In February 2013, the instrument was deployed on board the Magma White rover platform during the MARS2013 Mars analog field mission in the Kess Kess formation near Erfoud, Morocco. During these tests, we followed tele-science work flows pertinent to Mars surface missions in a simulated spaceflight environment. We report on the L.I.F.E. instrument setup, data processing, and performance during field trials. A pilot postmission laboratory analysis determined that rock samples acquired during the field mission exhibited a fluorescence signal from the Sun-exposed side characteristic of chlorophyll a following excitation at 405 nm. A weak fluorescence response to excitation at 532 nm may have originated from another microbial photosynthetic pigment, phycoerythrin, but final assignment awaits development of a comprehensive database of mineral and organic fluorescence spectra. No chlorophyll fluorescence signal was detected from the shaded underside of the samples.

Midlatitude ice-rich ground on mars as a target in the search for evidence of life and for in situ resource utilization on human missions

Midlatitude ground ice on Mars is of significant scientific interest for understanding the history and evolution of ice stability on Mars and is relevant for human exploration as a possible in situ resource. For both science and exploration, assessing the astrobiological potential of the ice is important in terms of (1) understanding the potential for life on Mars and (2) evaluating the presence of possible biohazards in advance of human exploration. In the present study, we review the evidence for midlatitude ground ice on Mars, discuss the possible explanations for its occurrence, and assess its potential habitability. During the course of study, we systematically analyzed remote-sensing data sets to determine whether a viable landing site exists in the northern midlatitudes to enable a robotic mission that conducts in situ characterization and searches for evidence of life in the ice. We classified each site according to (1) presence of polygons as a proxy for subsurface ice, (2) presence and abundance of rough topographic obstacles (e.g., large cracks, cliffs, uneven topography), (3) rock density, (4) presence and abundance of large boulders, and (5) presence of craters. We found that a suitable landing site exists within Amazonis Planitia near ground ice that was recently excavated by a meteorite impact.