Assessment of InSight Landing Site Predictions

In Situ Regolith Seismic Velocity Measurement at the InSight Landing Site on Mars

Interior exploration using Seismic Investigations, Geodesy and Heat Transport's (InSight) seismometer package Seismic Experiment for Interior Structure (SEIS) was placed on the surface of Mars at about 1.2 m distance from the thermal properties instrument Heat flow and Physical Properties Package (HP³) that includes a self-hammering probe. Recording the hammering noise with SEIS provided a unique opportunity to estimate the seismic wave velocities of the shallow regolith at the landing site. However, the value of studying the seismic signals of the hammering was only realized after critical hardware decisions were already taken. Furthermore, the design and nominal operation of both SEIS and HP³ are nonideal for such high-resolution seismic measurements. Therefore, a series of adaptations had to be implemented to operate the self-hammering probe as a controlled seismic source and SEIS as a high-frequency seismic receiver including the design of a high-precision timing and an innovative high-frequency sampling workflow. By interpreting the first-arriving seismic waves as a P-wave and identifying first-arriving S-waves by polarization analysis, we determined effective P- and S-wave velocities of v P = 11 9 - 21 + 45  m/s and v S = 6 3 - 7 + 11  m/s, respectively, from around 2,000 hammer stroke recordings. These velocities likely represent bulk estimates for the uppermost several 10s of cm of regolith. An analysis of the P-wave incidence angles provided an independent v _P /v _S ratio estimate of 1.8 4 - 0.35 + 0.89 that compares well with the traveltime based estimate of 1.8 6 - 0.25 + 0.42 . The low seismic velocities are consistent with those observed for low-density unconsolidated sands and are in agreement with estimates obtained by other methods.

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).

The dynamic atmospheric and aeolian environment of Jezero crater, Mars

Despite the importance of sand and dust to Mars geomorphology, weather, and exploration, the processes that move sand and that raise dust to maintain Mars' ubiquitous dust haze and to produce dust storms have not been well quantified in situ, with missions lacking either the necessary sensors or a sufficiently active aeolian environment. Perseverance rover's novel environmental sensors and Jezero crater's dusty environment remedy this. In Perseverance's first 216 sols, four convective vortices raised dust locally, while, on average, four passed the rover daily, over 25% of which were significantly dusty ("dust devils"). More rarely, dust lifting by nonvortex wind gusts was produced by daytime convection cells advected over the crater by strong regional daytime upslope winds, which also control aeolian surface features. One such event covered 10 times more area than the largest dust devil, suggesting that dust devils and wind gusts could raise equal amounts of dust under nonstorm conditions.

The shallow structure of Mars at the InSight landing site from inversion of ambient vibrations

Orbital and surface observations can shed light on the internal structure of Mars. NASA’s InSight mission allows mapping the shallow subsurface of Elysium Planitia using seismic data. In this work, we apply a classical seismological technique of inverting Rayleigh wave ellipticity curves extracted from ambient seismic vibrations to resolve, for the first time on Mars, the shallow subsurface to around 200 m depth. While our seismic velocity model is largely consistent with the expected layered subsurface consisting of a thin regolith layer above stacks of lava flows, we find a seismic low-velocity zone at about 30 to 75 m depth that we interpret as a sedimentary layer sandwiched somewhere within the underlying Hesperian and Amazonian aged basalt layers. A prominent amplitude peak observed in the seismic data at 2.4 Hz is interpreted as an Airy phase related to surface wave energy trapped in this local low-velocity channel.

We invert Rayleigh wave ellipticity curves extracted from ambient seismic vibrations at the InSight landing site to resolve, for the first time on Mars, the shallow subsurface to around 200 m depth. While our seismic velocity model is largely consistent with the expected stacks of lava flows, we find a seismic low velocity zone at about 30 to 75 m depth that we interpret as a sedimentary layer sandwiched between layers of basalt flows.

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.

Location and Setting of the Mars InSight Lander, Instruments, and Landing Site

Knowing precisely where a spacecraft lands on Mars is important for understanding the regional and local context, setting, and the offset between the inertial and cartographic frames. For the InSight spacecraft, the payload of geophysical and environmental sensors also particularly benefits from knowing exactly where the instruments are located. A ~30 cm/pixel image acquired from orbit after landing clearly resolves the lander and the large circular solar panels. This image was carefully georeferenced to a hierarchically generated and coregistered set of decreasing resolution orthoimages and digital elevation models to the established positive east, planetocentric coordinate system. The lander is located at 4.502384°N, 135.623447°E at an elevation of -2,613.426 m with respect to the geoid in Elysium Planitia. Instrument locations (and the magnetometer orientation) are derived by transforming from Instrument Deployment Arm, spacecraft mechanical, and site frames into the cartographic frame. A viewshed created from 1.5 m above the lander and the high-resolution orbital digital elevation model shows the lander is on a shallow regional slope down to the east that reveals crater rims on the east horizon ~400 m and 2.4 km away. A slope up to the north limits the horizon to about 50 m away where three rocks and an eolian bedform are visible on the rim of a degraded crater rim. Azimuths to rocks and craters identified in both surface panoramas and high-resolution orbital images reveal that north in the site frame and the cartographic frame are the same (within 1°).