In the end of November 2018 the InSight mission landed on the Martian surface deploying a six axis broadband and short period seismometer, in order record marsquakes and ambient noise, which can be used to constrain the deeper interior structures of the planet. In this study we process the three components of the broad band seismometer and apply autocorrelation methods to more than a year of ambient noise data and to 250 selected marsquake waveforms, to retrieve the empirical Greens functions (EGFs), that are related to the subsurface impedance discontinuities below the lander. The most prominent impedance discontinuity is commonly represented by the crust-mantle boundary (Moho), which yet needs to be confirmed on Mars. A lot of care is taken to attenuate the spurious signals and the wind induced lander resonance, that contaminate the data, before the autocorrelation analysis. We further apply attribute filtering and reject data windows that exceed wind speed thresholds or reveal too large amplitudes at later lags, which are often related to residuals of artefacts or lander resonance. To further improve the signal to noise ratio of the EGFs we apply phase-weighted stacking. We observe a good agreement in the autocorrelograms of the ambient noise and the marsquakes and determine several stable arrivals on the vertical component, in particular at 10.8 and 12.7 s, that we interpret as trapped P-waves, which are reflected between the surface and the potential Moho or other layer interfaces. Using available velocity constraints we convert the arrival times to possible Moho depths of 19-28 and 22-33 km, respectively. In addition, we find that large part of the seismic energy during the quiet night period of Mars is related to the 2.4 Hz mode and that removing it from the autocorrelations the distinct arrivals can no longer be identified.

Over the last decade, Distributed Acoustic Sensing (DAS) has gained increased attention as a cost-effective and practical ground motion monitoring technique, due to the unprecedented temporal and spatial sampling possibilities. Considering these inherent advantages, DAS-collected strain rate measurements can be beneficial as addition to traditional particle motion sensors, or potentially replace them under certain circumstances. A DAS system, consisting of an interrogator and attached optical fiber, is conventionally employed in a single (inline) direction providing 1D longitudinal strain rate measurements along the installed fiber. In this thesis, we explore unconventional fiber configurations to retrieve additional wavefield components. To investigate the potential of these unconventional fiber geometries, we perform numerical tests, discuss real data from a field campaign in Yverdon (Switzerland) and report on our analysis of synthetic and field data. Both synthetic and field results show that a loop- and cross fiber lay-out provide thepseudo-divergence, defined as the sum of the local spatial velocity gradients (∂xvx+∂yvy), which is proportional to the full wavefield divergence at the free surface. We confirm that the fiber loop & cross shape predominantly capture Rayleigh surface waves, but are insensitive to Love wave energy. An important factor regarding the loop & cross behaviour is the configuration size with respect to the wavelength (λ). Reduced amplitudes are recognizable for loop & cross dimensions spanning more than 1/5λ, followed by additional phase distortions from 1/3λ and completely altered waveforms for even larger loop & cross sizes.We show that a spherical configuration (composed of 3 independent orthogonal fiberloops) is theoretically attractive by enabling the retrieval of both the full divergence and the individual spatial gradients in the three orthogonal directions. The free surface-relation between the pseudo- and full divergence can be exploited to approximate the local ratio of the shear and pressure wave velocity (VS/VP ), which is demonstrated with synthetic data by means of spectral element modeling. However, the field results are less convincing due to, supposedly, poor cable-ground coupling as a result of required dense cable winding.Finally, we introduce a local approach to estimate the effective shear velocity (VS) without the need for larger arrays. We achieve this by combining local gradients and particle acceleration data, obtained from the fiber loop and one centred 3C-geophone respectively. Our novel approach is validated with synthetic data and we present promising field data results. The proposed 4C-configuration mitigates traditional finite-difference errors related to tilted or inaccurately spaced ground motion sensors. Furthermore, our novel arrangement offers the advantage of azimuthal independence, which can be of interest for VS-estimations from earthquake-, traffic- or potentially ambient noise recordings. The local character of the effective VS-computation is dependent on the incident P-wavelength and is therefore potentially exploitable with regard to 1D shear velocity subsurface models.The presented synthetic and field results in this thesis show the potential of employing unconventional fiber configurations with regard to multi-component gradient sensing. This work further contributes to the development of attractive DAS applications at various scales, especially related to wavefield separation (ground-roll suppression), shallow static corrections and near-surface characterization.

In the summer of 2020, ETH researchers installed a 9 km long fiber-optic cable on the Rhonegletscher (Switzerland), covering the whole glacier extent from accumulation to ablation zone. The fiber was then interrogated with a DAS system, turning it into a distributed seismic antenna. The DAS system recorded continuously for one month on more than 2000 channels at 1 kHz sampling rate. The large data volume (~18 TB) renders manual event picking and categorization practically unfeasible. For such DAS monitoring experiments, automatic event detection and classification might become indispensable. Different types of icequakes and meteorological effects are visible on the raw strain-rate recordings. Most cryoseismic events (stick-slip icequakes and surface crevassing) are of short-time duration and small spatial extent. Since most events are only visible on fractions of the array, the data is divided into smaller sub-windows in time and space. Different array processing techniques are discussed to obtain a low-dimensional feature representation of each sub-window. The output from the array processing is used as input for an unsupervised clustering algorithm assigning a class-membership to each sub-window. This is applied to parts of the Rhonegletscher dataset. Meaningful clusters are returned that corre- spond to seismic events or noise. The analysis yields a preliminary overview of signal types contained in the Rhonegletscher dataset and their spatio-temporal distribution. This method can be used to obtain an event catalogue of clustered signals. This could be used as basis for further analyses such as seismic imaging, template matching or supervised machine learning.

On the 25th of November 2018, NASA’s InSight Mars-lander landed at Elysium Planitia on Mars (NASA, 2022a). The lander includes the SEIS instrument, which measures the seismic signals on the planet (NASA, 2022b). Because seismic waves are altered by the medium they travel through from the source to the receiver, they contain information on the interior structure of the planet. This information about the structure of Mars can be extracted by applying different data processing and evaluation techniques. One of the proposed methods is the polarization analysis of the first-arriving P-wave, which is expected to contain information about the near-surface S-wave velocity structure. The technique uses the polarization of an incoming P-wave in horizontal and radial direction to estimate the apparent P-wave incidence angle (Knapmeyer-Endrun et al., 2018). The measured P-wave incidence angle can further be used to estimate a frequency-dependent S-wave velocity from the first break, given that the ray parameter is known. An inversion of such frequency-dependent S-wave velocity curves can then potentially lead to velocity-depth profiles of the near-surface zone. A first pre-testing of the polarization analysis on a synthetic model should help to understand the process of frequency-dependent S-wave velocity extraction and to work out the limitations of the method. The synthetic data testing showed, that there are a range of important parameters, which influence the velocity estimation. It is highly frequency-dependent and later arrivals, as well as noise, can affect the accuracy. One of the indicators that can be used to evaluate whether or not the extracted S-wave velocities can be trusted is the ellipticity of the polarized wave, which should not be above a threshold of 0.2. The time delay between the Pand the mode-converted PS-arrival (defined as ∆t_app) could be used to define the areas where the estimated velocities change from their expected value. It was found, that ∆tapp has to be greater than 1.4×1e-4 - 2×1e-4 s, that a velocity estimation of the first layer is possible. This is valid for frequencies between 0.08 Hz up to 6 Hz. The second layer velocity could only be calculated for frequencies lower than 0.6 - 2 Hz for the tested models. Furthermore, a proper velocity extraction is not possible for certain ∆tapp and frequency combinations because the angle estimation in this area can not be calculated properly, so far. However, synthetic tests showed that the velocities of a two-layer model could be extracted for specific first layer thicknesses in a given frequency range and a following basic inversion enabled the extraction of the interface depth between these layers. The application of the polarization analysis to two Martian events allowed a frequency-dependent Vs-velocity extraction for the event S1222a, as 2451 m/s and 2665 m/s for the frequencies of 0.21 Hz and 1.43 Hz respectively. These values could be further used to compare with velocity extractions from other methods. For the second event S0235b, the ellipticity of the first break was above the 0.2 threshold and did therefore not lead to trustworthy outcomes. The polarization analysis applied to real data showed, that a velocity calculation is challenging but possible under certain conditions. Many parameters like the source and its frequency content should be known to actually invert the data, which is why a further analysis with receiver functions is recommended. For further processing, an extended synthetic data testing for other parameters should be performed.