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The internal structure of a planet provides constraints for understanding its evolution and dynamics. In November 2018, the InSight spacecraft landed on Mars and deployed a set of geophysical instruments, including one seismological station. In this work, the subsurface structure at the InSight landing site (ILS) is explored, from the shallow subsurface to crustal depths, by applying single-station seismological techniques (SST) on martian ambient vibrations and seismic events data. The shallow subsurface at the ILS, in the order of meters, is investigated using the horizontal-to-vertical spectral ratios (HVSR) from the coda of martian seismic events. Assuming a fully diffuse wavefield, a nonlinear inversion using the conditional Neighbourhood Algorithm (NA) allowed to map the shallow subsurface at the ILS. Due to the non-uniqueness problem, different sets of models are retrieved. The 8 Hz HVSR peak can be explained by a Rayleigh wave resonance due to a shallow high-velocity layer, while the 2.4 Hz trough is explained by a P-wave resonance due to a buried low-velocity layer. The kilometer-scale subsurface was constrained by Rayleigh wave ellipticity measurements from large martian seismic events. The ellipticity measurements (0.03-0.07 Hz) were jointly inverted with P-to-s Receiver Functions and P-wave lag times from autocorrelations, to provide a subsurface model for the martian crust at the ILS. The joint inversion allowed the thickness and velocities of a new surface layer, previously proposed only conceptually, to be constrained by multiple seismological data. The HVSR in the 0.06-0.5 Hz frequency range from the coda of S1222a, the largest event ever recorded on Mars, suggests a gradual transition from shallow to crustal depths and consolidates the group of shallow subsurface models with the largest shear-wave velocities as the most compatible with the crustal structure. A comprehensive multi-scale model of the ILS subsurface is proposed. The ILS is characterize

We estimated the Empirical Green¿s Functions (EGF) from ambient noise cross-correlations using a dense array of 3C broadband seismometers deployed above an anticline structure hosting an underground gas storage in France. In total, 580 recording locations are available. Several array configurations have been used, some of the seismometers being moved to new locations every day. The survey duration was of 16 days, with around 2 days of recording per location, and a typical interstation distance of 400 meters. Our methodology uses polarization characteristics to separate body and surface waves. The approach uses the imaginary part of ZR+RZ cross-coherency (Z: vertical; R: radial) to enable the distinct reconstruction of diving P-waves. In order to enhance the signal-to-noise ratio of the retrieved P-wave, we employed common-offset bin-stacking over all virtual sources and receivers, with an offset bin of 50 meters. Subsequently, we assessed the stability of the extracted P-wave by computing a separate common-offset bin-stack for each recording day and each station couple azimuth interval. The consistent moveout of the extracted P-wave, regardless of various station couple azimuths and recording days, suggested that there was no significant source distribution bias in our EGFs. In the next step, by using the P-wave window from the common-offset bin-stack as a template, we selected only the individual station pairs for which the correlation coefficient between the EGF and the template was above 0.8. This resulted in rejecting about 95% of the station couples. Around 7000 P- arrival times were picked from the selected EGFs in a semi-manual way. The accuracy of these arrival times was validated against the Eikonal solution for the first arrival within the ¿known¿ 3D velocity model of the site, based on active seismic and well logging data. Finally, a 3D tomography based on the picked arrivals allowed us to invert for a P-velocity model up to a depth of around 700 meters.