Ambient Noise Cross-Correlations along Distributed Acoustic Sensing (DAS) for Imaging the Subsurface at Stromboli Volcano.

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Abstract
The deployment of dense seismic arrays on volcanoes has increased significantly over the past decades, enabling more precise monitoring of volcanic activity. While short-period sensors are commonly used, Distributed Acoustic Sensing (DAS) represents a promising complementary technology, providing high spatial resolution and remote location of the interrogator. Accurate monitoring requires a robust understanding of seismic wave propagation, particularly within the shallow subsurface beneath the sensors. On volcanic edifices, the distribution of eruptive deposits along the flanks can be highly heterogeneous, leading to strong lateral variations in physical properties that can significantly affect seismic records.We use ambient noise cross-correlation to investigate the subsurface velocity structure beneath a 4 km-long DAS cable installed on Stromboli volcano, Italy. The analysis relies on two months of continuous strain-rate data recorded on this persistently active volcano, enabling a passive approach. Empirical Green’s Functions (EGFs) are retrieved using Phase Cross-Correlation and time-scale Phase-Weighted Stacking methods, and are validated through comparison with EGFs derived from collocated short-period seismic sensors. Local phase velocities are then estimated along the fiber and inverted to obtain a 2D S-wave velocity model. The results reveal two distinct regions along the profile, which correlate with variations in topography and volcanic deposits.