Magma and fault dynamics from novel approaches in seismology and geodesy

Seismic and magmatic activities represent a major part of natural hazards. Studying these events is essential, as this phenomenon governs surface and subsurface displacement and deformation. The alliance of seismology and geodesy covers the characterization of ground movement below and above the surface. It is in those research branches that major advances are made to identify event sources and features. My research focuses on new methods of modelling and analysing data in order to distinguish between the sources of movements induced by tectonic and/or magmatic activity. To this end, my thesis is divided into three chapters that allow the methods to be assessed in different geodynamic contexts. First, I analyse two seismic sequences that occurred in 2023 on the Gulf of Aden mid-ocean ridge, using a range of seismological methods to deduce the source of seismic activity. Then, I revisit one of the largest European earthquakes, the Mw 6.2 Aigion earthquake in Greece, using InSAR and seismicity modelling and challenging previous models and knowledge about the structure of the Corinth rift. Finally, the thesis details the construction of a Machine Learning (ML) tool that deduces fault parameters for ground displacement measured by InSAR. The tool demonstrates that it is possible to use ML to solve fault parameters that caused surface deformation visible by InSAR.