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This thesis concerns the detection and analysis of micro-seismicity and low-frequency earthquakes in New Zealand's central Southern Alps. We make use of the 6.5 year continuous seismic dataset collected using the Southern Alps Microearthquake Borehole Array (SAMBA), alongside other temporary and permanent seismic deployments nearby. The small station spacing of this deployment allows for high resolution seismic studies near the Alpine Fault, a dextral-transpressive plate boundary fault between the Pacific and Australian plates.  Using this dataset we have documented the  rst evidence of low-frequency earthquakes on or near the deep extent of the Alpine Fault. By using a network based crosscorrelation detection method we have generated a 3 year catalogue of 14 low-frequency earthquake families. These low-frequency earthquake families locate close to other indicators and models of the deep extent of the Alpine Fault, and we interpret these low-frequency earthquakes to represent shear failure on or near the deep extent of the Alpine Fault. These low-frequency earthquakes highlight a near-continuous background rate of deformation, punctuated by short periods of tremor. We also observe higher rates of low-frequency earthquake generation after large regional earthquakes. The magnitudes of our low-frequency earthquakes range from Mʟ‒0.8‒1.8, and appear to follow an exponential distribution, implying that there might be a characteristic length-scale of failure.  We have extended the catalogue of low-frequency earthquake templates using the full 6.5 year dataset and an objective synthetic detection methodology. We developed a new methodology for template detection after other methods failed, or were not feasible. This method employs simple synthetic template events, which, rather than trying to capture all of the complexities of the body waves we try to detect, approximate a simple waveform that does not correlate well with background noise. To undertake this method we have developed a multi-parallel Python package, which is highly portable (we have run this on computers ranging from dual-core, 8GB RAM laptops to a 393 node, 6349 CPU cluster computer) and distributed via an open-source model. This package was run through the 6.5 year dataset on the New Zealand E-Science PAN cluster to e fficiently (

Improved earthquake detection as a probe for active fault structures in New Zealand's central Southern Alps