Hazards that arise from volcanic settings are abundant, and the continuous monitoring of volcanoes remains an important task to protect civilians. Early warning systems have an enormous impact in effectively informing the general public of potential hazards and reducing the associated risks involved with volcanic eruptions. Volcano monitoring infrastructures rely on various complementary geophysical techniques, and the maintenance of such a diverse system of instruments is often challenging. This dissertation concerns the automated assessment of geophysical instruments, and the application of microgravity observations to long-term volcano monitoring.

Array processing of infrasound data uses the coherency between sensors to calculate directions of incoming waves. The Cabauw Infrasound Array (CIA) provides unique opportunities for infrasound processing. Because unlike most infrasound arrays, CIA has sensors with height differences. Specifically sensors distributed on a 200m tall tower. But the data from these tower sensors are of limited use for time-domain array processing due to the measurement of both the incoming wave and its reflection. To make the measurements suitable for array processing the reflection needs to be removed. The ground measurements are used to approximate the waveform and a time-shifted ground average is removed from the tower measurements. The new cleaned data was successfully used for full 3D array processing.

All over the world a so called oceanic 'hum' can be recorded, dominating the ambient noise field. The hum is generated by nonlinear interaction of ocean surface waves, radiating acoustic signals in the atmosphere and water (named microbaroms), and coupling to the solid earth as microseisms. The hum can be generated by local near-coastal sources and distant deep ocean sources. Deep oceanic generated 'hum' occurs within the range 0.1-0.3 Hz, dominantly around 0.2 Hz. The near-coastal generated 'hum' occurs at higher frequencies. Microseisms are mainly recorded as surface waves corresponding to near coastal activities. These surface waves overwhelm the weaker deep ocean signals, body and surface waves, because they attenuate less due to the shorter travel path. Previous studies are done with individual 3-component sensors, thus spectral data of all kind of microseisms, or for teleseismic distances only. This study of deep ocean microseisms is done by seismic arrays to analyze regional microseisms. Arrays provide more information about the microseisms by applying beamforming. This enables an improved localization of the source area, in specific near coastal activity or deep ocean generated. To validate the observed results a comparison with the numerical simulated source area is be made. Denote that the use of seismic arrays requires verification on the performance of arrays due to local conditions (sensitivity variances) to find possible deviations regarding the back azimuth. It is shown that, using classical beamforming, the recordings are dominated by near coastal surface waves. Applying adaptive beamforming using multiple signal classification, also other events become visible in the f-k spectrum. Due to this method an improved deep ocean source area is obtained. This observed source area agrees with the simulated source area. Improving the localization requires to define array correction factors.