We use ground and space geodetic data to study surface deformation and gravity change at Kīlauea volcano from January to September 2015. This period includes an episode of heightened activity in May 2015, which we refer to as ’the May 2015 event’. The data set consists of Global Navigation Satellite System (GNSS), tilt, visual and seismic time series along with 25 descending and 15 ascending acquisitions of the Sentinel-1a satellite in Interferometric Wide swath mode and microgravity surveys taken a few years before and just after the May 2015 event. We identify four different stages of surface deformation and volcanic activity during the May 2015 event which we attribute to the movement of magma and pressure changes in response to a magma supply and withdrawal imbalance in the shallow plumbing system. In particular, we model the deformation sources attributed to the Halema’uma’u reservoir (HMMR) and South caldera reservoir (SCR). The SCR was best described by inflation of a spheroidal at 2.8 (2.65-3.07) km depth below the Southern caldera region. The HMMR source was modelled by a point source deflation located East of the Halema’uma’u crater at 1.5 (0.95- 2.62) km depth. The surface microgravity changes which would result from changes in these reservoirs are significantly lower than the actually observed microgravity changes. We attribute this to the lack of complexity of the single point source model used. Mechanisms that add/remove mass from the subsurface without accompanying surface deformation, which are not part of the point source model, played a significant role. More frequent microgravity campaign surveys, if needed with a smaller network, are the only way to improve our understanding of these processes and help to quantify them.

In the Krafla region in North East Iceland, a change in the deformation pattern was observed in 2018. Since the 1975-1984 rifting event, there was subsidence seen in the Krafla caldera and along the fissure swarm. This subsidence was explained by deflation which decreased exponentially along the years. In 2018, this deformation pattern reversed, and for the first time since 1989, uplift was observed in the region. Therefore, this work concentrates on examining the change in deformation pattern in the region that occurred in 2018. Four geodetic techniques, a combination of ground and space geodetic techniques, are used to study this change in deformation pattern noted in the Krafla region. Data from 2016 to 2019 are considered as they span the time of interest when the change took place. In levelling, InSAR and GPS, the uplift observed is located to the North of the Krafla power plant. Similarly, there is an increase in net gravity seen to the North of the power plant. This suggests there is an increase in mass/density. A possible reason could be movement of magma from the deep to the shallow magma chamber. The reason behind this start of the magma movement is not known. On the other hand, there is continued subsidence and an increase in net gravity seen in the fissure swarms present to the south of the power plant. This result agrees with the fact that the uplift is concentrated (a local phenomena) in the northern region and there is still subsidence seen in the south. A simple Mogi model is fitted to InSAR and GPS data to understand the cause for this change in deformation. But, the fitted model provided very few insights in this work. The results from modelling mainly concentrated on the subsidence in the southern region and corresponding model parameters were obtained. The location of the source responsible for the modelled deformation (subsidence) is found to be near the power plant. The depth and volume however are not properly constrained. But since the model tries to constrain at deeper depths, correspondingly larger volume is also seen. This outcome strengthens the hypothesis that the source for the deformation could lie at deeper depths. Based on the overall results, the following recommendations are made to enhance the results: i) Maintaining the continuity in the data ii) To increase the number of benchmarks measured near the deformation area (especially in gravity and levelling) iii) Use of multiple source modelling for the better understanding of the sub-surface processes.

In this study an analysis of the efficacy of using satellite data, in the form of InSAR measurements, as an extension of the volcanic monitoring network on Saba and St. Eustatius is performed. For this research, data from three different satellites that operate at three different wavelengths are available: ALOS-2 (L-band SAR), Sentinel-1 (C-band SAR) and PAZ (X-band SAR). The data are analysed through the formation of interferograms that are obtained using the Delft Object-oriented Radar Interferometric Software (DORIS) and Persistent Scatterer Interferometry (PSI) performed following the Delft Persistent Scatterer Interferometry (DePSI) algorithm. The interferograms and PSI results differ strongly per satellite and are affected by the combined impact of several factors. In this study the impact of the misalignment of the master image used in the generation of the interferograms with respect to the Digital Elevation Model (DEM) is discussed, as well as the impact of the incidence angle, the spatial resolution, the temporal resolution, the perpendicular baseline, the number of available images and the wavelength. The interferograms of ALOS-2 are of a good quality, however the low temporal resolution makes studying fast surface deformation difficult. However, they could be used to study surface changes in retrospect or to study slower processes, such as the pressurisation of a magma chamber, causing gradual surface deformation. The low spatial resolution makes the interferograms of Sentinel-1 difficult to interpret and the interferograms for the PAZ data currently show too large amounts of decorrelation to study surface deformations. The PSI analysis produces reliable results for Sentinel-1. The estimated linear deformation for the Persistent Scatterers (PS) shows constant values over both islands, which are centred around 0 mm/y and have low standard deviations. Therefore it is assumed, based on the data and prior knowledge about the area, that there is currently no deformation on either of the islands. The PSI analyses for the other two satellites do not provide reliable results, because the number of available images in the stacks is too low (only 10-12 images compared to the 116-123 available images for Sentinel-1). The PAZ data might be used in the future, when more images are available, however the low temporal resolution of the ALOS-2 data means that an appropriate stack cannot be acquired within the design lifetime of the satellite. The ALOS-2 interferograms and the PSI analysis for Sentinel-1 could thus at present be a useful addition to the ground-based monitoring network. When a larger stack of data for PAZ is available, the PSI analysis could potentially be conducted again in order to determine its use as a volcanic monitoring tool.

Over the years, InSAR has become an indispensable tool in the study of ground deformation, including volcanic deformation, and this continues to be the case in times of improved technology. Since the volcanoes on the Caribbean islands of Saba and St. Eustatius are active, the implementation of an InSAR-based monitoring system is crucial to enhance the spatial resolution of volcano monitoring beyond the capabilities of the ground-based monitoring network, for instance in the case of localized deformations such as dike intrusions. However, technical challenges arise in these tropical settings, caused by dense rainforest, atmospheric artifacts and terrain variability, posing serious challenges to the use of InSAR. Time series InSAR, including SBAS and PSI, can be used to overcome these limitations. A previous study has explored the use of PSI for monitoring, using the already available DePSI software. In this research, an SBAS approach within the Delft InSAR software framework is developed using state-of-the-art Python packages, including (sar)xarray, dask and zarr, and is used to assess whether there is capability to develop SBAS into a volcanic monitoring tool for Saba and St. Eustatius. In addition, a preliminary comparison between the SBAS and PSI methodologies is performed based on a theoretical and (semi-)quantifiable approach. This study combines data from two satellites operating at different wavelengths: Sentinel-1 (C-band) and ALOS-2 (L-band). Assuming no ongoing deformation, based on GNSS results, the variability of the results around zero can be used as an indicator of precision. The results obtained through SBAS are promising, in particular for L-band, on account of e.g., extensive spatial coverage, efficiency and relatively low variability even with the presence of atmospheric and DEM components. Overall, the results reveal mm order deviations. In the event of volcanic activity, the expected deformation signals are in the range of cm-dm's and can therefore be detected, i.e., with an estimated minimal detectable deformation of 1.5 cm/year in the worst-case scenario. The implementation of three different coherence-based masking approaches-water, single and individual-give an indication of the level of robustness and reliability of the results. Generally, a relatively high level of consistency can be observed among the different masking results of ALOS-2 for both islands, for St. Eustatius following the correction of the unwrapping errors using two testing approaches: an interferogram removal approach and an adaptive approach based on the DIA procedure. The latter procedure allows for retaining all observations and their residuals and is therefore preferred. In contrast, the Sentinel-1 results reveal a lower level of consistency. It is suspected that this inconsistency mainly arises on account of the numerous unwrapping errors within the single masking approach. The individual masking approach appears to be less susceptible to unwrapping errors, however is more prone to outliers than the single masking approach. Further research, following the correction of the atmospheric component and DEM errors, may offer insights into the preferred masking approach. Overall, the use of L-band imagery shows potential, offering spatial coverage where C-band does not, even with limited ALOS-2 data availability and large temporal baselines. The preliminary comparative analysis with the PSI approach, based on the respective strengths and limitations from literature, spatial coverage, processing steps, precision and computational requirements, suggests that a hybrid method could prove to be advantageous to minimize (potential) signal loss, e.g. either from limited spatial coverage or spatial resolution, and enhance volcanic risk assessment. SBAS excels in the extensive spatial coverage, especially using L-band, providing nearly homogeneous coverage of St. Eustatius, even on the flanks of the Quill, and on the outer flanks Mt. Scenery on Saba. However, regardless of the mask, wavelength or method, acquiring coverage around the summit of Mt. Scenery on Saba remains challenging. The study contributes to advancing InSAR time series analysis for the volcanic monitoring on Saba and St. Eustatius through the successful implementation of an SBAS approach within the Delft InSAR software framework based on state-of-the-art packages, the implementation and evaluation of new approaches to enhance the method in terms of the efficiency and robustness and a comparison with existing software. In addition, the software can be applied in a generic sense for various applications and can be extended for further improvements.