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.

Undiscovered underground cavities might exist in the subsurface. A catastrophic ground failure event follows when such a cavity starts to migrate upwards and finally intersects with the surface, resulting in a sinkhole. Catastrophic collapse events are usually preceded by precursory subsidence. An upward migrating cavity causes the development of a (subsidence) trough at the surface. The trough deepens as the cavity nears the surface, changing its surface expression. With the technique called InSAR, displacements over a large area can be measured. Literature shows that precursory subsidence is measurable using InSAR. However, automatically detecting impending sinkholes from InSAR displacements has not yet been researched in depth. This study shows that the developed novel arc-based temporal strategy can early detect an impending sinkhole. The kinematic model is adequate to model the surface expression of an impending sinkhole. The results are used to implement an artificial sinkhole based on the kinematic model into a subset to test the developed strategies. The first strategy was based on spatio-temporal characteristics of a sinkhole. This strategy can locate the subsiding area and indicate a surface expression size range. However, during this study, a second strategy was developed to identify anomalous behavior quicker and more reliable than the spatio-temporal strategy. The second strategy is arc-based and marks point measurements behaving anomalously. The result demonstrates a potential automated early warning system based on the InSAR displacement time series. The developed strategies harbor the potential of monitoring for impending sinkholes on a large scale. This study is anticipated to be a starting point for more development in early warning systems for impending sinkholes. Future research could entail verifying the strategies in regions with collapsed sinkholes.

For hundreds of years, ditch water levels in Dutch agricultural peatlands have been lowered to increase the loading capacity of farming parcels. This lowering results in groundwater levels in the middle of the parcels that fall a few decimeters under the ditch levels. When the groundwater level in a peat soil is lowered, newly uncovered peat is exposed to oxygen and begins to oxidise. This process emits greenhouse gasses (GHG), releases nutrients; like nitrogen and phosphorus that stimulate eutrophication, dries out the top subsurface layer and causes the land to subside. This study focuses on an island polder in Warmond, the Zwanburgerpolder, with a clay - peat subsurface. Half of the Zwanburgerpolder belongs to the Eenzaamheid, a biological cheese farm with the ambition to transition to a regenerative cheese farm. One of the key objectives to achieve this regenerative goal is to limit the GHG emitted from the farm. An analysis of the current (ground)water system of the Zwanburgerpolder was done which focused on limiting land subsidence by raising the groundwater level and thereby reducing the emission of GHG, improving (ground)water quality and stimulating biodiversity. First, four research components were examined through field experiments and literature studies: 1) water quantity, 2) water quality, 3) GHG emissions and 4) land surface displacements. The obtained results were used to understand how the Zwanburgerpolder works and identify the relationships between the four components. Then, two groundwater models were developed to represent the current groundwater level and flows in the Zwanburgerpolder: one in iMOD and one in FlexPDE. The iMOD model was used to get a visual representation of the groundwater level variations across the island and to see the groundwater response to precipitation and evaporation. The FlexPDE model was used to get an overview of the phreatic groundwater level drop between two ditches over the summer. To find the most suitable way to limit land subsidence in the Zwanburgerpolder, the models were adjusted to represent possible future situations. Instead of using the collected climate data of 2021 as input parameter, the projected climate data of 2065 was used. The future models consisted of a base scenario, in which no changes were made to the polder compared to the current situation and adapted scenarios, in which the following five water management measures were tested: 1. Adding ditches, 2. Installing horizontal drains, 3. Temporarily inundating parcels, 4. Installing vertical drains and 5. Raising the summer ditch water level. Temporarily inundating parcels performed the best quantitatively and qualitatively during the comparison of the measures. However, this measure is agriculturally unfavourable because as a consequence, parcels cannot be used for grazing during a significantly long period of time. For the Eenzaamheid, where regenerative practices and agricultural capacity take center stage, the recommendation for limiting land subsidence is to combine and adjust two measures: temporarily inundating parcels and adding ditches. Gutters that currently run down the center of the parcels should be enlarged and inundated during the summer period, by siphoning water from the boezem. Inundation can take place during the whole summer, since grazing is still possible alongside the gutters. It is recommended to start off by only applying the measures in the most critical parcels in order to use it as a testing ground to check the possibly negative effects of the measures besides the desired positive effects of limiting land subsidence, reducing GHG emissions and improving the (ground)water quality. Further, the results discussed in this report provide an interesting addition to peatland subsidence studies. They were obtained through field experiments done on a much smaller budget than other studies done so far with expensive measurement setups. The recommendation towards such peatland subsidence studies is therefore to apply a large network of lower cost measurement setups, instead of a few costly ones, in order to get an extensive representation of the behaviour of different Dutch peatlands. The main limitations in this study are the uncertainties linked to the parameters used to build the iMOD and FlexPDE models and the time constraint on the field experiments. The parameter uncertainties mean that the final model outputs fall within a certain error range. To minimize the error range, a model sensitivity and uncertainty analysis should be done. Without the field work time constraint, it would have been possible to identify the seasonal patterns in the groundwater level fluctuations compared to the other water bodies and in the land surface displacements.

Measurements of a tachymetric network in the geothermal area of Bjarnarflag in North-East Iceland are performed during four consecutive years (2015-2018). For the yearly adjustment of the measurements an alternative iteration scheme to Baarda’s ’B-method of testing’ is proposed, because the level of significance of the F-test performed in the detection step is too large due to the large redundancy of the measurements. The proposed alternative method detects outliers and verifies the stochastic model simultaneously, resulting in 3
to 4% rejected measurements per year. From the yearly solutions absolute and relative horizontal velocities are estimated. The relative velocities are significant, but have large uncertainties. Adding three years of data reduces the mean standard deviation of the estimated velocities from 2.4 mm in east-direction to 0.9 mm and 1.8 mm in north-direction to 0.8 mm. The improvement of precision can be accelerated by reevaluating the stochastic input parameters, adding more GNSS measurements and reconsidering the network design.
Improved horizontal relative velocities can be used to understand the horizontal deformation patterns in the area of study due to extraction of water or steam by the geothermal powerplant, due to the instability of the benchmaks or due to natural processes.

Bathymetry strongly affects nearshore hydrodynamics that drive sediment transport. However, recent bed level information is not always available, especially not simultaneously resolved in space and time. Time series of radar backscatter images can be used to retrieve bed levels in the intertidal area with the so-called Temporal Waterline Approach (TWA) by Bell et al. [2016], yielding a two weeks average bathymetry at spatial resolutions in the order of a few meters. Bed levels are estimated for each radar cell individually by correlating temporal patterns of wet-dry transitions from the radar with hypothetical patterns found in the water level record for different tidal levels. In this study data recorded by a marine X-band radar located at Bunker Hill station (Sylt, German Wadden Sea island) is used to improve TWA, validate the improvement as well as to show its potential in application. A survey was conducted in May 2018 to provide ground truth. Two modifications are made, that improve robustness and reliability of TWA’s output by adding a second threshold and semi-automating the quality procedure. Root mean square error between radar-derived bathymetry (RDB)
and ground truth for the intertidal area is 43 cm (bias 12 cm) on a 7.5 m squared grid. Sensitivity analysis of four parameters (i.e. vertical resolution, inclusion of wave induced effects on water level, length and position of analysis window, thresholds in quality check) reveals, that TWA is most sensitive to the choice of thresholds. Sensitivity analysis is utilized to tune TWA to achieve full coverage of the intertidal area (zero coverage elsewhere) with sufficient accuracy. Additionally it is found that at costs of accuracy the period for which averaged bed levels are retrieved can be shortened from 14.5 to 8.3 days. This is promising, because RDB potentially is able to observe short-term changes in the order of a few days (e.g. storm events). To demonstrate the value of the improved TWA for bathymetry surveys in intertidal areas the method is applied to a 3.2 km stretch of beach in front of Bunker Hill station, capturing the beach state variations in the course of 2017. During wind sea dominated season (winter) a ridge-runnel type of beach is present, that changes to a skewed transverse bar and rip system during swell dominated season (summer). The method is sufficiently accurate and robust for application and proves its potential to reveal new insights, e.g. indications on how the transition between two beach states evolves. In coastal science RDB could serve as a tool to improve existing theories by providing detailed information, that reveals underlying processes. In coastal engineering it fills gaps in monitoring schemes, for example to evaluate effects of nourishment strategies.

Almost four million people in the Netherlands who live below sea level are protected by 17000 km of dikes against the water. Since deformation can be an indicator of a developing failure mechanism, information about this parameter can help authorities to detect weak spots in the dutch water defense structures.
In this research, Radar Interferometry (InSAR) is used to estimate deformation time series on the vegetated part of the dike. Using Point Scatterers (PS), it is already possible to estimate deformation time series with mm precision on objects with a coherent reflection over time. Apart from objects, also surfaces provide a reflection of the radar signal. These so-called Distributed Scatterers (DS), which can for instance be found on dikes, are often strongly affected by temporal decorrelation. Although conventional approaches to detect and estimate these DS do not work, there may still be coherent information for interferograms with small temporal baselines. In this research project, a methodology is presented to detect coherent DS on the vegetated part of a dike and to estimate their deformation time series.
To do so, the phases of PS are subtracted from the DS on the vegetated part of the dike to reduce the phase noise due to different states of the atmosphere. The estimated coherence matrix is then used to only select coherent interferograms which are used to unwrap the phases with respect to PS. Using data obtained from the TerraSAR-X (X-band) and Radarsat-2 (C-band) satellites, it was shown that DS could be detected on some parts of the grass-covered inner slope of the Marken dike.

Flooding is a very costly natural disaster especially when it hits urban areas. Yet synthetic aperture radar (SAR) based flood mapping barely works in urban areas. Buildings and man made objects have similar backscatter signatures as still standing water. This makes them hard to distinguish from one another. Structures can block the visibility of the ground surface for side looking SAR satellites making large parts of potentially flooded ground going unseen by SAR satellites. Smooth surfaces and limited ground visibility make it hard to produce accurate flood maps using SAR in urban environments. Here we have shown how the use of a temporal stack can improve the result of urban flood detection with
SAR. Traditionally SAR based flood mapping uses a single image or an image pair to classify flooded and non-flooded pixels. This study found these methods unable to detect flooded pixels in an urban setting. By using a temporal stack of SAR images more pixels are correctly classified as flooded while keeping false positive classifications low. However the number off correctly classified pixels remains too low to be useful on its own, by adding ancillary data in the form of a high resolution DEM an accurate flood map for a very specific area is produced. This means that SAR images are not suitable for flood mapping in urban areas as a single source of information. When they are combined with other data they have the potential to produce accurate flood maps useful for First responders when the next flooding disaster hits.

Parameter and ambiguity estimation in the temporal domain, for arcs of differential phase observations between two persistent scatterers (PS), is a critical part in Persistent Scatterer Interferometry (PSI). Deformation models, used as constraint in the parameter estimation, often do not capture the full extent of the deformation behaviour. This results in a poor separation of signal and noise, and rejection of arcs that do not behave conform the functional model. Previous work assumed that deformation behaviour is stationary and that a full time series can be described with a single set of deformation parameters. In order to develop a more broadly applicable deformation model, this study applies a temporal smoothness constraint during parameter estimation, by assuming that deformation rates are affected by a temporally correlated zero-mean random acceleration. This constraint is implemented using recursive least-squares, similar to Kalman filtering, which also enables efficient updating of arcs when new acquisitions are available.

Various kind of deformation types are simulated to create phase observations based on real TerraSAR-X, Radarsat2 and ERS stacks of interferograms. This simulated data is processed using the new recursive estimator and results are compared to that of a batch estimator using a steady-state assumption, to analyse the impact of adding a priori information about the smoothness of the physical signal. Furthermore, a case study on real data is performed on an area where non-linear subsidence has occurred, due to soil remediation. This study presents a mathematical framework for incorporating a priori knowledge about the smoothness of the deformation signal as constraint for parameter and ambiguity estimation. Especially non-linear deformation is better estimated using this method, resulting in a higher success-rate, better separation of signal and noise, and more PS passing quality thresholds. The framework moreover enables efficient updating of existing datasets when new acquisition are available.