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.

Nowadays, many people and organizations depend on Global Navigation Satellite Systems (GNSS. Monitoring of GNSS is important to ensure the quality of GNSS measurements and products. The availability of the signals-in-space (SiS) is an essential part of the monitoring of GNSS, but it is not clear how availability is defined and standards for monitoring are lacking. The main research question for this thesis is therefore: Which are the key performance indicators related to availability that unambiguously describe sensor station and system performance in time, how can these be computed in an operational manner, and how can they be presented in a condensed form to the stakeholders? This includes an objective of defining unambiguous performance parameters for sensor station and system, and address the considerations related to the definition. A prototype software tool is created to study the algorithms and compute the key performance indicators. Availability is in the basis a binary operation: a signal is available or unavailable. When this is applied on daily measurements, daily statistics can be computed. A signal is considered available if the code, carrier phase and C/N0 measurements are present, and meet certain standards. A signal is said to be expected if the satellite is expected to transmit that signal, the receiver is configured to receive that signal, and the signal is not blocked by objects in the signal’s path to the sensor station. For this it’s needed to define and compute an elevation mask for each station. The sensor station and system performance parameters are computed from a network of sensor stations, using files in the Receiver Independent Exchange format (RINEX). Four key performance indicators are defined for the sensor station performance. The Daily Station Availability describes the part of the day that the station is operational, the Daily Station Total Availability gives how well the station receives, and the Effective Mean Elevation quantifies the elevation mask and thus the location of the sensor station. These three parameters are summarized into the Overall Station Quality parameter, which gives and overall performance class to the sensor station. For the system performance a satellite is considered available if all signals are received by a sensor station of the monitoring network and the health status is healthy. The satellite is considered unavailable if the signals are received by none of the monitoring stations, while expected by at least two stations, or the health status is unhealthy. The Daily GNSS Availability parameter gives the percentage of the day that the satellite was available and the Daily Available number of Satellites tells how many satellites were available during the day.  The parameters are computed for a period of 100 days. Results are presented using color codes and by showing only detailed information in case of anomalies or specific investigations. The proposed key performance indicators showed to be very useful at pointing out good performances or anomalies. While SiS availability gives much insight in the performance, a monitoring tool can be improved when combined with other performance aspects.  

Interferometric Synthetic Aperture Radar (InSAR) and Global Navigation Satellite Systems (GNSS) are widely used to monitor the dynamic behavior of the Earth. InSAR is a geodetic technique that estimates millimeter-level relative displacement time-series in an opportunistic network of a multitude of coherent points on the Earth’s surface, in a local datum. GNSS uses ground-based instrumentation to acquire time-series data over a limited number of specific and well-defined points in a known geodetic datum.The Integrated Geodetic Reference Station (IGRS) is designed to combine these (and other) techniques into one common instrument, establishing an integrated benchmark, i.e., a GNSS antenna and two radar corner reflectors, ensuring an identical kinematic behavior. This enables a geodetic datum connection, effectively enabling the InSAR results to be represented in a common geodetic datum, instead of a free network.However, the efficacy of the IGRS has not yet been proven, i.e., a thorough analysis of the first empirical results of an IGRS network has not yet been performed.Here we show that by using three years of data from a spatio-temporal network of 29 IGRS stations in an area of 60×60 km, and 742 independent Synthetic Aperture Radar (SAR) acquisitions, we reach a high level of agreement, demonstrating that IGRS can be used to connect InSAR information products to a well-defined geodetic datum.By using an Overall Model Test with a significance level of 5% we found that 96% of the double-difference arcs in time and space, sustain the null hypothesis that both the InSAR and the GNSS results stem from the same distribution. We found that the main reason for rejecting the null hypothesis for the remaining 4% of the double-difference arcs is that the results of both the InSAR and the GNSS are affected by a leakage of signal from the functional to the stochastic model. For the InSAR observations there is inadequately modeled atmosphere leaking into the stochastic model, while for the GNSS it appears that the precision estimate of the periodically moving stations is worse than the non-periodically moving stations, which suggests that the stochastic model is influenced by the the functional model.In the end, this study proved the efficacy of the IGRS to connect different geodetic datums, and this enables the InSAR results to be integrated in a well-defined geodetic datum.

Robot Care Systems (RCS) is involved in the development of the WEpod, an autonomous shuttle which can transfer up to six people. Based on a predefined map of the environment, the shuttle is able to navigate through mixed traffic its perception sensors such as camera, radar and lidar sensors. This study is acquired in collaboration with RCS and focuses on two parts: assessing the influence of different factors on the domain shift and assessing the importance of depth information in the transformation of scene understanding from image space to top view. For the WEpod, or any self-driving vehicle to safely travel over the road and through traffic, it is important to understand road scenes that appear in our daily life. This scene understanding is the base for a successful and reliable future of autonomous vehicles. Deploying a Convolutional Neural Network (CNN) in order to execute the task of semantic segmentation is a typical approach to attain such understanding of the surroundings. However, when a CNN is trained on a certain source domain and then deployed on a different (target) domain, the network will often execute the task poorly. This is the result of differences between the source and target domain and is referred to as domain shift. Although it is a common problem, the factors that cause these differences are not yet fully explored. We filled this research gap with the investigation of ten different factors. To explore these factors, a base network was generated by a two-step fine-tuning procedure on an existing convolutional neural network (SegNet) which is pretrained on the CityScapes dataset (dataset for semantic segmentation). Fine-tuning on part of the RobotCar dataset (road scenery dataset recorded in Oxford, UK) is followed by a second fine-tuning step. The latter is done on part of the KITTI dataset (road scenery dataset recorded throughout Germany). Experiments are conducted in order to obtain the influence of each factor on a successful domain adaptation (i.e. negligible domain shift). The influence of factors on the domain shift based on semantic segmentation is assessed by comparing the result of every factor to the result on the base network. Results consist of the F1-measure and Jaccard index for drivable path segmentation and occupancy segmentation although the emphasis lies on the drivable path segmentation. Significant positive influence on the estimation of drivable path for the WEpod domain was obtained when the ground truth labels only consisted of two labels (i.e. drivable path and non-drivable path) instead of three classes. This performance gain is signed by an increase of 8 percent points for both the IoU and the F1 metric. Making all images intrinsically consistent, and thus removing all geometric differences between the camera sensors, resulted in a larger increase of performance metrics. Compared to the baseline, both the Jaccard index and F1 metric increased with 10 percent points. The training order is a main contributor for domain adaptation with an increase of the IoU metric of 18 percent points and 20 percent points for the F1 metric. This shows that the target domain (WEpod) is more closely related to RobotCar than to KITTI. Although the investigation of different factors potentially can realise a better performance on the WEpod domain, understanding the environment in image space is not enough because path planning is utilised in top view. Hence, a transformation between image space and top view is needed to use the scene understanding based on semantic segmentation to the full extent. For this transformation, three setups are utilised with each a different form of depth information available: no depth information, ground truth depth information and estimated depth information. This approach gains insight into the relevance of depth information on the usability of scene understanding. The accuracy of top view transformations is measured in the form of four metrics: raw lateral error, scaled lateral error, overlap length and a count metric. The first metric is concerned with the raw difference between the estimated and ground truth trajectory. The second metric is a scaled form of the former. The overlap length measures to what extent the trajectory is estimated while the count metric takes into account if the estimated trajectory is present in top view. From the experiments it is concluded that depth information plays an important role in the lateral sense of the trajectories while it is of less importance for the longitudinal length of the trajectory. It is also noticed that depth information does not necessarily needs to be dense. Moreover, the sparse but ground truth depth information leads to a better trajectory.

The Delft real-time GNSS single-frequency precise point positioning (RT-SF-PPP) algorithm is extended to include velocity and receiver clock drift as unknown states to be estimated from Global Navigation Satellite Systems (GNSS) measurements. Carrier-phase ambiguities are assumed constant over time. Two different variance models are used, one obtains variance as a function of satellite elevation, and the other obtains variance as a function of carrier-to-noise density ratio as estimated by the receiver. The elevation based variance model was used in the original RT-SF-PPP algorithm, and adapted to include Doppler measurements. The carrier-to-noise density ratio based variance model components are estimated from double difference (DD) observation combinations using measurements obtained from a shortbaseline experiment with two receivers setup over multiple days. Two velocity observables are used and related to velocity and clock drift through the extended functional model of the original algorithm: the receiver generated Doppler and a time-derivative of the carrier-phase observable: the time-differenced carrier-phase (TDCP). Algorithmic performance is evaluated by the horizontal RMSE, which represents accuracy as the variance plus bias squared, precision and reliability. This was validated using three different experiments: a stationary receiver on top of a roof, a buoy freely adrift in the North Sea, and a receiver mounted on a car driving a regional road. It was found that in terms of position in the static experiment and under calm water conditions during the drifting buoy experiment the horizontal RMSE was between 0.429 and 0.530 [m], and under rough water conditions and a road partly flanked by fences and trees between 0.682 and 0.812 [m]. Furthermore in terms of velocity it was found that the TDCP observable in combination with the carrier-to-noise density based variance model has a horizontal RMSE between 0.014 and 0.068 [m/s] over all experiments, and using the Doppler observable with either variance model a RMSE between 0.033 and 0.122 [m/s]. The algorithm was even found by means of external reliability to be capable of detecting faults at the boundary of 0.5 [m] for position and 0.1 [m/s] for velocity in the TDCP observable case.

In the Netherlands, the Delta Programme aspires to adjust spatial planning climate-proof and water-resilient, in order to be prepared for extreme weather in 2050. To achieve this ambition, municipalities, provinces, regional water authorities and central governments conduct stress tests to map out the vulnerabilities in their areas of authority by no later than 2019. The stress tests comprise four themes: pluvial flooding, drought, heat and floods. In addition, the Delta Programme 2019 acknowledges the mitigation of and adaptation to land subsidence as an important tasking. The municipality of Rotterdam faces the challenge of adding land subsidence as stress test theme and assessing its influence on pluvial flooding. Contrary to the stress test pluvial flooding, no consended methodology exist on how to map out vulnerabilities concerning land subsidence. In addition, only few studies have numerically investigated the spatial-temporal effect of land subsidence on pluvial flooding in urban areas. However, the advent of techniques to measure ground level (LiDAR) and land subsidence (InSAR) and advances in high resolution flood modelling (3Di) enable the numerical modelling of urban pluvial flooding influenced by land subsidence. This research explores the investigation of the influence of land subsidence on pluvial flooding in Rotterdam by supplementing the conducted stress test pluvial flooding with a land subsidence assessment. The conducted stress test pluvial flooding in Rotterdam is based on a 3Di-simulation of standardised rain events, based on a DEM 2016. To asses the current influence of land subsidence on pluvial flooding, a Digital Elevation Model (DEM) that approximates the sub-neighbourhood Tuinenhoven at design level is created and used as 3Di-input. When comparing 3Di-results based on this design DEM to the stress test pluvial flooding, it becomes clear that the total volume of water during extreme rainfall stored on the streets is not affected by land subsidence. The bathymetry of the DEM does affect the water's distribution however. The Tuinenhoven case-study demonstrates that currently land subsidence increases the severity of the impact of pluvial flooding but that the main cause of pluvial flooding during extreme rainfall is the limited capacity of the drainage system. Land subsidence in Rotterdam complex. The conducted land subsidence analysis based on an InSAR data-set supports this complexity. It illustrates that the subsidence behaviour of Rotterdam is influenced by foundation type, land use classification, the presence of dredge in the anthropogenic layer and top soil type. This respectively indicates the occurrence of pole rot and shallow foundations, anthropogenic compression and compaction of shallow soft layers caused by loading, landfill subsidence as a result of land fillings that contain dredging spoil and consolidation of the Holocene clay layer as a result of drainage. However, the land subsidence analysis failed to identify location-specific dominant land subsidence processes. This failure was primarily caused by the limitation to only one linear subsidence rate between 2009 and 2014 per point. To demonstrate how land subsidence can be translated to pluvial flooding based on a land subsidence analysis, land use classification was selected as the most dominant influencing factor and used in a linear land subsidence prognosis until 2030. The linear assumptions largely obstructs results to be interpreted location-specific. The IJsselmonde case-study shows that land subsidence is expected to decrease the passability of roads and decrease the risk per building in the future. These decreases are caused by the fact that roads relatively subside fast and buildings relatively slow. The biggest influence on the risk per building classification is the assumed threshold value per building. Simulated road maintenance results in an increase of the passability of roads and an increase of buildings at risk of water nuisance. The loss of the water-storing function of the road after reconstruction increases the water levels in gardens and puts buildings at an increasing risk. In conclusion, the most challenging part of investigating the influence of land subsidence on pluvial flooding is the crucial identification of the different occurring land subsidence processes. It is demonstrated that the possibilities with InSAR-data are promising, when used with sufficient competency, although the available InSAR data should be divided in shorter intervals to detect the subsidence rate trends. Land subsidence rate trends are crucial in the identification of land subsidence processes and assessing influences like groundwater variations and increased loading due to maintenance or construction works. When the land subsidence analysis is improved, so will the land subsidence and threshold height per building prognosis. When the relative prognosed decrease of the threshold value per building is improved, it can be quickly assessed whether buildings classified at risk in the stress test pluvial flooding are at future increasing risk during extreme rainfall, without conducting a full 3Di-simulation.

Satellite radar interferometry (InSAR) is a powerful technique for monitoring deformation phenomena. While deformation phenomena occur in a three-dimensional (3D) world, one of the limitations of the InSAR phase observations is that they are only sensitive to the projection of the 3D displacement vector onto the radar line-of-sight (LoS) direction. To uniquely estimate the three displacement components, we would require at least three sets of spatiotemporally coinciding independent (STCI) LoS observations, (i.e., scatterers on an object that is not subject to internal deformations, observed at the same time) available over the same Region of Uniform Motion (RUM). More importantly, the system of equations needs to have a full rank coefficient matrix. Unfortunately, in most practical situations at most two sets of STCI LoS observations are available, resulting in an underdetermined system with an infinite amount of possible solutions. Within the InSAR literature we encounter different approaches to address the underdeterminancy problem, unfortunately often with either mathematical or semantic flaws. We concluded that the InSAR community has no uniform way of addressing the underdeterminancy problem. We developed a taxonomy for the different fallacious approaches that can help by evaluating InSAR results and reviewing InSAR papers. Moreover, using the east-north-up (ENU) reference frame for decomposing the LoS observations provides results that are not tuned to the needs of the end-user of an InSAR product. Therefore, we developed an alternative solution to the underdetermined problem, in the form of a `strap-down' approach, which uses a local strap-down reference system that is fixed to the deformation phenomenon with transversal, longitudinal, and normal (TLN) components. For many practical cases, such as line-infrastructure, landslides, or subsidence bowls, analysis of the main driving forces supports the assumption that significant deformations in the longitudinal direction are unlikely. We found that using the strap-down approach gives physically more relevant estimates. Moreover, it results in more relevant estimates since it properly includes all uncertainties. We can further conclude that the conventional way of communicating (PS)-InSAR results by means of a `dot distribution map' is sub-optimal when considering the quality of the estimates. For many cases, `vector arrow maps', or traditional geodetic vector-based visualizations, including error ellipses are a viable and more optimal alternative.

Geodesists use multiple methods to monitor surface deformation. This gives the opportunity to integrate complementary data for better interpretation of deformation processes. The integration of data has to deal with: (1) spatio-temporal differences in sampling methodologies, meaning that observed objects are not the same and thus observed processes may stem from different sources; and (2) physical differences in the methodologies leading to different kinds of coordinate reference systems with possibly different datums. This makes integration of data challenging.In this thesis, we address one of the fundamental roots to this integration problem, by developing co-located reference points for multiple geodetic monitoring methods. This will ensure that, for multiple geodetic monitoring methods, one common deformation process is observed. This eliminates interpolation between observations. I show the main requirements for an Integrating Geodetic Reference Station (IGRS), present a design for a fully functional IGRS and describe its performance. Furthermore, the protocols for deployment and operational use are given. Benchmarks for InSAR, GNSS, levelling, LiDAR, and gravimetry are present on the IGRS. From field tests, it is found that presented radar reflectors have a 1-sigma measurement precision of <0.5 mm in the Line-of-Sight of the radar. This includes both the structural stability as the influence due to clutter. Furthermore, it is shown that the GNSS antenna has mm precise performance, similar to standard monitoring GNSS set-ups.The developed IGRS can be deployed to create a local datum connection between datasets. Ideally IGRSs, either the design presented in this thesis or similar, are deployed where integration, validation and calibration of data, especially InSAR data, is needed.

In the Second World War Dutch New Guinea was a strategic battle front for both the Japanese and the Allied forces in the Pacific War. A lot of airstrips were constructed and bombed during this time, of which at least three (Mongosah, Otowari and Sagan) have never been visited after the war. This provided a great opportunity to find potential war heritage and airstrip equipment. Later this year an additional research team will go on an in-situ exploration to potentially find those objects. To do so, they needed a classification map giving information on the type and location of the vegetation. This map helps to know where to land with a helicopter, to setup base camp, to find travel ways, etc. Thus, the main objective of this thesis is to check whether it is possible to create a proper classification image with the available data. I used data obtained from the Sentinel 2 Mission (Optical data), the ALOS PALSAR Mission (L-Band Radar data) and the SRTM Mission (Digital elevation data). I pre-processed the data and used the supervised classification method, “Maximum Likelihood Classification” (MLC). I masked clouds via three different cloud masking methods, MLC Method, Threshold Method and Sen2cor (scene classification) Method. I compared the three different methods with each other and there is no significant difference between them. The classifications have been cross-validated with a reference validation dataset and the classified pixels are on average about 90% correctly classified.

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.

Heavy rainfall, combined with expanding (unplanned) urban settlements in flood prone areas, expose Dar es Salaam (Tanzania) to the risks of flooding. The urbanisation is so rapid in many areas that it is not beneficial to carry out expensive surveys which are quickly out of date. The work carried out by community-mapping project Dar Ramani Huria (Swahili for "Open map") aims to make a detailed map of Dar es Salaam, to enable the hydrologic models to approach the real situation more closely. However, the surveying methods used until recently are not sufficiently accurate. However, an alternative emerges in the form of community members using a low-cost, dual-frequency global navigation satellite system (GNSS) receiver during surveys. However, before this receiver can be implemented a detailed research has to be done. In this thesis the horizontal and vertical performance of the U-blox ZED-F9P receiver in Delft (the Netherlands) and Dar es Salaam is studied. The research is divided into two parts: performance and case study. For the performance study a series of post-processed kinematic (PPK) experiments were conducted in Delft and Dar es Salaam. The experiments have been designed in order to provide a variety of location, antenna-performance, baseline length, software package and movability. In addition, two re-initialisation experiments were conducted to measure how fast the interrupted GNSS signal is regained by the receiver. The case study focused on the desirability and feasibility, mainly focussing on accuracy, of implementation in the project of Dar Ramani Huria. Structured and unstructured interviews with employees of the Humanitarian OpenStreetMap Team (HOT) Tanzania were held to find out the requirements of implementation. The positioning performance of the receiver varies between the different experiments. The conclusions regarding the positioning performance are based on the scatter plots in the horizontal plane and the positioning over time for the three separate directional components; East, North and Up. The values for the horizontal performance (RMS East, RMS North) and for the vertical performance (RMS Up) of the fix solutions insofar as they fall inside the 95% confidence ellipse are decisive. Only the relevant experiments, namely those who can map a larger area with a single reference station are taken into consideration. The horizontal positioning performance ranges from 1.13 till 16.83 However the latter, high value is from the 9 baseline Dar es Salaam experiment with a very low percentage of fixed solutions. If we disregard the experiments with low percentage of fixed solutions then the horizontal positioning performance ranges van 1.13 till 9.42. The vertical positioning performance shows less accuracy ranging from 3.56 till 14.75. If we compare this performance with the requirements for Dar Ramani Huria’s project, even the strictest of 2cm, the performance is more than adequate according to the "few cm accuracy" requirement. The experiment with the high-end antenna shows with values 2.44mm (RMS East) and 3.42mm (RMS North) the best horizontal and with the value 3.75$mm(RMS Up) the best vertical performance. Another factor influencing the performance is the location, in particular the aspect of atmospheric delay that varies between Dar es Salaam and Delft. This research thesis concludes that the implementation of the receiver in Dar Ramani Huria's project is well possible and that the performance of the receiver is adequate. This conclusion is confirmed by what is actually occurring in the field: HOT Tanzania and Dar Ramani Huria already started using the GNSS receiver and carrying out surveys with this receiver.

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.

Met hun grafische weergave van de werkelijkheid hebben kaarten al eeuwenlang tot de verbeelding gesproken. Grote veranderingen rond 1800 op nationaal en koloniaal gebied hebben de wereldwijde vraag naar betrouwbare kaarten aanzienlijk doen toenemen. Met “Indonesië op de kaart” is onderzocht hoe de Indonesische archipel in de periode 1800-1990 in kaart is gebracht. Tot de overdracht aan de Republiek Indonesië in 1949 hebben koloniale verhoudingen invloed uitgeoefend op het ontstaan van kaarten. De invloed van het koloniale verleden op het ontstaan van kaarten en de toegepaste geodetische methoden is nauwelijks bekend. Opeenvolgende Gouverneurs-Generaal en Ministers van Koloniën hebben hun stempel gedrukt op het beleid en zo mede de historische context bepaald voor de vraag naar kaarten. Aan de hand van de activiteiten van een elftal bestuurders zijn politieke en economische ontwikkelingen geschetst, die van invloed waren op het ontstaan van kaarten. Een hoofdvraag is de rol, die de Nederlandse aanwezigheid in Indonesië gespeeld heeft, voor de technische en de organisatorische ontwikkeling van de geodesie en het geodesie-onderwijs in Nederland in de periode 1850-1950. Landmeten en het waterpassen waren eeuwenlang een belangrijk onderdeel van de civiele, militaire en geodetische opleidingen in Nederland. Uitgezonden militaire en civiele experts waren vaak ingenieurs. Zij publiceerden hun technische resultaten in jaarverslagen, rapporten en artikelen. Hier laten we zien dat die Nederlandse aanwezigheid in Indonesië grote invloed heeft gehad op de geodesie en het geodesie-onderwijs in Nederland. In het kader van de wetenschapsgeschiedenis zijn de ontwikkelingen in de geodesie gevolgd als basis voor topografische en hydrografische opneming en kartering. Zoals vaak in de wetenschap werd lang uitgegaan van een paradigma, totdat dit niet meer houdbaar was en een nieuw paradigma ervoor in de plaats kwam. Een voorbeeld van een paradigmaverandering in Indië was het gebruik van triangulatie of driehoeksmeting. Die werd aanvankelijk gebruikt ter controle achteraf van de topografische opnemingen, maar werd later vooraf gebruikt als wiskundige basis voor die opnemingen. Drie terreinen zijn gekozen waar kaarten onontbeerlijk waren en waardoor ook veel kaarten ontstaan zijn: steden en openbare werken, spoor- en tramwegen en telecomverbindingen. De groei van de bevolking en de snelle ontwikkeling vanaf 1870 van de infrastructuur hebben de vraag naar kaarten enorm doen toenemen. De geodetische uitdagingen, die de basis voor kaarten vormden, zijn behandeld aan de hand van navigatie en plaatsbepaling, hydrografie, triangulatie, hoogtemeting en fotogrammetrie. Op enkele gebieden speelde Indië een voortrekkersrol en heeft Nederland van de opgedane ervaring kunnen profiteren. Verstorende factoren bij de metingen in de tropische omgeving weken nogal af van die in Nederland. Het onderzoek laat zien dat het tropische klimaat, de andere geografie, atmosferische refractie, schietloodafwijkingen, zwaartekrachtafwijkingen en kaart-projecties een geheel andere benadering dan in Nederland vergden. De geodetische activiteiten zijn beschreven aan de hand van uitgevoerde triangulaties en topografische opnemingen, die de basis voor kaarten vormden. De organisatie en werkwijze van de Topografische Dienst en het Kadaster, zowel in Nederlands-Indië als in Nederland, krijgen alle aandacht. Belangrijke personen en hun resultaten worden naar voren gehaald. Hydrografische activiteiten en de oceanografische expedities in het eilandenrijk, laten het grote belang zien van veilige vaarroutes en diepzee-onderzoek. Behalve topografische kaarten is ook het ontstaan van zeekaarten, luchtvaartkaarten en atlassen onderzocht. Aan de hand van een representatieve selectie uit duizenden vervaardigde kaarten, waarvan een deel als annex is opgenomen, wordt een beeld gegeven van de geleverde prestaties. Een globale vergelijking is gemaakt met initiële geodetische activiteiten in Frankrijk, Nederland, Duitsland, Groot-Brittannië en India. India was vergelijkbaar met Indië en werd door de Topografische Dienst in Batavia (nu Jakarta) op de voet gevolgd. Een vergelijking is gemaakt tussen Nederland en Nederlands-Indië voor enkele specifieke geometingen zoals astronomische waarneming, triangulatie, hoogtemeting, fotogrammetrie en hydrografie. Aan het geodesie-onderwijs, met name aan de TH Delft en TH Bandung, is uitvoerig aandacht besteed en de wisselwerking is daarin meegenomen. Vergelijking van studieboeken uit Europa en Indië laat zien dat het kennisniveau goed overeenkwam. De wetenschap in Nederlands-Indië, die op een hoog peil stond, heeft ook invloed op de Nederlandse wetenschap gehad. Zowel de uitwisseling van kennis aan de hand van publicaties en congressen, als de terugkeer van experts hebben hieraan bijgedragen. De conclusies zijn onderscheiden in drie categorieën: geometingen, personen en resultaten. Die hebben een nauwe relatie en tonen aan dat “Indonesië op de kaart” meer is dan een grafische voorstelling van de topografie of hydrografie. De andere lokale omstandigheden hebben in Nederland de geodesie-ontwikkeling en het onderwijs aanzienlijk verbreed. Het zijn echter de mensen geweest, die met bescheiden middelen de resultaten tot stand gebracht hebben. De grote hoeveelheid literatuur is daar getuige van.@en

The subject of this study is deformation analysis of the earth's surface (or part of it) and spatial objects on, above or below it. Such analyses are needed in many domains of society. Geodetic deformation analysis uses various types of geodetic measurements to substantiate statements about changes in geometric positions. Professional practice, e.g. in the Netherlands, regularly applies methods for geodetic deformation analysis that have shortcomings, e.g. because the methods apply substandard analysis models or defective testing methods. These shortcomings hamper communication about the results of deformation analyses with the various parties involved. To improve communication solid analysis models and a common language have to be used, which requires standardisation. Operational demands for geodetic deformation analysis are the reason to formulate in this study seven characteristic elements that a solid analysis model needs to possess. Such a model can handle time series of several epochs. It analyses only size and form, not position and orientation of the reference system; and datum points may be under influence of deformation. The geodetic and physical models are combined in one adjustment model. Full use is made of available stochastic information. Statistical testing and computation of minimal detectable deformations is incorporated. Solution methods can handle rank deficient matrices (both model matrix and cofactor matrix). And, finally, a search for the best hypothesis/model is implemented. Because a geodetic deformation analysis model with all seven elements does not exist, this study develops such a model. For effective standardisation geodetic deformation analysis models need: practical key performance indicators; a clear procedure for using the model; and the possibility to graphically visualise the estimated deformations. This study shows that key performance indicators can be derived from the method of hypothesis formulation and testing, and from rejection criteria. They can also stem from the description of the test quality by means of minimal detectable deformations. A clear procedure is possible, if an unambiguous way is provided to distinguish the observation noise, the deformation signal with zero mean in time, and the deformation trend from each other. The graphical visualisation, finally, demands clearly defined quantities that are sensitive only to the deformations of the object at hand and not to changes in, e.g., the reference system. In this study I propose a geodetic deformation analysis model, which is built around a least-squares adjustment model. Two adjustment models are developed in this study: one model uses geodetic measurements in the observation vector. In the other model this vector holds pre-computed coordinates, which follow from separate adjustments per epoch. The parameter vector holds, for both models, the final coordinates.  Both models yield the same adjustment results. The choice, which one to use, depends on the professional context in which the model is used. The developed geodetic deformation analysis model is shown to be effective in several use cases. These use cases are geodetic networks in 1D, 2D and 3D that have been measured in several epochs, and which are analysed with one of the two adjustment models, mentioned above. Moreover, the proposed analysis model not only possesses the seven necessary elements, mentioned before, it also has some additional advantageous characteristics. First, it is possible to define the S-basis of the geodetic network, used for deformation analysis, with points that are under influence of deformation. Secondly, there is no need for a separate analysis of reference and object points; they are analysed simultaneously. Thirdly, the deformation estimates of moving points are relative to all the other points of the same network (moving or not), not relative to an S-basis. These estimates are invariant for a change of S-basis, i.e. for an S-transformation. Finally, biases in geodetic measurements and deformation hypotheses can be tested simultaneously. The availability of key performance indicators, based on the analysis model and its characteristic elements as described in this study, and the definition of a statistically significant deformation, provided in this study, make a standardised procedure for geodetic deformation analysis possible. Thus a tool is available for the improvement of communication about geodetic deformation analysis. @en