For this Thesis a weighted spherical harmonic analysis is performed on the intensity distribution of Io's hotspots to find potential long wavelength patterns. Unfortunately, no definitive conclusion can be drawn as to whether the primary signal (Loki Patera) is caused by a long wavelength signal originating from deep within Io, or whether it is caused by a local phenomenon. This is because the spectral power associated with the analysis does not just have significant power in one or a few degrees. Instead all harmonic degrees return a strong signal. This has been checked up to at least degree 30 which is well into the shorter wavelengths.

Comparing the weighted spherical harmonic analysis of Io’s hotspot intensity distribution to an unweighted spherical harmonic analysis of the hotspot distribution (so without intensities), the location of the primary signal(s) is different between the two analyses, but both still point towards the asthenospheric heating model or magma ocean heating model as the explanation for Io’s heat flow pattern.

Railway transportation is crucial to reducing greenhouse gas emissions and meeting increasing global demand for passenger and freight transport. To maintain a reliable, high-capacity railway infrastructure, regular and accurate maintenance is necessary. The recent development of a Rail-based Track
Surveying System that can be mounted on any operational train, presents a comprehensive solution to acquire track geometry measurements while limiting track unavailability. The system is able to simultaneously acquire measurements of both the absolute- and relative track geometry using a combination of a GNSS / INS integrated navigation system and a laser ranging sensor. The measurement unit is able to obtain consistently accurate absolute track geometry measurements (σ2D = 8 [mm] (Wang et al.2019)) in areas with good GNSS signal reception. However, in areas with limited GNSS coverage, the accuracy of these measurements can fall below the requirements for rapid track inventory acquisition (3 [cm], p = 0.95 (Specht et al. 2016)). This thesis, developed and conducted in lose collaboration with Fugro, aims to improve the accuracy of the trajectory solution for rail-based track surveying systems in such limited GNSS environments.

At the time this research was performed, there was no ground truth or reference trajectory available to assess the accuracy of a trajectory solution. Therefore, the research first establishes quality metrics to provide a measure of the accuracy and certainty of the integrated GNSS/INS estimated trajectory solution. By nature of the data acquisition process of the RTSS, multiple runs, or trajectory estimates, are available of an arbitrary track segment. The observed cross-track trajectory spread (precision) provides a qualitative metric to assess the level of accuracy of multiple passes over the same track segment, given that the
individual measurements are unbiased. To quantify the cross-track trajectory
spread, the standard deviation and smallest circle radius are selected as statistical and absolute metrics.

Next, the research identifies the existence of unreliable or inaccurate GNSS positioning updates in the integrated trajectory solution by linking the cross-track trajectory spread to the Quality Control metrics of individual runs. The level of accuracy of the GNSS / IMU integrated trajectory solution was found to be decreased at track segments where one (or multiple) runs showed sustained periods of high (> 5) PDOP values. A decreased accuracy in the order of 10 [cm] was observed for the high PDOP GNSS positioning updates. Furthermore, these inaccurate position updates were weighted too heavily in the Loosely Coupled integration scheme, reducing the accuracy of the integrated GNSS/IMU
trajectory solution. To improve the accuracy and certainty of the integrated trajectory solution, the GNSS positioning updates in segments with sustained high PDOP values can be inactivated. Inactivating these high PDOP GNSS positioning updates, reduced the observed cross-track trajectory spread by
as much as c.50%.

The thesis provides valuable results for the improvement of the accuracy and certainty of GNSS/IMU trajectory determination in rail-based applications. Furthermore, the framework and data-analysis algorithm developed and presented in this thesis research could be used to quantify the effect of different
quality parameters and processing thresholds on the accuracy of the trajectory solution. The main conclusion and recommendation of this report - processing the trajectory against a tight PDOP constraint - leads to a trajectory estimate for a rail-based surveying application with improved accuracy and certainty. Moreover, recommendations for research implementation, further trajectory accuracy gains and continuation of this research are also presented in this report.

This thesis introduces a new approach to Glacial Isostatic Adjustment (GIA) modeling using Machine Learning (ML) techniques. The work addresses two main challenges – uncertainty in historical ice load history and the complexity of inverse problems – by developing two ML-based surrogate models (emulators) to rapidly estimate Relative Sea-Level (RSL) history and uplift rates from varying ice load histories, given a constant Earth model. The emulators are constructed using a Convolutional Neural Network (CNN) with U-Net architecture and spherical data representation, enabling an efficient, cost-effective approach to the GIA forward model. The performance of these emulators was evaluated in two separate experiments, displaying encouraging results in efficiency, accuracy, and versatility. The prediction performance exceeded existing models in computational speed and offers accuracy comparable to other GIA studies. The successful implementation of these emulators could advance GIA modeling by integrating ML, but enhanced resolution is needed for direct scientific application.

In the last few decades, a large increase in interest in space and particularly the Moon has taken place. The Moon is seen as a gateway to the rest of the Solar System. Missions to the Moon will inevitably lead to technological and scientific advancements. These would help in humanity’s mission to explore and develop habitats in the Solar System. Companies see economic opportunities in these places for activities such as the acquisition of rare Earth materials, as well as commercialising space travel. Furthermore, countries see these accomplishments
as a sort of international competition while also collaborating with other nations. The mission design presented here aims to facilitate these objectives by providing the necessary navigation support to any future mission on or around the Moon...

Nowadays, Mobile Mapping Systems (MMS) have been widely used in railway, with integrated Inertial Navigation System (INS)/Global Navigation Satellite System (GNSS) system as the common approach. For environments where GNSS signals become unavailable, additional aiding sources need to be considered to preserve the quality of measurement. Typically, in most applications, a Distance Measurement Indicator (DMI) is combined with the INS/GNSS system to ensure the desired accuracy. Nevertheless, as this approach is physically less feasible for railway, alternative solutions would be preferred. To bridge this gap, we investigate the applicability of Simultaneous Localization and Mapping (SLAM) integration with INS/GNSS for the case of a railway MMS. In particular, we aim to propose a solution for adapting a Monocular Visual (Inertial) SLAM method for railway application and further evaluate our solution using real-world data based on the RILA system (Fugro’s rail MMS). Accordingly, this dissertation consists of the following three research activities.
Firstly, we have conducted a literature review on the existing monocular Visual Inertial SLAM methods to identify the technique which fulfils the key requirements of the rail application. Considering the results of the study, we selected the ORB-SLAM3 method and proposed an end-to-end pipeline that covers all the phases to adapt it for RILA system.
Secondly, the impact of adapting ORB-SLAM3 technique on performance of the trajectory estimation has been evaluated using two criteria: Absolute Position Error (APE) and Relative Position Error (RPE). Accordingly, a case study using RILA dataset was developed for the experimental evaluations. In this case study, we have simulated a scenario in which the train entered the station, stayed there stationary for 1 minute, and then left the station slowly and manually inserted GNSS blockages before and after the station. Furthermore, a ground-truth trajectory was generated to evaluate the quality of the estimated SLAM-based trajectory. The results revealed that both APE and RPE increases with significant fluctuations in the first 15 seconds due to the lack of SLAM initialization time. Therefore, we introduced an strategy for fine-tuning the accuracy by allocating sufficient time for SLAM initialization phase. The APE and RPE were significantly reduced after fine-tuning and the expected estimated error at each time was equal to 4.3% of the travelled path length.
Finally, we presented the effect of using Zero Velocity Update (ZUPT) signals as aiding information on the accuracy of the estimated trajectory in the areas with poor GNSS coverage. Consequently, we manually inserted the extracted ZUPT signals to the INS/GNSS integration process and then compared the positional accuracy of the generated trajectories with and without this information. The results show that the estimated positional accuracy was improved by 30% with only 51 seconds of stationary condition in our case study.
Overall, based on the obtained results from the evaluations, it is possible to claim that our proposed ORB-SLAM3 technique has great potential to improve the estimated positional accuracy and in particular can be used as a standalone ZUPT detector in railway application.

Glacial Isostatic Adjustment (GIA) is a process which focuses on the deformations of the Earth due to changing ice sheets. It is an important study in Climate Sciences, gravimetric studies and Earth modelling. Studying GIA allows to contribute to a better understanding of the Earth’s composition, thanks to the testing of multiple Earth models, as well as a broader understanding of the Earth’s ice age cycles. In GIA research, spherical Earth models have been used for half a century. However, 3D Earth models distinguish themselves by using a 3D varying viscosity profile. The reason for this recent interest is that little is known with precision about the Earth’s mantle and deeper layers structure and that such a model was more difficult to create; the inclusion of three dimensional (3D) varying viscosity profiles have not yet been widely used in GIA studies in Greenland. Hence, to this day and to our knowledge, only two papers have made use of a laterally varying viscosity in order to study GIA in Greenland: Milne et al. (2018) and van der Wal and Xu, (2016).

The first novelty introduced by this Master Thesis is the use of the Olivine flow viscosity model, with a wet rheology, to study GIA in Greenland. The second main novelty in this Master Thesis, is the use of a unified ice history from 122000 years from present till 2019 in one GIA model; while using a resolution of 10 [𝑘𝑚], which is an improvement, compared to for instance Milne et al. (2018), Simpson et al. (2011) or Lecavalier et al. (2014) which use resolutions ranging from 15 to 75 [𝑘𝑚], which is found to still not be sufficient enough to properly model modern elastic and viscous deformation.

The following conclusions were made through analysing the final results. First, the simulations which use 3D viscosity models are more sensitive regionally and react, to ice load changes with larger amplitudes of solid Earth deflections in shorter time spans. Second, 3D varying viscosity models, with the same ice loads as the 1D varying viscosity models, have a pattern of deflection which is more explicitly linked to the changes in viscosity across Greenland, whereas the 1D viscosity profiles deflection rates are clearly positive in the present day on land and negative in the sea, and hence are more explicitly linked to the coastal limits of Greenland. Last, the inability of the model to properly model elastic uplifts in recent times, is made evident by the constant under estimation of total uplift rates.

Uncertainty in ice sheet modelling affects centennial and longer time-scale projections of the Greenland Ice Sheet's (GrIS) sea level contribution. One source of this uncertainty is the interaction between the ice sheet’s evolution and the Earth’s deformation in response to changes in the applied surface loading as the ice sheet waxes and wanes. Such deformation, Glacial Isostatic Adjustment (GIA), causes a vertical displacement of the ice sheet’s surface which affects temperature dependent precipitation and ice ablation. The significance of this feedback mechanism depends on the magnitude of GIA which is dependent on the mantle’s viscosity. Studies find that the sub-Greenland mantle viscosity varies in three dimensions which leads to a spatially varying rate of GIA. Results obtained with an ice sheet model coupled with an Earth model including 3D variations in sub-Greenland viscosity illustrate its significant effect on the GrIS’ modelled evolution by affecting both elevation-melt and elevation-precipitation feedback mechanisms.

During its thirteen-year long mission in the Saturnian system, the Cassini spacecraft routinely used Titan, Saturn’s largest moon, for performing its gravity assists. The problem of determining the gravity field of Titan by performing a precise fit of Cassini’s orbit to the available Doppler tracking data was reviewed in this study. The knowledge of the gravity field of Titan can be used to constrain the moon’s internal structure and composition, providing clues about its formation process and the properties of an internal ocean (Grasset et al., 2000). Previous solutions obtained by Durante et al. (2019) and van Noort (2021) were respectively found to have inconsistencies regarding the reported small uncertainties given the noise level of the Doppler measurements and the estimation of an unfeasible negative value for the second-degree Love number k₂. It was demonstrated in the present work that this last parameter should be estimable. Here, the data from the ten Titan flybys considered in those studies was analysed and emulated by using a relativistic model for Doppler measurements in search of ways of improving the accuracy of the gravity field solution. Both the GEODYN (McCarthy et al., 2015) software from NASA GSFC and Tudat libraries (see appendices in Dirkx et al., 2019) developed by the Astrodynamics and Space Missions department at TU Delft were used to investigate the nature of this gravity determination problem and compare the results against the previous solutions. A model mismatch in Doppler in the order of 10² mHz was found between the estimation setups with GEODYN and Tudat. In the search for the source of the mismodelling, it was tested that the empirical accelerations, measurement biases, measurement timing and the spherical harmonics of Saturn have a great influence on the solution and residuals. Thus, they should be reviewed with care for future estimation efforts. It was proven that the flyby geometry is not favourable for resolving the dipole field spherical harmonics coefficients, especially J₂, C₂₂ and k₂, which reveal information about the tidal interactions from Saturn on Titan. They were found to be highly correlated and, when simulating equivalent noises to those found in the previous research, presented similar uncertainties to those obtained by van Noort (2021), but large in relation to the ones determined in Durante et al. (2019). Nevertheless, there are some prospects of estimating the dipole coefficients without the need of adding constraints on the solution, although the search for well grounded constraints is recommended and necessary when pursuing a more accurate solution. The power of fully simulated gravity field estimations as a means for addressing the quality of the available real data and verifying models and constrains, has been manifested throughout this study.

Of the four Galilean satellites the only one without ice is Io. While it is possible that Io never contained any ice the starting point of this research work is an icy Io. As present-day Io does not contain any ice, icy Io must have lost its ice through some sort of ice loss mechanism. In this work the assumed ice loss mechanism is geysers driven by tidal heating. Tidal dissipation of sufficient magnitude is able to melt part of an icy layer creating a subsurface ocean and is also able to crack the overlying icy shell. The subsurface ocean then acts as a reservoir from which water vapor molecules and icy grains accelerate upwards through the cracks and are erupted from the surface. Erupted material with a sufficient velocity is able to escape from icy Io resulting in ice loss.

Within a Protoplanetary disk (PPD), planets form from micron sized particles, but what are the processes taken for planet formation? How does the evolution of micron sized particles via settlement and coagulation lead to the gigantic planets as the ones in our Solar System? This thesis explores the planet formation process of pebble accretion which is a planet accretion model involving the accretion of smaller bodies onto larger planetesimals. The evolution of micron sized particles into millimetre – centimetre sized pebbles are discussed. These particles will experience growth via settlement and coagulation, radial drift before acting as reservoir for planet cores to accrete and grow from. From the results, it is found that planet formation via pebble accretion is more efficient in the outer regions of the Solar System, where pebble formation was favoured and resulted in smaller inner planets and larger ice giants.

The Indian Space Research Organisation(ISRO) plans to equip future satellites of its Indian Nano Satellite(INS) with COTS dual frequency receivers in order to let them contribute to various scientific research opportunities. This thesis develops a test framework for Commercial Of The Shelf (COTS) Global Navigation Satellite System (GNSS)receivers on Nano satellites of the Indian Space Research Organisation(ISRO) to be used for scientific applications. This thesis aims to provided answer to the suitability of this data for scientific application. We have analyzed that the current generation Skytraq single frequency receiver, mounted in previous INS-1A to INS-1C missions, has with an accuracy in the meters range insufficient position accuracy to be used for scientific applications. Nevertheless, based on historical mission experiences and design constraints, a receiver-antenna system selection has been executed. Using this system as an example configuration, a test framework has been setup to analyze influential design and system configuration parameters influence on the GNSS receivers for future missions. The test setup consist of a series of static tests that enable to research the hardware configuration, such as the influence of a ground plane, and the data processing options, such as filters for the data and the choice of atmospheric models. It is complemented with a dynamic analysis of the receiver simulated performance in orbit using a GNSS simulator. Multiple data series were obtained for each individual test of the framework. These data series were analyzed with a developed data handling protocol in which multiple data processing software packages were used. In order to obtain comparable results in all test series, average deviations of the position fixes in the test periods were calculated and analyzed. This leads to a number of conclusions: The current antenna mounting on INS-1C is less than optimal and a ground plane would enhance the antenna performance with 20%. The raw data are essential for scientific experiments. However, they can most likely be limited to those obtained from GPS satellites excluding GLONASS and other GNSS constellations. It does pay off to include low viewing angle measurements for optimal results. The ionospheric models are indispensable to achieve sub meter accuracy with single frequency receivers.

The evolution of ice loads during the last Ice Age causes an ongoing Earth response with deformations and stress fields. The viscosity of the mantle depends on stresses, therefore the model stresses should be combined with ambient stresses such as due to mantle convection. This combination has been successfully simulated in the FEM software ABAQUS.

At each timestep background stresses are added to existing component and the Mises stress is recalculated to be used in a custom creep law. This leads to a new viscosity leading to different stress components, which is solved an iterative procedure.

This work shows that the initial model provided can be adapted to simulate this iterative process with a loop inside each timestep of the computation. Results show that stresses increase with time while deformations and viscosity decrease, an opposite trend compared to a non-ambient stresses case.

It has been shown that glacially induced decompression rates under Vatnajökull cause an increase in mantle melt and enhancement in volcanic activity. Eruptions under ice can form tuyas, that can be used to constrain past ice sheet thickness. Several mountains in the Martian South Polar Region qualify as tuyas, but their exact origin is still unknown. In this study we reconstruct a palaeo ice sheet from the height and spatial distribution of these tuyas and study glacially induced decompression rates within the Martian mantle.
In a finite element model we use the reconstructed ice sheet to constrain the surface pressure load and test different lithosphere thicknesses and linear deglaciation periods. We find a general decrease in decompression rates over depth and time. Results show that a decompression rate equal to the one induced by present-day deglaciation of Vatnajökull occurs at a lower depth inside the Martian mantle. Given that the mantle temperature is close to the solidus at this depth and magma ascent velocity is sufficiently high, mantle unloading due to ice melt could have contributed to the formation of the tuyas in the Martian South Polar Region. Our study proposes present-day deglaciation of Vatnajökull as a potential analogue for processes related to deglaciation on Mars.

By analysing spectra of meteors ablating in the atmosphere, one can infer the composition of their parent bodies (asteroids and comets). A challenge to the accurate composition inference comes from external factors: factors other than the parent body composition, which affect meteoroid-atmosphere interactions and hence influence meteor spectral appearances. External factors considered here were meteoroid entry speeds, ablation temperatures and yearly meteoroids' interaction in space. This research aimed to assess to what degree these external factors influence the appearance of meteor spectra and meteoroids’ composition retrieval from them.

The analysis revealed a strong correlation between meteors' entry speeds and elements’ number densities; number densities of meteoric elements showed a proportional decrease with speed. Moreover, the study concluded that increases of meteor spectra line intensities with height strongly correlate with increase in the ablation temperature. Finally, significant changes in meteoroid composition were seen among meteors generated from the same parent body but observed over different years.

Saturn's largest natural satellite, Titan, is an icy moon expected to harbour a liquid sub-surface water ocean capable of habiting extra-terrestrial life. The spherical harmonic expansion of the gravity field and the tidal Love number k2 can be used to estimate densities, depths, and phases of different layers from Titan’s interior structure, granting insight on the sub-surface ocean and its habitability. Recent research has determined the spherical harmonic expansion of the gravity field up to degree five including the estimation of Titan’s tidal Love number k2. This work estimates the spherical harmonic gravity field of Titan up to degree three through a multi-arc batch weighted least squares approach, with fundamental differences from previous research. We include observation biases and empirical accelerations for estimation in our dynamic force model and apply no constraints on the gravity and tidal parameters for estimation. Previous research claims the applied global constraints do not constrain the solution, yet an independent estimation of the gravity and tides of Titan yields significantly different results: high correlation between global parameters results in the inability to determine a realistic k2 Love number. We refrain from applying any global constraints to the gravity and tidal parameters, as there exists no a priori information on these parameters to apply a physical and unbiased constraint.

NASA's ICE, Cloud and Land Elevation Satellite-2 (ICESat-2) has been measuring the topography of the Earth's surface since its launch in September 2018. Equipped with a single instrument, namely, the Advanced Topographic Laser Altimeter System (ATLAS), ICESat-2 is able to acquire the along track vertical profiles of its laser footprints. While satellite based land classification has traditionally been performed with the use of multi-spectral data, which doesn't consider the vertical structure of the surface in question, the three-dimensional Light Detection and Ranging (LiDAR) product provided by ATLAS allows for the observation of the vertical structure of the illuminated surface. This provides information for the discrimination of surfaces that are only distinctly different from one another in this dimension, such as different types of vegetative species. Moreover, a greater understanding of how the signal interacts with different land types will benefit current and future users of the data. This study presents a first look at the potential of the base scientific data set provided by ATLAS, "ATL03", as a means of land type classification. Features extracted from ATL03 vertical profiles are used to classify multiple land types in The Netherlands, namely, "Artificial Surfaces", "Agricultural Areas", "Forest and Semi-Natural Areas", "Wetlands" and "Water Bodies". 100m grid cells were classified and validated with the CORINE land cover database. The overall classification accuracy was 71.2%, however, after a visual inspection of the misclassification errors it was found that that the actual accuracy was a minimum of 5.5% higher, that is, 76.7%. 51 features were created to discriminate between land classes and their importance per class was analysed. In general, simple statistical parameters, such as the standard deviation and percentile ranges worked well in distinguishing between classes. For the classes with a greater vertical range, such as "Artificial Surfaces", features that described the height and prominence of its scattering surfaces were most important.

The subsurface of Mars is impossible to measure directly, yet it has been the subject of many studies. An understanding of the subsurface of Mars would yield large amounts of information on the history of the planet. Two of the tools available to indirectly interact with the Martian subsurface, in particular the lithosphere, are the gravity and topography signals of the planet. These two datasets can be combined using a variety of geological theories in order to investigate the subsurface. In this study, an isostatic model (Airy-type) and two flexural isostatic models (an infinite plate model and a thin shell model) will be the methods of choice. A distinction is made between isotropic or global models, which use one set of physical parameters for the entire planet, and anisotropic or multi-region models which allow for regional variation in physical parameters. The goal of this study is to investigate the performance of the novel thin shell model as compared to the older infinite plate model.

To investigate this, the theory behind each model is explained, after which the models are validated using results from literature. Several regions of interest are defined, mostly among large geological formations or gravity anomalies. Two parameters are chiefly investigated: the average thickness of the lithosphere and the lithospheric elastic thickness, which is a measure of the strength of the lithosphere. Each model is run globally for a variety of these two parameters, and the best fitting parameters are identified. After this, the planet is split into different regions with their own physical parameters. The first study is a dichotomy study which splits the planet into a northern and southern hemisphere, aimed at characterizing the disparity between the Martian north and south. After this, each region is assigned its best fitting physical parameters and the regions are combined into a 'global' regional model. A best fitting multi-region model is obtained via manual observation of the results and adjustment of the inputs until a visual best fit is achieved.

The results are then discussed. A key takeaway is that better methods of judging the performance of models without human visual inspection of their results is necessary in order to realize the full potential of the flexural isostasy models presented in this study. The lack of suitable methods leads to a manifold of best fitting solutions for many of the problems modelled in this study, hindering firm conclusions about the subsurface of Mars. Having said this, global average lithospheric values of about 200 km combined with very low effective lithospheric elastic thickness values of 0 to 40 km are the best fits found in this study. Literature values are typically lower, but this can partially be explained by differences between the flexural isostasy models in this study and the models from literature. Regionally there are large variations, with some features (Hellas basin, Alba mons) being isostatically compensated, others being supported by locally strong lithospheres (much of the Tharsis region), and others resting on buried mass anomalies that cannot be explained with the models in this study (Isidis planitia, Argyre basin). In a dichotomy study, the best fitting values were found for a northern lithosphere zero to ten kilometers thinner than the southern lithosphere. In general, the thin shell model is more sensitive to nonzero lithospheric elastic thickness values, providing very strong lithospheres at low elastic thicknesses. This is due to its aggressive flexural response function's filtering of higher spherical harmonic degree signals. The thin shell models yields higher residuals in the global analyses, but lower residuals in the multi-region studies. At the same time, 80% of the error in all models can be attributed to spherical harmonic degrees between 1 and 10. These signals are likely not caused by flexural isostasy, and require models incorporating more physics (mantle plumes, mass anomalies, etc) to be explained.

The Antarctic ice sheet is a complex system highly influenced by global and local processes and characteristics including a varying bedrock elevation and structure of the solid Earth and a changing climate. Sea level rise has a high impact on society and the improvement of forecasts are vital to generate both adaptation and mitigation strategies. A recent comparison of 15 ice sheet models projected that the Antarctic Ice Sheet could contribute -7.8 to 30 centimeters of sea level rise between 2015 and 2100, meaning that sea level rise could increase a lot although the uncertainty is high. To better predict the future of the AIS, more accurate simulations of the evolution of the AIS are needed. The Antarctic ice sheet consist of three main components: grounded slow-moving ice, fast flowing ice streams or outlet glaciers and floating ice shelves. Over glacial-interglacial cycles, the evolution of an ice sheet is influenced by Glacial Isostatic Adjustment (GIA) via two negative feedback loops. First, vertical bedrock deformation due to a changing ice load alters ice-sheet surface elevation. Second, bedrock deformation will change the location of the grounding line of the ice sheet. GIA is mainly determined by the viscosity of the interior of the solid Earth which is radially and laterally varying. Underneath the Antarctic Ice Sheet (AIS), there are relatively low viscosities in West Antarctica and higher viscosities in East Antarctica, which affect the response time of the above-mentioned feedbacks. However, most ice-dynamic models do not consider lateral variations of viscosity in the upper mantle in GIA feedback loops when simulating the evolution of the AIS. The main research question of this study is: •What is the effect of the interaction between Glacial Isostatic Adjustment and ice sheet dynamics on the Antarctic Ice Sheet growth during the last glacial cycle? This study presents a new method to investigate 3D GIA feedback effects in detail at any chosen period during the last glacial cycle. The method is applied using ANICE and a 3D GIA FEM model. This led to the development of a fully coupled ice dynamic-3D GIA model with coupling timesteps of 1000 and 5000 years. Following the new method, the model computations alternate between the ice-sheet model, ANICE, and a 3D Finite Element Method model until convergence of the ice thickness occurs at each timestep. We simulate the evolution of the AIS from 120 000 years to 115 000 years before present, considering 1D and non-linear 3D rheologies. The results of the coupled model are discussed in detail for the period 120,000 years to 115,000 years before present with a focus on the Siple Coast and the Ross Ice Shelf. The maximum difference between the uncoupled deformation (iteration 1) and the coupled deformation (average between the last two iterations) for the period 120,000 to 115,000 years BP is 3 to 8 mm per year, depending on the viscosity of the upper mantle. The maximum difference in ice thickness at 115,000 years BP is 50 meters close the Ronne Ice Shelf and the Ross Ice Shelf. The grounding line position differs up to 80 meters when applying the coupling method compared to the uncoupled result. The increases in deformation using a 3D wet rheology with a grain size of 10 mm are highest at the Siple Coast, the Ronne Ice Shelf, and several other locations along the grounding line of the AIS. The results of this study emphasize the importance of the 3D GIA feedback effects when simulating the evolution of the AIS during the last glacial cycle. Therefore, the GIA feedback effects should be taken into account in future studies.

Io is Jupiter's innermost Galilean satellite and the most volcanically active body in the Solar System. Its volcanism is driven by tidal heating generated by its interaction with Jupiter and maintained by other Galilean satellites. The tidal forces acting on Io also cause significant stresses on its interior. It is investigated if tensional stresses play a significant role in the formation of volcanic centers on Io. On a global scale, it is investigated if the locations of maximum tensile stress coincide with the locations of maximum volcanic activity. On a local scale, it is investigated if chains of Io's volcanoes follow the directions of the tensile stresses. The results on a global and local scale are shown to be consistent with the hypothesis that tensional stresses play a significant role in the formation of volcanic centers on Io. However, tensional stresses alone are insufficient for the formation of volcanic centers.