06 Fakultät Luft- und Raumfahrttechnik und Geodäsie
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/7
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Item Open Access Water level monitoring at SAPOS stations through GNSS-IR : a case study at the station Iffezheim(2023) Wagner, Sven B.The German SAPOS-Network comprises approximately 270 permanent GNSS receivers, capturing signals from Global Navigation Satellite Systems such as GPS, GLONASS, Galileo, and BeiDou. Primarily employed for generating kinematic, mathematical, and physical models within their respective regions, these receivers hold untapped potential for alternative applications. GNSS receivers capture multipath errors, typically considered unwanted interferences resulting from signal reflections off surfaces beneath the antenna. Despite their potential to adversely affect data precision, these interferences contain valuable information about the reflecting surface. As satellites pass through the receivers’ field of view at specific elevation angles, the interference between the direct and reflected signals leads to constructive and destructive patterns. This phenomenon occurs due to variations in signal phase between the direct and reflected signal, enhancing or dampening the signal strength. These variations in signal strength are captured in the satellites Signal-to-Noise Ratio (SNR) data. Spectral analysis of the SNR data can be used to determine the frequency of the interference pattern. Combining this frequency with the corresponding signal wavelength and satellite elevation angles allows the calculation of the vertical distance between the antenna phase centre and the reflecting surface on Earth. This method, known as GNSS Interferometric Reflectometry (GNSS-IR), provides a valuable means of monitoring surface information, including soil moisture, snow depth, and water levels. At SAPOS stations near rivers and water bodies, GNSS-IR offers a cost-effective, accessible, and innovative opportunity to gather water level information using the already existing infrastructure. This research explores the potential of GNSSIR for water level monitoring at SAPOS stations focusing on the Iffezheim station along the Rhine River near the City of Karlsruhe in southern Germany.Item Open Access A MATLAB toolbox for the Scintrex CG-5 gravimeter at GIS(2017) Gu, SiyunThis thesis is about a MATLAB toolbox for the Scintrex CG-5 gravimeter. The aim of this toolbox is to offer a basic data process for gravity measurement, which is compatible for most applications in geodesy. In particular, the toolbox covers: 1. data selection, 2. adjustment, 3. gravity gradient computation, 4. gravity visualization, 5. calibration factor estimation. A graphical user interface enables users without deeper programming knowledge to operate this toolbox and obtain the results like adjusted values or figures.Item Open Access Dynamic water masks from optical satellite imagery(München : Verlag der Bayerischen Akademie der Wissenschaften, 2019) Elmi, Omid; Sneeuw, Nico (Prof. Dr.-Ing.)Investigation of the global freshwater system has a vital role in critical issues e.g. sustainable development of water resources, acceleration of the hydrological cycle, variability of global sea level. Measurement of river streamflow is vital for such investigations as it gives a reliable estimate of freshwater fluxes over the continents. Despite such importance, the number of river discharge gauging station has been decreasing. At the same time, information on the global freshwater system has been increasing because of various types of ground observations, water-use information and spaceborne geodetic observations. Nevertheless, we cannot answer properly crucial questions about the amount of freshwater available on a certain river basin, or the spatial and temporal dynamics of freshwater variations and discharge, or the distribution of world’s freshwater resources in the future. The lack of comprehensive measurements of surface water storage and river discharge is a major impediment for a realistic understanding of the hydrological water cycle, which is a must for answering the aforementioned questions. This thesis aims to improve the methods for monitoring the surface extent of inland water bodies using satellite images. Satellite imaging systems capture the Earth surface in a wide variety of spectral and spatial resolution repeatedly. Therefore satellite imagery provides the opportunity to monitor the spatial change in shorelines, which can serve as a way to determine the water extent. Each band of a multispectral image reveals a unique characteristic of the Earth surface features like surface water extent. However selecting the spectral bands which provide the relevant information is a challenging task. In this thesis, we analyse the potential of multispectral transformations like Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA) to tackle this issue by condensing the information available in all spectral bands in just a few uncorrelated variables. Moreover, we investigate how the change between multispectral images at different epochs can be highlighted by using the transformations. This study proposes an automatic algorithm for extracting the lake water extent from MODIS images and generating dynamics lake masks. For improving the accuracy of the lake masks and computational efficiency of the algorithm, two masks are defined for limiting the search area. The restricting masks are developed according to DEM of the surrounding area together with a map of the long-term variation of pixel values. Subsequently, an unsupervised pixel-based classification algorithm is applied for defining the lake coastline. The algorithm particularly deals with the challenges of generating long time series of lake masks. We apply the algorithm on five lakes in Africa and Asia, each of which demonstrates a challenge for lake area monitoring. However in the validation section, we demonstrate that the algorithm can generate accurate dynamic lake masks. Rivers show diverse behaviour along their path due to the contribution of different parameters like gradient of the elevation, river slope, tributaries and river bed morphology. Therefore for generating accurate river reach mask, we need to consider additional sources of information apart from pixel intensity. The region-based classification algorithm that we propose in this study takes advantages of all types of available information including pixel intensity and spatial and temporal interactions. Markov Random Fields provide a flexible frame for interaction between different sources of data and constraint. To find the most probable configuration of the field, the Maximum A Posteriori solution for the MRF must be found. To this end, the problem is reshaped as an energy minimization. The energy function is minimized applying graph cuts as a powerful optimization technique. The uncertainty in the graph cuts solution is also measured by calculating the minimum marginal energies. The proposed method is applied to four rivers reaches with different hydrological characteristics. We validate the obtained river area time series by comparing with in situ river discharge and satellite altimetric water level time series. Moreover, in this study, we present river discharge estimation models using the generated river reach masks. Our aim is to find an empirical relationship between the average river reach width and river discharge. The statistics in the validation periods support the idea of using river width-discharge prediction models as a complementary technique to the other spaceborne geodetic river discharge prediction approaches.Item Open Access Analyzing the spatio-temporal behavior of Poyang Lake using Google Earth Engine(2020) Schneider, Nicholas M.Poyang Lake, China’s largest freshwater lake, undergoes a yearly repeating cycle of drastic inundation and subsequent considerable shrinkage. Essentially, as a result of local precipitation and feedings from its tributaries, as well as a natural water exchange with the Yangtze River, Poyang Lake experiences such dimensional fluctuations on a annual and interannual scale. The ongoing change plays a significant role for the surrounding anthropogenic activity and wildlife. Despite being considered as a hydrological phenomenon, the dynamics of this Chinese water body set up a hurdle for any accurate documentation of its regime and therefore remains insufficiently studied upon to this day. Further impeding the comprehension of Poyang Lake’s behavior is the near inaccessibility and nonexistence of in situ data, such as water level measurements and bathymetric maps. Consequently, this study, driven by its aim to analyze the spatio-temporal behavior of Poyang Lake, focuses solely on satellite observations. Making use of the cloud computing platform, Google Earth Engine, image time series are used from Landsat-8 and Sentinel-1 datasets in order to map Poyang Lake’s spatio-temporal behavior on an annual and interannual scale. Produced from the Landsat-8 dataset, results show that only under circumstances, do techniques, such as the combination of visible and infrared bandsand the calculation of the Normalized Difference Water Index, provide a reasonable approach for the delineation of continental water bodies. For the study on Poyang Lake, a water body subject to humid climate and thus frequent cloud coverage, these techniques do not apply very well. With synthetic aperture radar observations from the Sentinel-1 dataset, dynamic water masks, involving the removal of certain elevated areas and the classification of water from thresholding, could be generated. The resulting binary water masks are then merged with a digital terrain model to create monthly maps of the study area. The results show an evident correlation between this study’s visual and numeric findings. Although the results are nearly impossible to compare with any in situ data, they show a trend that annually occurs in Poyang Lake’s hydrological regime. In particular, they reveal the cycle of drastic inundation in rainy summer months and considerable shrinkage in dry winter months, especially when examining the years prior to 2019. Using SAR imagery for continental water body delineation, particularly in humid climates, proved to be a suitable technique and should be considered for future documentations of the lake.Item Open Access Analytical solutions for gravitational potential up to its third-order derivatives of a tesseroid, spherical zonal band, and spherical shell(2023) Deng, Xiao-Le; Sneeuw, NicoThe spherical shell and spherical zonal band are two elemental geometries that are often used as benchmarks for gravity field modeling. When applying the spherical shell and spherical zonal band discretized into tesseroids, the errors may be reduced or cancelled for the superposition of the tesseroids due to the spherical symmetry of the spherical shell and spherical zonal band. In previous studies, this superposition error elimination effect (SEEE) of the spherical shell and spherical zonal band has not been taken seriously, and it needs to be investigated carefully. In this contribution, the analytical formulas of the signal of derivatives of the gravitational potential up to third order (e.g., V , Vz, Vzz, Vxx, Vyy, Vzzz, Vxxz, and Vyyz) of a tesseroid are derived when the computation point is situated on the polar axis. In comparison with prior research, simpler analytical expressions of the gravitational effects of a spherical zonal band are derived from these novel expressions of a tesseroid. In the numerical experiments, the relative errors of the gravitational effects of the individual tesseroid are compared to those of the spherical zonal band and spherical shell not only with different 3D Gauss–Legendre quadrature orders ranging from (1,1,1) to (7,7,7) but also with different grid sizes (i.e., 5∘×5∘, 2∘×2∘, 1∘×1∘, 30′×30′, and 15′×15′) at a satellite altitude of 260 km. Numerical results reveal that the SEEE does not occur for the gravitational components V , Vz, Vzz, and Vzzzof a spherical zonal band discretized into tesseroids. The SEEE can be found for the Vxxand Vyy, whereas the superposition error effect exists for the Vxxzand Vyyzof a spherical zonal band discretized into tesseroids on the overall average. In most instances, the SEEE occurs for a spherical shell discretized into tesseroids. In summary, numerical experiments demonstrate the existence of the SEEE of a spherical zonal band and a spherical shell, and the analytical solutions for a tesseroid can benefit the investigation of the SEEE. The single tesseroid benchmark can be proposed in comparison to the spherical shell and spherical zonal band benchmarks in gravity field modeling based on these new analytical formulas of a tesseroid.Item Open Access Analysis of river surface slope using ICESat-2 satellite altimetry(2022) Bao, JingyiItem Open Access The optimal regularization and its application in extreme learning machine for regression analysis and multi-class classification(2018) Qian, KunExtreme Learning Machine (ELM) proposed by Huang et al. (2006) is a newly developed single layer feed-forward neural network (SLFN). It is attractive for its high training efficiency and satisfactory performance, especially when dealing with a large amount of data, which are often in high-dimensional space. However, current ELM cannot solve the over-fitting problem among other several problems. While minimizing residuals of output errors for the training data, it tends to generate an over-fitting model, whose generalization ability is relatively weak. Even if the model fits the training data perfectly, it performs unsatisfactory for the testing data. In training process, we aim to minimize residuals of output errors of training data. It tends to generate an over-fitting model, which has poor generalization ability. The model maybe fit the training data perfectly, but performs badly in testing data. Furthermore, in order to improve accuracy, the traditional way is increasing the number of hidden-layer neurons, but excessive hidden-layer neurons result in an ill-posed normal matrix and a model which is over sensitive to the change of the training data. In such case, the performance of ELM is significantly affected by the outliers in the training data. In order to overcome these problems, we apply the regularization to the original ELM. In this study, the A-optimal design regularization is performed to improve the generalization ability and stability of ELM. The performance of ELM with the A-optimal design regularization will be evaluated through two main applications, respectively, regression analysis and satellite image multi-class classification.Item Open Access GPS time-variable seasonal signals modeling(2015) Chen, QiangSeasonal signals (annual plus semi-annual) in GPS time series are of great importance for understanding the evolution of regional mass, i.e. ice and hydrology. Conventionally these signals (annual and semi-annual) are derived by least-squares fitting of harmonic terms with a constant amplitude and phase. In reality, however, such seasonal signals are modulated, i.e. they will have a time-variable amplitude and phase. Recently, Davis et al. (2012) proposed a Kalman filter based approach to capture the stochastic seasonal behavior of geodetic time series. In this study, a non-parametric approach, singular spectrum analysis (SSA) is introduced. It uses time domain data to extract information from short and noisy time series without prior knowledge of the dynamics affecting the time series. A prominent benefit is that obtained trends are not necessarily linear and extracted oscillations can be amplitude and phase modulated. In this work, the capability of SSA for analyzing time-variable seasonal signals from GPS time series is investigated. We also compare SSA-based results to two model-based results, i.e. least-squares analysis and Kalman filtering. Our results show that singular spectrum analysis could be a viable and complementary tool for exploring modulated oscillations from GPS time series. Based on the SSA-derived seasonal signals, we look into the effects of the input noise variances in the framework of Kalman filtering. Two Kalman filtering based approaches with different process noise models are compared over 79 GPS sites. We find that the basic Kalman filtering technique with the input noise model suggested by Davis et al. (2012) turns out to be optimal.Item Open Access Understanding the limitations of Sentinel-3 inland altimetry through validation over the Rhine River(2022) Schneider, Nicholas M.Satellite altimetry is developing into one of the most powerful measurement techniques for long-term water body monitoring thanks to its high spatial resolution and its increasing level of precision. Although the principle of satellite altimetry is very straightforward, the retrieval of correct water levels remains rather difficult due to various factors. Waveform retracking is an approach to optimize the initially determined range between the satellite and the water body on Earth by exploiting the information within the power-signal of the returned radar pulse to the altimeter. Several so-called retrackers have been designed to this end, yet remain one of the most open study areas in satellite altimetry due to their crucial role they play in water level retrieval. Moreover, geophysical properties of the stratified atmosphere and the target on Earth have an effect on the travel time of the transmitted radar pulse and can amount to severalmeters in range. In this study we provide an overall analysis of the performances of the retrackers dedicated to the Sentinel-3 mission and the applied geophysical corrections. For this matter, we focus on nine different locations within the Rhine River basin where locally gauged data is available to validate the Sentinel-3 level-2 products. Furthermore, we present a reverse retracking approach in the sense that we use the given in-situ data to determine the offset to each altimetry-derived measurement of every epoch. Under the assumption that these offsets are legitimate, they can be seen as an a-posteriori correction which we project onto the range and thus on a waveform level. Further analyses consist in the investigation of the relationship these a-posteriori corrections have to the waveform properties of the same epoch. Later, the question whether the a-posteriori corrections to the initial retracking gates are appropriate for the retrieval of correct water levels, drives us to assign a probability to each and every bin of the waveform. Following this idea, we design stochastic-based retrackers which determine the retracking gate for water level retrieval from the bin with the highest probability assigned to it. To distribute the probabilities across all bins of the waveform, we consider three empirical approaches that take both the waveform itself and its first derivative into account: Addition, multiplication and maximum of both signals. For all three of the new retrackers, we generate the water level timeseries over the aforementioned sites and validate them against in-situ data and the retrackers dedicated to the Sentinel-3 mission.Item Open Access Bahnstörungen durch Ozeangezeiten(2007) Daubrawa, JulianDiese Arbeit beschäftigt sich mit dem Aspekt der Ozeangezeiten in der Satellitenbahnberechnung. Durch Gravitationskräfte des Mondes, der Sonne und der Planeten kommt es zu Massenverlagerungen in den Ozeanen. Diese Massenverlagerungen haben eine Änderung bzw. Störung des Gravitationspotenzials der Erde zur Folge. Diese Störung hat Auswirkungen auf die Bahn eines Satelliten in Form von Störbeschleunigungen. In dieser Arbeit wird die Geschichte der Ozeangezeiten und die Verwendung der Ozeangezeitenmodelle dargestellt. Es werden die Prädiktionsmethoden für die Veränderung der Meeresoberfläche vor den ersten Modellen für Ozeangezeiten erläutert. Ebenfalls wird auf die verschiedenen Klassen der Modelle eingegangen. Ein weiterer Punkt, der in dieser Arbeit Beachtung findet, ist die Theorie der Admittanz. Es werden die Auswirkungen der Ozeangezeiten auf die Satellitenbahnberechnung und auf die Koeffizienten des Schwerefeldmodells untersucht. Die Satellitenbahnberechnung konzentriert sich auf den GOCE-Satelliten und die GPS-Satelliten. Zusätzlich hierzu werden die Auswirkungen der Ozeangezeiten auf einen Punkt auf der Erdoberfläche über verschiedene Zeiträume und auf einen Punkt in verschiedenen Höhen über der Erdoberfläche berechnet. In den Fällen, in denen es interessant ist, werden zwei Ozeangezeitenmodelle miteinander verglichen.