06 Fakultät Luft- und Raumfahrttechnik und Geodäsie

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/7

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Open Access
Advancing ADAS perception : a sensor-parameterized mmplementation of the GM-PHD filter
(2024) Bader, Christian; Schwieger, Volker
Modern vehicles equipped with Advanced Driver Assistance Systems (ADAS) rely heavily on sensor fusion to achieve a comprehensive understanding of their surrounding environment. Traditionally, the Kalman Filter (KF) has been a popular choice for this purpose, necessitating complex data association and track management to ensure accurate results. To address errors introduced by these processes, the application of the Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter is a good choice. This alternative filter implicitly handles the association and appearance/disappearance of tracks. The approach presented here allows for the replacement of KF frameworks in many applications while achieving runtimes below 1 ms on the test system. The key innovations lie in the utilization of sensor-based parameter models to implicitly handle varying Fields of View (FoV) and sensing capabilities. These models represent sensor-specific properties such as detection probability and clutter density across the state space. Additionally, we introduce a method for propagating additional track properties such as classification with the GM-PHD filter, further contributing to its versatility and applicability. The proposed GM-PHD filter approach surpasses a KF approach on the KITTI dataset and another custom dataset. The mean OSPA (2) error could be reduced from 1.56 (KF approach) to 1.40 (GM-PHD approach), showcasing its potential in ADAS perception.
Open Access
Analysing normal modes of the earth from high-rate GNSS time series
(2017) Chen, Zhongyi
Normal modes of the Earth, or Earth’s free oscillations, correspond to a global deformation of the Earth that vibrates at different frequencies, like a bell, after a strong excitation, usually an earthquake of magnitude greater than 6.5. Normal modes of the Earth were first described by Lord Kelvin (Kelvin, 1863) with a computation of the lowest fundamental spheroidal mode 0S2 frequency for a homogeneous Earth model (Lognonné and Clévédé, 2002). With the theory and the deployment of the first long-period sensors in the late 1950s, day-scale Earth’s free oscillation after large earthquakes has been detected by underground instruments such as strainmeters, gravimeters and seismometers (Benioff et al., 1961) (Dziewonski and Gilbert, 1972) (Mendiguren, 1973). In the 1960s, since the U.S. military developed the first satellite navigation system, Transit, the era of Global Navigation Satellite System (GNSS) has arrived. Among all navigation satellite systems, Global Positioning System (GPS), operated by the U.S. Department of Defense (DOD), is currently the world’s most utilized satellite navigation system. With the developments of receiver technology and sampling capability, GPS becomes a powerful tool to study long-period Earth deformations such as plate tectonics and post-glacial rebound, or to monitoring short-period and short-duration motion such as waves generated by earthquakes (Bilich et al., 2008). In recent years, several studies have demonstrated the effective use of GPS in estimating coseismic displacement waveforms induced by an earthquake with accuracies ranging from a few millimeters to a few centimeters. In these studies, two well-known processing strategies, single Precise Point Positioning (PPP) and Different Positioning (DP), have been used to reduce the latency between earthquake occurrence and coseimic displacement waveforms estimation. In this thesis, a new approach named Variometric Approach for Displacements Analysis Standalone Engine (VADASE) is used to detect the normal modes of the Earth. Then the Welch’s PSD estimate is applied to transform the time series into frequency domain. Several simulations have been performed on synthetic time series to investigate the influence of noise level, sampling rate, time series length, window size and overlapping rate of Welch’s method, as well as the influence of stacking. The experiments on real data show the capability of VADASE time series for detecting normal modes of the Earth with the help of the stacking method. Some fundamental modes with small amplitude are not visible because the SNR is not sufficient to lift the signal out of the noise.
Open Access
Analysis of coordinate transformation with different polynomial models
(2017) Gao, Yueqing
The main task of geodesy is providing geodetic networks with fixed points in order to create a uniform geographical spatial reference frame as a fundament for the data collection by the official geodesy survey institutes. A german geodesy survey institute called AdV (Arbeitsgemeinschaft der Vermessungsverwaltungen der Länder der Bundesrepublik Deutschland) declared in 1991 that the ETRS89 datum should be introduced in Germany as a reference system. In order to transform the already exciting coordinate informations in the Gauß-Krüger coordinate system into the later introduced UTM coordinate system, different transformation models have been developed and discussed. Besides the most commonly used 7-parameter Helmert transformation and 6-parameter affine transformation models, polynomial transformation models can also be applied. A method for improving the transformation results of a polynomial model will be discussed, with which a significance test (T-test) for each parameter will be done and the polynomial terms with lower significance to the model will be eliminated in order to get the optimal polynomial model. Here different transformation models are reviewed and the transformation results based on these models with the Least Squares estimation method are compared and analysed.
Open Access
Analysis of earthquake signals by spaceborne gravimetry
(2011) Cao, Zhou
The Gravity Recovery And Climate Experiment (GRACE) mission was launched on Mar. 17, 2002 and has provided the scientists with the gravity data for nearly ten years. The time variable gravity field provided by the GRACE has improved our knowledge of the earth in many fields such as hydrology, oceanography and glaciology. But compared to those “hot” fields, the publications of GRACE in seismology is considerably less. However, GRACE can provide scientists with an independent observation of the earthquake process. Coincidentally, some of the largest earthquakes are within GRACE’s life span - Sumatra-Andaman Earthquake (Indonesia) 2004, Maule Earthquake (Chile) 2010 and Tohoku Earthquake (Japan) 2011. Furthermore, a smaller earthquake - Sichuan Earthquake (China) 2008 has also been examined to test whether the GRACE can detect earthquakes smaller than Mw = 8.0. Different from the traditional methods of the earthquake researches, the gravity method has its advantages: 1. Massive: global scale; 2. Insight: gravity changes can reveal the underground mass changes which do not cause so much motion on the earth surface; 3. Convenient: superior to the traditional methods, the spaceborne gravimetry can get the data from the ocean and glacier parts. The conditions of the data are different among these four earthquakes. The procedures to eliminate the GRACE observation errors and unwanted geophysical data are necessary. First, the C20 term should be replaced by the Satellite Laser Ranging (SLR) data. Second, the hydrology signal especially in the regions of Chile and Sichuan should be eliminated by the Global Land Data Assimilation System (GLDAS) model. Third, Fan filter or Gauss filter 350 km should be applied. Time series analysis by the two-phase changepoint detection and hypothesis testing are applied for each earthquake which is a point-wise analysis. Least squares adjustment is performed on each point to display the coseismic and postseismic signals. Meanwhile, the surface analysis is done by the Empirical Orthogonal Functions (EOF) as it has a flexible base which can suit the data automatically. Although the observation errors have been removed as much as possible, the limited spatial and time resolutions of the GRACE satellite and to retrieve relatively weak earthquake signal among the strong hydrological signals are still problems in the analysis. GRACE can detect some of the large earthquakes, but it depends on the earthquake type, area and the length of the time-series before and after the earthquake. Both coseismic signal and postseismic signal are detected in Sumatra-Andaman Earthquake. Meanwhile, there is no significant coseismic signal in the time series of Sichuan Earthquake, but the EOF detects suspicious earthquake signal in mode 2 with the magnitude less than 1 µGal. For Maule Earthquake, only the coseismic signal is detected. Due to the limited dataset, the detection of the coseismic signal is successful but the postseismic signal is not long enough to be detected in Tohoku Earthquake. However, the different filters will affect the magnitude of the gravity change, so the real gravity changes of those four areas are still under debate. Last, EOF can be used for the separation of the earthquake signals. Compared to other geodetic technics the gravity method can detect the signals underground and in the ocean areas. The coseismic and postseismic signals detected by GRACE show underground processes of the earthquakes which can help scientists better understand the earthquake mechanism and will contribute to the earthquake prediction in the future.
Open Access
Analysis of geodetic time series using allan variances
(2010) Friederichs, Thomas
The Allan variance is a statistical measure, developed in the 1960’s by the American physicist David W. Allan. With its aid, data series measured by devices like oscillators or gyroscopes can be analyzed with regard to their stability. In contrast to the Allan variance, the standard variance as a measure of total signal power, is not able to characterize signal stability. There exist further developments of the Allan variance. This student research project considers mainly non-overlapping, overlapping and modified Allan variances. The result of an Allan variance computation is the so-called sigma-tau-diagram. This diagram provides information about the stability and beyond, it allows identification of various random processes that exist in the series of measurement. The Allan variance may be computed directly in the time domain as well as via the frequency domain using the power spectral density of the time series and a transfer function. A domain conversion between the Allan variance and the power spectral density is only unidirectional. More precisely, one can compute the Allan variance by means of the power spectral density, but not vice versa. This student research project takes up the challenge of applying the concept of the Allan variance to geodetic time series (pole coordinates as part of the Earth orientation parameters, GPS measured coordinates of one position, Scintrex CG-5 gravimeter data and GOCE gravity gradients, in addition to oscillator frequencies). The Allan variance turns out to be a reasonable statistical measure for analysis of geodetic time series. The Allan variance, or better the Allan deviation, especially in an entire diagram, can be considered as a form of spectral analysis. Having said this, it is possible to consider the averaging interval tau as the inverted frequency.
Open Access
Analysis of helicopter-borne gravity gradiometry
(2017) Xia, Zhuge
Nowadays the FALCON partial tensor gravity gradiometer is the only applied AGG instrument to be used in a helicopter to collect high-resolution data for commercial demand. In order to know its principles and make full use of its advantages, in this study thesis, a helicopterborne gravity gradiometry data set offered by USGS is processed and analysed. It is interesting to figure out that whether the gradient tensor invariants are truly "invariant". Also through Fourier transformation, all gradient tensor components can be determined mathematically. Besides, the effects of terrain corrections and different flight line spacings and drape heights are also concerned to obtain high-resolution data in the easiest way.
Open Access
Analysis of long term variations of ocean mass in the arctic region using satellite gravimetry
(2020) Daud Gisiri, Thomas
The Arctic region has experienced rapid sea ice melt in the past decade, which leads to the global sea level rise. The volume of the ice, area and extent have been declining in recent years. The inflow of the Atlantic Ocean water into Arctic Ocean have made changes including the weaker stratification. Moreover, shoaling of Atlantic water in Eurasian Basin reduced sea ice and accelerate the Atlantic water layers’ heat fluxes further Northeast into Eurasian Basin. The salty water (denser than fresh water), the melting of sea ice and warming of Arctic Ocean surface are causing the density of water to change as well as the variations in ocean mass. These huge amounts of the mass variations lead the variations of the Earth gravity field that are being monitored by satellite gravimetry. The main objective of this thesis is to estimate and analyse ocean mass variations in the Arctic Ocean and all seas around namely Laptev Sea, Kara Sea, Barents Sea, Green Land Sea, Baffin Bay, Hudson Bay, Baffin Bay, Beaufort Sea, Chukchi Sea and East Siberian Sea. For this purpose, the standard GRACE level-2 data product from GeoForschungsZentrum (GFZ), Potsdam and the Centre for Space Research (CSR) from University of Texas has been used to estimate the ocean masses. Moreover, the Sea Level Anomaly (SLA) data from satellite altimetry was used for further analysis of the trend in the Arctic region computed from GRACE data. The SLA data is provided by Technical University of Denmark (DTU). Results show that the Beaufort Sea has experienced the highest positive trend in ocean mass of 9.99 mm/year and SLA of approximately 10 mm/year. The positive trends are influenced by the presence of Beaufort Gyre which the anticyclone winds accumulate the fresh water and deeper in this region there are cold and salty water from Pacific Ocean. The Chukchi Sea has positive trend in ocean mass of 7.64 mm/year and Sea Level Anomaly trend range from −1 mm/year and 1 mm/year. The positive trends are influenced by Pacific Ocean water which are warmer and saltier. The Baffin Bay has the strongest negative trend in ocean mass of −59.59 mm/year and Sea Level anomaly trend of approximately −9 mm/year. These negative trends are caused by the Gravitation attraction of Greenland masses and the Arctic Ocean freshwater outflows through it on the way to North Atlantic Ocean. The Hudson Bay have positive trend in ocean mass of 0.35 mm/year and Sea Level Anomaly trend ranges from 1 to 3 mm/year. The positive trends are due to large input of fresh water from river and precipitation, ice melting influenced by air temperature and inflow of Arctic Ocean waters. The Greenland Sea has negative trend in ocean mass of −9.10 mm/year and Sea Level Anomaly trend ranges between −1 mm/year and 6 mm/year. The negative trend is influenced by Gravitational attraction of Greenland masses or due to freshwater outflow from the Arctic Ocean through western side of Fram Strait. Barents Sea has positive trend in ocean mass of 0.13 mm/year and Sea Level Anomaly trend ranging from −1 mm/year to 7 mm/year. Kara Sea has positive trend in ocean mass of 3.73 mm/year, Laptev Sea has positive trend in ocean mass of 6.83 mm/year, East Siberian Sea has a positive trend of 8.25 mm/year and Arctic Ocean has positive ocean mass trend of 5.83 mm/year. The positive trends in this region are influenced by the so-called Atlantification of Arctic Ocean. The Kara Sea, Laptev Sea and East Siberian Sea all have negative trends in Sea Level Anomaly ranging from −2 mm/year to −6 mm/year. The negative trends are influenced by the gain of fresh water, net precipitation, run off increased and more discharge from the land to the sea water.
Open Access
Analysis of river surface slope using ICESat-2 satellite altimetry
(2022) Bao, Jingyi
Open Access
Analysis of seasonal loading-induced displacements from GPS and GRACE
(2014) Zhang, Jinwei
Mass transport within the Earth system over time (e.g., hydrological circulation) induces the mass redistribution on the surface. The temporal variation of mass load on the surface consequently leads to elastic deformation of Earth’s surface (van Dam et al., 2001; Ilk et al., 2005; De Linage et al., 2007). The surface deformation could be derived from GRACE through time-variable gravity field and also be observed by IGS stations in GPS 3D coordinates. The surface deformations derived from GRACE are spatially smoothed with about 350 km resolution. However, the deformations of IGS stations observed by GPS are discrete point measurements on the globe. Therefore, a validation of the consistency between the deformations from GRACE and GPS is necessary to be done, which would benefit the further research on mass transport and climate change. In this study, using the data from GFZ, the deformations from GRACE are theoretically calculated in vertical and horizontal directions (Wahr et al., 1998; Kusche and Schrama, 2005). To investigate the disagreement between GPS and GRACE, a number of IGS stations in three regions are selected (i.e., Tibetan plateau, Danube basin and Great Lakes area) with period of 8 years (2003 – 2011). For a proper comparison, the spatial and temporal reference of GRACE and GPS need to be unified. For validation, the correlation coefficient, the Nash-Sutcliffe efficiency, and WRMS reduction are estimated. After comparisons of deformation time series, almost all the stations in those regions show good consistency between GRACE and GPS in vertical component. There is distinct disagreement in horizontal component, probably due to the weak loading signals and strong local effects. Thus, several representative stations in those regions would be discussed and analysed in detail. Furthermore, to detect an optimal filter for GRACE, 40 IGS stations in Europe are involved to evaluate the filter performance. As a result, 52.5% stations filtered by the stochastic filter (i.e., Wiener filter) show better results, which indicates the optimal choice.
Open Access
Analysis of water volume change of the lakes and reservoirs in the Mississippi River basin using Landsat imagery and satellite altimetry
(2021) Wang, Lingke
In recent years, the demand for freshwater has been steadily increasing owing to population growth and economic expansion. Surface waters such as lakes and reservoirs function as a dominant factor in mankind's freshwater provision. Analysis of changes in their water storage is consequently vital for understanding of the global water cycle and water resources. However, the water volume changes in lakes or reservoirs cannot be measured directly from space, but can be inferred from lake areas and lake water levels. Lake area can be measured globally from space but lake water level is not easy to be obtained globally. Because the number of in situ stations is few, and in situ data are only accessible for some lakes with few measurement epochs, despite in situ stations can measure lake water level and provide high accuracy observations. Although the altimetry technique can generate the time series of the water level for the majority of lakes, they are not global coverage due to the distance between satellite tracks and the gap between different missions. Therefore, in situ data and satellite altimetry measurements of water levels of lakes and reservoirs are not always available. For example, there are only 22 lakes or reservoirs in this study covered by satellite altimetry or in situ stations out of 90 research cases in Mississippi River Basin. Then, in case of unavailable in situ data or altimetry measurements, this research proposes an alternative method to estimate the water level through Digital Elevation Model (DEM). Because satellite imagery offers global coverage and DEM is the global digital representation of the land surface elevation with respect to any reference datum, this study allows for the evaluation of global water volume changes by acquiring lake area data from space and lake height data from DEM. Therefore, the objective of this study is that changes in water volume in lakes or reservoirs can be successfully monitored even when in situ data and satellite altimetry measurements are not available for lakes or reservoirs. Hereby, we investigate 90 lakes and reservoirs in the Mississippi River Basin and develop an alternative remote sensing technique to monitor the water volume changes by combining the improved water mask with DEM. Meanwhile, we propose practical methods to detect the shoreline pixels of the water body from improved water mask. Given the assumption that all pixels in the shoreline should have the same height, four water level estimation models are developed, including water level estimation model based on statistical analysis, frequency maps, change pixels and pixel pair analysis. To this end, the study estimates the time series of lake height from water level estimation model and obtains the time series of lake surface area from HydroSat. Subsequently, this study builds the unique function between the lake water level and the lake surface area and then develops the function between the lake water volume change and the lake surface area. Finally, this study analyses the water volume changes of lakes and reservoirs in the Mississippi River Basin using this alternative remote sensing method. Four water level estimation models are proposed and evaluated. They are respectively based on statistical analysis, frequency maps, change pixels and pixel pair analysis. As a result of their actions, the first model based on statistical analysis, with an average correlation of 0.62 and an average RMSE of 0.91 meters, functions in the majority of situations and demonstrates excessive outlier removal in some cases. The second model based on frequency maps is more general than the first, with an average correlation of 0.66 and an average RMSE of 1.11 meters. The average correlation for the third model based on change pixels is 0.71, and the average RMSE is 0.99 meters. The resulting model based on pixel pair analysis obtains a mean correlation of 0.67 and a mean RMSE of 1.00 meters. Finally, these models behave differently in different seasons, so they exhibit distinct monthly behaviour. To conclude, the above validation results show that this alternative method can be used in different lakes and reservoirs in case of absence of water level observation data, and achieve to monitor the water volume changes during a long period.
Open Access
Analysis of waveforms in the satellite altimetry by using neural networks
(2019) Mattes, Dennis Frederic
The in situ data of inland water bodies is only limited and is declining lately. At the same time, it is more and more important to monitor the inland water bodies, since the climate is changing rapidly. To handle this problem, space born sensors are used more and more. One of the possibilities is to use satellite altimetry, which was previously designed for measurements over the oceans. Thereby, the satellite is transmitting a radar signal towards the earth surface at nadir. This signal is reflected by the ground back to the satellite. By doing so, it estimates the surface height with the runtime of the signal. However, caused by the fast changing terrain over the inland, more noise is included and lead to errors in the height estimation. To solve this, retracker are applied which analyse the received signal and estimate the correct runtime. In this thesis, a new approach will be presented which aims to use neural networks for the retracking purpose. The advantage is that neural networks can learn the characteristic pattern of the signals and then find this pattern during the retracking process. Thereby two approaches are developed, one which uses solely a neural network and a second one, which uses the results of the neural network as an input for an algorithm. They are then applied to different study areas to analyse their performance. It could be shown that the neural networks can estimate the water height well so that a reasonable water height time series can be created. Thereby, the neural network approach shows better results than the algorithm. At the end also the transferability of the neural networks could be shown. Thus, one can use a trained neural network also on other water bodies as which are used for training.
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, Nico
The 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.
Open Access
Analyzing and characterizing spaceborne observation of water storage variation : past, present, future
(2024) Saemian, Peyman; Sneeuw, Nico (Prof. Dr.-Ing.)
Water storage is an indispensable constituent of the intricate water cycle, as it governs the availability and distribution of this precious resource. Any alteration in the water storage can trigger a cascade of consequences, affecting not only our agricultural practices but also the well-being of various ecosystems and the occurrence of natural hazards. Therefore, it is essential to monitor and manage the water storage levels prudently to ensure a sustainable future for our planet. Despite significant advancements in ground-based measurements and modeling techniques, accurately measuring water storage variation remained a major challenge for a long time. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) and its successor GRACE Follow-On (GRACE-FO) satellites have revolutionized our understanding of the Earth's water cycle. By detecting variations in the Earth's gravity field caused by changes in water distribution, these satellites can precisely measure changes in total water storage (TWS) across the entire globe, providing a truly comprehensive view of the world's water resources. This information has proved invaluable for understanding how water resources are changing over time, and for developing strategies to manage these resources sustainably. However, GRACE and GRACE-FO are subject to various challenges that must be addressed in order to enhance the efficacy of our exploitation of GRACE observations for scientific and practical purposes. This thesis aims to address some of the challenges faced by GRACE and GRACE-FO. Since the inception of the GRACE mission, scholars have commonly extracted mass changes from observations by approximating the Earth's gravity field utilizing mathematical functions termed spherical harmonics. Various institutions have already processed GRACE(-FO) data, known as level-2 data in the GRACE community, considering the constraints, approaches, and models that have been utilized. However, this processed data necessitates post-processing to be used for several applications, such as hydrology and climate research. In this thesis, we evaluate various methods of processing GRACE(-FO) level-2 data and assess the spatio-temporal effect of the post-processing steps. Furthermore, we aim to compare the consistency between GRACE and its successor mission, GRACE-FO, in terms of data quality and measurement accuracy. By analyzing and comparing the data from these two missions, we can identify any potential discrepancies or differences and establish the level of confidence in the accuracy and reliability of the GRACE-FO measurements. Finally, we will compare the processed level-3 products with the level-3 products that are presently accessible online. The relatively short record of the GRACE measurements, compared to other satellite missions and observational records, can limit some studies that require long-term data. This short record makes it challenging to separate long-term signals from short-term variability and validate the data with ground-based measurements or other satellite missions. To address this limitation, this thesis expands the temporal coverage of GRACE(-FO) observations using global hydrological, atmospheric, and reanalysis models. First, we assess these models in estimating the TWS variation at a global scale. We compare the performance of various methods including data-driven and machine learning approaches in incorporating models and reconstruct GRACE TWS change. The results are also validated against Satellite Laser Ranging (SLR) observations over the pre-GRACE period. This thesis develops a hindcasted GRACE, which provides a better understanding of the changes in the Earth's water storage on a longer time scale. The GRACE satellite mission detects changes in the overall water storage in a specific region but cannot distinguish between the different compartments of TWS, such as surface water, groundwater, and soil moisture. Understanding these individual components is crucial for managing water resources and addressing the effects of droughts and floods. This study aims to integrate various data sources to improve our understanding of water storage variations at the continental to basin scale, including water fluxes, lake water level, and lake storage change data. Additionally, the study demonstrates the importance of combining GRACE(-FO) observations with other measurements, such as piezometric wells and rain-gauges, to understand the water scarcity predicament in Iran and other regions facing similar challenges. The GRACE satellite mission provides valuable insights into the Earth's system. However, the GRACE product has a level of uncertainty due to several error sources. While the mission has taken measures to minimize these uncertainties, researchers need to account for them when analyzing the data and communicate them when reporting findings. This thesis proposes a probabilistic approach to incorporate the Total Water Storage Anomaly (TWSA) data from GRACE(-FO). By accounting for the uncertainty in the TWSA data, this approach can provide a more comprehensive understanding of drought conditions, which is essential for decision makers managing water resources and responding to drought events.
Open Access
Analyzing and modeling environmental loading induced displacements with GPS and GRACE
(2015) Chen, Qiang; Sneeuw, Nico (Prof. Dr.-Ing.)
The redistribution of atmospheric, oceanic and hydrological masses on the Earth's surface varies in time and this in turn loads and deforms the surface of the solid Earth. Analyzing such environmental loading signal and modeling its induced elastic displacements are of great importance for explaining geophysical phenomena. Based on the well-established loading theory, this thesis makes use of two different space-borne measurements, i.e. GPS and GRACE, along with other environmental loading data to investigate three different aspects of environmental loading and its induced elastic deformations: Firstly, an increasing concern is observed recently over time variable seasonal signals in geodesy. Several model based approaches were applied to extract amplitude and phase modulated annual and semiannual signals. In view of this phenomenon, this thesis introduces an alternative approach, namely, singular spectrum analysis (SSA). With respect to these model-dependent approaches, the advantage of SSA lies in data-driven and model-independence. Several aspects regarding the application of SSA, e.g. optimal choice of window size, are investigated before showing its abilities. Through applying SSA to the lake level time series of Lake Urmia (Iran) and the basin averaged equivalent water height time series of the Congo basin, the capabilities of SSA in separating time varying seasonal signals are demonstrated. In addition, we find that SSA is also able to extract the non-linear trend as well as long-term oscillations from geodetic time series. Secondly, we look into the comparison between GPS and GRACE with an emphasis on GRACE data filtering. Three types of deterministic filters and two types of stochastic filters are studied and compared over GPS sites from two regions, i.e. the Europe area and the Amazon area. The comparisons indicate that no single filtering scheme could provide consistently better performance over other considered filters. However, we find that the stochastic filters generally show better performance than the deterministic filters. The DDK 1 filter outperforms other filters in the Europe area and the regularization filter of parameter lambda=4, which follows the concept of the DDK filters, shows optimal performance in the Amazon area. The combination of the isotropic Gaussian filter of a low smoothing radius, e.g. around 300 km with the destriping filter is proved to be optimal filter choice if only the deterministic filters are considered. Thirdly, based on an overview of displacements modeling at various spatial scales, we evaluate three methods, i.e. two types of half-space approaches and the classic Green function approach, by using a high spatial resolution local load data along the lower Mississippi river when a severe flood happened in 2011. The equivalence between the two half-space approaches, i.e. point load approach and surface load approach, are demonstrated with the local load data. However, the point load approach is recommended for practical use in terms of computational efficiency. In addition, within such a limited spatial extent, we investigate the differences between the half-space approach and the Green function approach. It is shown that the half-space approach predicts larger displacements than the Green function approach and agrees better with the observed deformations at 11 considered GPS sites. Meanwhile, strong global environmental loading effects are found via two global hydrological models, i.e. GLDAS and MERRA. Thus, a reduction of these far-field loading effects beforehand is suggested before probing the local crustal structure using the half-space approach. Last but not least, based on the local load data, the effects of site-dependent Green functions are studied with two types of site-dependent Green functions, which were generated by modifying the local crustal structure of the REF Earth model using the CRUST 1.0 and CRUST 2.0 models. A relative RMS of differences of more than 5% in vertical component and 25% in horizontal components are found with respect to the PREM Earth model based Green functions. It indicates that the Green functions could contribute more uncertainties in loading induced displacements modeling than reported in the literature.
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.
Open Access
Analyzing the surface height of Nam Co by using CryoTrack
(2018) Liu, Mo
In recent decades, the global climate change is increasingly accelerating and intensifying. The plateau climate is an important part of the global climate. In this thesis, we will take the plateau lake Nam Co as an object to research and analyze the climatic variation in this area. Since Nam Co is located in Tibet Plateau with a high elevation and it doesn’t have too much human disturbance, it is an ideal study object to observe. In this thesis, we will use the data from the satellite CryoSat-2 and the software CryoTrack to obtain the surface height of Nam Co as well as the trend of the water level variation of it. Meanwhile, by using CryoTrack we can also observe the frozen and breakup time of the lake ice.
Open Access
Application of image segmentation techniques in satellite altimetry retracking : a feasibility study
(2020) Eitel, Maximilian
Im Bereich der Ozeanographie ist Satellitenaltimetrie die bevorzugte Methode, um Meereshöhen präzise zu erfassen. Wir möchten diese Technologie auch für Binnengewässer nutzen und mit einer neuen Signalverarbeitungsmethode, die auf Bilderverarbeitungsalgorithmen basiert, die Genauigkeit dieses Verfahrens verbessern. Unser Ansatz basiert auf einer zweidimensionale Datenstruktur, die wir erlangen indem benachbarte Signale miteinander kombiniert werden. Dadurch entsteht ein Graustufenbild, welches die Stärke des gemessenen Signals in Graustufen illustriert. In den so entstehenden Bildern können wir die Leading Edge als helle herausstehende Struktur, die nach einem sehr dunklen Bereich auftritt, identifizieren. Unser Ziel ist es mit Hilfe von Bildsegmentierungsverfahren die Retracking Line aufzulösen indem wir das Bild in einen Hintergrundbereich (vor der Leading Edge) und einen Objektbereich (die Leading Edge) teilen.
Open Access
Application of spaceborne geodetic sensors for hydrology
(2013) Tourian, Mohammad Javad; Sneeuw, Nico (Prof. Dr.-Ing.)
How much freshwater do we have on land? How is the freshwater cycle changing with time? Actually, we can not properly answer these questions as our knowledge of the spatial and temporal dynamics of the hydrological cycle is limited. The lack of knowledge is mainly induced by shortage of observational evidence, which motivates the objective of this study: the monitoring of the hydrological cycle using spaceborne geodetic sensors. Among the current space geodetic sensors, GRACE and satellite altimetry are the two active mission concepts, that can capture part of the hydrological cycle. However, monitoring the hydrological cycle using these two sensors is challenging. Satellite altimetry is investigated as an independent spaceborne sensor that provides the water level and discharge time series. An algorithm is developed to improve the quality of water level time series over inland water surfaces. This algorithm particularly deals with the challenges of resolution and uncertainty of altimetry. The obtained altimetric water level time series is validated against in situ measurements showing about 10% improvement in accuracy of the time series. Moreover, this study proposes an algorithm to reduce the random noise from pre-retracked data. The algorithm combines the results of different retrackers and provides water level time series with reduced noise level. The validation shows a significant reduction of noise level and a clear improvement in correlation with in situ measurements. Moreover, this study proposes a statistical approach based on quantile functions to infer a functional relationship between altimetric water level and in situ river discharge without the need for synchronous data sets. This method is based on a scatter diagram of quantile functions, in which the probability-coordinate is eliminated. In contrast, the conventional methods for simultaneous measurements operate directly on time series and eliminate the time-coordinate. The results show that the proposed methodology provides the same range of error as the common conventional empirical method. The good performance of the statistical approach supports the usage of altimetry to salvage pre-satellite altimetry discharge data and turn them into active use for the satellite altimetry time frame. In addition, a stochastic process model is implemented to (i) deal with the data outages in altimetric discharge, (ii) provide a scheme for data assimilation and (iii) smooth the discharge estimation. The model benefits from the cyclostationary behaviour of the discharge and is combined with the estimated discharge from altimetry and available in situ measurements to form a linear dynamic system. The dynamic system is solved using the Kalman filter, that provides an unbiased discharge with minimum variance. The error level of the results is comparable to the empirical approach. In this study, the utility of GRACE data as sensor of hydrological water storage changes is shown to be limited by the following challenges: consistency, resolution, separability and uncertainty. The challenge of inconsistency is addressed by developing two filters for hydrological and hydro-meteorological water storage changes, which lead to a better correlation with GRACE mass storage changes. The challenges of separability and resolution are not specifically investigated in this study, yet their consequences, which appear in different forms of uncertainties is investigated. To deal with the GRACE uncertainties, an algorithm is developed to detect outliers in monthly solutions. The outliers have been corrected by replacing them by an inter-annual monthly mean of the respective month. The results conclude that outlier identification and correction must be performed before further assimilation of GRACE products into hydrological or hydro-meteorological analysis. Further, a longrange correlation has been identified as another source of uncertainty in GRACE monthly solutions. EOF analysis is employed to identify the zonal behaviour of the GRACE C20 errors as the responsible source for the long-range correlation. It is considered as an error source because its residual contains tidal aliasing errors instead of white noise. Therefore, to reduce the uncertainties in GRACE monthly solutions, tidal aliasing errors are also investigated. Primary and secondary tidal aliasing errors of main tidal constituents, S1, S2, P1, K1, K2, M2, O2, O1 and Q1 are identified in GRACE monthly solutions. The effect of tidal aliasing error is estimated using a least squares Fourier analysis indicating errors up to 22mm over the globe. In general, after dealing with GRACE’s challenges and achieving a data set without outliers, long-range correlation and tidal aliasing errors, the noise level of GRACE is quantified. The quantification shows a variation between 2–20mm/month over different parts of the globe, with higher values over tropical and boreal regions. The results specifically confirm that small catchments in the tropics contain more noise contamination. It is also shown that a lower noise level of a catchment does not necessarily lead to a better correlation of GRACE with hydro-meteorological signal. Finally, the joint performance of spaceborne geodetic sensors for estimating the actual evapotranspiration ETa is assessed. There, two approaches are introduced to estimate ETa using the results of GRACE and satellite altimetry. The results of both approaches are compared with different models and their ensemble mean. All in all, given the obtained relative discrepancy, the methods seem to be a viable way for determining ETa for most non-desert catchments containing hot and warm summers.
Open Access
Applying stochastic constraints on time-variable GRACE data
(2009) Lorenz, Christof
Since its launch in the year 2002, the space satellite mission GRACE provides spherical harmonic coefficients, which can be used to observe the time-variable part of the Earth's gravity field. It was initially assumed that the derived gravitational quantities from these coefficients are of high accuracy and would thus deliver reliable large scale mass estimates. However, the provided coefficients of higher harmonic degree and order turned out to be seriously contaminated with noise, yielding an unrealistic signal of mass variations in form of massive north-south stripes. In this work, two methods are investigated, which add stochastic constraints to time variable GRACE coefficients. It is assumed that these techniques are able to reduce the noise level in the monthly datasets by assimilating the GRACE coefficients with more reliable data. Both approaches need prior estimates of a signal and error covariances. Hence, the signal covariance of the time-variable gravity field is assumed to be of isotropic nature and is thus computed as a Kaula-type power law, which is fit into the part where the signal degree variances of the GRACE solutions linearly attenuate. The error covariance is estimated according to the energy balance approach which allows the simulation of a fully populated GRACE covariance matrix. Stochastic constraining in the spectral domain combines both signal and error covariance estimates in a Bayesian type regularization procedure, which constrains the monthly GRACE solutions with the modelled signal covariance. It is shown that Bayesian type regularization can be used to build a spectral filter kernel. Furthermore, the weight between both GRACE coefficients and the regularization term is estimated by a variance component estimation. Tests with a full, block diagonal and diagonal covariance matrix are performed, as it is widely believed that full covariance information can be sufficiently approximated by a block diagonal matrix. Furthermore, the Bayesian type regularization filter is tested with three different monthly GRACE solutions and compared with other widely used filtering techniques. The second approach constrains the time-variable GRACE coefficients with hydrological observations, which are provided as monthly precipitation and run-off values on basin scale. Both the GRACE and hydrological observation group are assimilated in one linear model, which is solved by sequential least squares estimation, yielding an agreement between mass estimates from GRACE and observed hydrology.
Open Access
Assessing hydrological changes in the Murray-Darling basin
(2010) Schmid, Stefanie
In this diploma thesis GRACE-derived time-variable gravity, TRMM precipitation, and in-situ hydrological observations (water level, river flow) between May 2003 and April 2009 (6 years) are used to assess hydrological changes in the Murray-Darling Basin (MDB). The investigations in terms of Multiple Linear Regression Analysis (MLRA) and Principal Component Analysis (PCA) show distinct differences between the northern and southern climatic regions of the MDB. While the north is dominated by precipitation occurring within the early part of each year, precipitation appears in the south half a year later. Furthermore, a severe drought is detected, which appeared in 2006/07. The analysis of seasonal variations reveals that gravity changes are preceded by precipitation by about one month in the north of the MDB, while the south shows the inverse behaviour. The phase shift of gravity changes between the north and the south suggests a mass transport taking about 5 months to cross the MDB from the north to the south, which is confirmed by the in-situ hydrological observations.