06 Fakultät Luft- und Raumfahrttechnik und Geodäsie

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

Browse

Filters

2007 - 20096

Settings

Publication Type: search.filters.UBSTyp.Abschlussarbeit (Diplom)Start date: 2003End date: 2009Subject: search.filters.subject.550

Search Results

Now showing 1 - 6 of 6
  • Thumbnail Image
    ItemOpen Access
    Empirical orthogonal function analysis of GRACE gravity data
    (2009) Bentel, Katrin
    The Gravity Recovery and Climate Experiment (GRACE) twin-satellite mission has been providing measurements of the time-varying gravity field of the Earth for almost seven years now. Gravity changes on Earth are due to mass changes and play an important role in Earth sciences. Monthly maps of mass changes are derived from the satellite measurements and need to be interpreted. The major difficulty in analyzing GRACE data are North-South stripes in the estimated gravity fields, caused by the fact that the GRACE satellites are flying in a near-polar orbit, one following the other. A microwave ranging instrument is measuring the distance between the two spacecraft, which is about 220 km. Due to these longitudinal stripes, major errors, analyzing the GRACE gravity fields is demanding. The technique of empirical orthogonal function (EOF) analysis is investigated in this thesis, and it is demonstrated the performance of EOF analysis for separating signal from noise and errors, and for identifying different sources of gravity changes in a real GRACE data set. EOF analysis is explained from a theoretical point of view and is applied to the GRACE data. Basically, the EOF method gives a transformation of the data into a new coordinate frame in the data space, where the axis are chosen according to the data variances. The core of the method is a singular value decomposition of the data matrix. The components obtained from this decomposition need to be interpreted, and signal has to be separated from noise. Additionally, EOF analysis can be used as a filtering tool. In the detailed data analysis, benefits and shortcomings of the EOF method are studied and described with respect to GRACE data. Global maps of mass changes as well as different smaller regions are analyzed, and global and regional results are compared.
  • Thumbnail Image
    ItemOpen Access
    Einfluss lateraler Variationen in Lithosphäre und oberem Mantel auf den glazial-isostatischen Ausgleich in der Antarktis
    (2009) Rau, Daniel
    Diese Arbeit beschäftigt sich mit den Auswirkungen der lateral variierenden Lithosphärenmächtigkeit auf die regionale glazial-isostatische Ausgleichsbewegung (GIA) in der Antarktis. Damit einhergehend wird auch die Viskosität des oberen Mantels variiert. Die Lithosphäre in der Antarktis ist in zwei Bereiche mit scharfem Übergang unterteilt, eine dicke Lithosphäre in der Ostantarktis und eine dünne Lithosphäre in der Westantarktis. Nun wird untersucht wie sich die verschiedenen Lithosphärendicken im Modell auf das Verhalten der nacheiszeitlichen Hebung bzw. auf den glazial-isostatischen Ausgleich auswirken. Zur Einordnung werden die Vertikalbewegung, die Horizontalbewegung sowie die Geoidhöhenänderung modelliert. Hierzu wird zunächst ein dreidimensionales (3D) Viskositätsmodell mit einer lateral variablen Lithosphäre erstellt. Dieses Erdmodell wird mit einem Lastmodell belastet, welches sich aus der Vereisungsgeschichte ICE-5G ergibt. Die Berechnung der in dieser Arbeit untersuchten Größen erfolgt unter Verwendung der spektralen Finite-Elemente-Methode für 3D viskoelastische Belastung. Durch ein inhomogenes Abschmelzen der Eismassen in der Antarktis sind dessen Auswirkungen in der Westantarktis stärker ausgeprägt. Um die Effekte der Lithosphärenvariation zu extrahieren, werden Vergleichsmodelle erstellt, die beispielsweise einen 3D-Mantel, jedoch nur eine eindimensionale (1D) Lithosphäre aufweisen. Anhand der durchgeführten Vergleiche wurde deutlich, dass der Einfluss der Lithosphärenmächtigkeit in Relation zu den Einflüssen des Mantels sehr gering ist. Lediglich im Bereich der Horizontalbewegungen ist ein Einfluss von 20-30 % der Gesamtgeschwindigkeit messbar. Für die Vertikalbewegungen bleibt der Einfluss mit < 1 mm/a unter 10 %, und für die Geoidhöhenänderungen ist die Änderung aufgrund von Lithosphärenvariationen < 0.10 mm/a. Der Einfluss der Mantelviskosität ist in allen Bereichen höher.
  • Thumbnail Image
    ItemOpen Access
    Variance-covariance matrix estimation with LSQR in a parallel programming environment
    (2008) Guo, Ronggang
    Knowledge about the gravity field allows an insight into the structure and dynamics of the earth. It provides the geoid as the most important physical reference surface in geodesy and oceanography. Since 2000, the CHAMP (CHAllenging Mini-satellite Payload) mission detects the structure of the global gravity field, followed by the launch of GRACE (Gravity Recovery And Climate Experiment) in 2002. In 2008, finally, the GOCE (Gravity field and steady-state Ocean Circulation Explorer) satellite is supposed to be set in orbit. These missions demonstrate satellite-based gravity field recovery to be at the center of geo-scientific interest. Interpretation and evaluation of satellite observations are difficult, especially the determination of the unknown gravity field parameters from a huge amount of measurements. Because of the immense demand for memory and computing time, the occurring systems of equations pose a real numerical challenge. Therefore, High-Performance Computing (HPC) is commonly adopted to overcome computational problems. Basically, parallel programming with MPI and OpenMP routines allows to speed up the solution process considerably. In this thesis, firstly global gravity field modelling by means of satellite observations is reviewed. Secondly, the LSQR method (Least-Squares using QR factorization) is introduced in detail in order to solve the resulting least-squares problems. Because the LSQR method is an iterative solver, it basically can not provide the variance-covariance information of the parameter estimate. To investigate the approximate computation of the variance-covariance matrix, two methods are introduced. The first one is based on the generalized inverse of the design matrix. The second approach applies Monte-Carlo integration techniques. Because parallel programming is very helpful to implement such iterative methods, it is necessary to introduce some basic principles and concepts about HPC.
  • Thumbnail Image
    ItemOpen Access
    GOCE sensitivity studies in terms of cross-over analysis
    (2009) Xue, Yang
    The GOCE (Gravity field and steady-state Ocean Circulation Explorer) satellite, launched on 17 March 2009, for the first time applies satellite gravity gradiometry (SGG) to recover the Earth's gravity field with cm accuracy at a resolution of 100km. To meet the envisaged accuracy, measurement validation at cross-over points (XOs) is necessary. Typically, validation is based on gravity gradients (GGs). However, the coefficient matrix of the gravitational tensor is dependent on orientation. In order to avoid matrix rotation, analysis based on orientation-independent invariants is possible. By applying various noise models, the goodness of XO-validation based on GGs and invariants will be studied in this thesis. First, by determining the maximum of scalar products from two tracks, the XOs can be predicted. Next, using local polynomial approximation, the geographical coordinates of XOs are calculated by solving a system of equations. Due to the orbit drift, the interpolation of height is performed separately along ascending and descending track before final comparison. Considering a sampling rate of 1Hz, GGs and invariants in all points of a one-week orbit are simulated for the further interpolation at the XOs. To determine the goodness of the selected interpolation algorithm, a closed loop test with noise-free data is investigated first. Since signal to noise ratios of GGs and invariants are all above 70dB, the same algorithm is applied in closed loop tests with noisy data. Since GOCE can only provide high accuracy for the main diagonal tensor components, various noise models, i.e. homogeneous and inhomogeneous white noise as well as homogeneous and inhomogeneous coloured noise, are added to the simulated values. The comparison of the goodness of GGs opposed to invariants is based on the signal to noise ratio (SNR). In this study, the second invariant demonstrates better SNR than GGs and the third invariant in the case of homogenous noise. However, due to the impact of inaccurate GGs, the SNR of invariants is poorer than the SNR of all GGs in the case of inhomogeneous noise.
  • Thumbnail Image
    ItemOpen Access
    Surface Deformation Analysis of GPS Dense Networks based on Intrinsic Approach
    (2007) Moghtasad-Azar, Khosro
    Here we present a method of differential geometry, an intrinsic approach that allows deformation analysis of the real surface of the Earth on its own rights for a more reliable and suitable estimate of the surface deformation measures. The method takes advantage of the simplicity of the two-dimensional Riemannian manifold spaces versus the three dimensional Euclidean spaces without losing or neglecting information and effect of the third dimension in the results. Here we describe the regularized Earth's surface as a graded two-dimensional Riemann manifold, namely a curved surface, embedded in a three dimensional Euclidean space. Thus, deformation of the surface can be completely specified by the change of the first and second fundamental tensors, namely changing of metric tensor and changing of curvature tensor, of the surface, which changing of curvature tensor is responsible for detection of vertical displacements on the surface. This study describes analytical modelling, derivation, and implementation of the surface deformation measures based on the proposed method, particular attention to the formulation and implementation of the tensors of rotation and tensor of change of curvature in Earth deformation studies. The method is applied to a real data set of dense space geodetic positions and displacement vectors across the Southern California. A comparison of the patterns with the geological and geophysical evidences of the area indicated how well the patterns were able to reveal different geodynamical features of the region.
  • Thumbnail Image
    ItemOpen 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.