Surface Based Modelling of Ground Motion Areas in Lower Saxony

Systematic investigations have shown subsidence in almost 30% of the land area in Lower Saxony. It is essential to model these variations of the Earth surface especially to update the spatial reference system. Since the geodetic observations result in discrete points, it is necessary to mathematically model these measurements to have a continues surface. This enables the user to do predictions at any position. This is challenging especially because these types of measurements usually result in non-uniformly distributed data. There are different approaches to deal with this problem, here the stochastic method of Kriging and the deterministic method of Multilevel B-Splines are implemented to model ground motion. This paper investigates the ground motion of specific areas in Lower Saxony through the cooperation of Landesamt für Geoinformation und Landesvermessung Niedersachsen (LGLN) and Geodetic Institute of Hannover. For this investigation, a time series of measurements from leveling, Global Navigation Satellite System (GNSS) observations and height changes that are acquired by Persistent Scatterer Interferometry (PSI) technique are taken into consideration. Evaluation of the results show not only good performance and promising results from both the approaches, but also compatibility between the approximated surface from both of them

Mutual Validation of GNSS Height Measurements and High-precision Geometric-astronomical Leveling

The method of geometric-astronomical leveling is presented as a suited technique for the validation of GNSS (Global Navigation Satellite System) heights. In geometric-astronomical leveling, the ellipsoidal height differences are obtained by combining conventional spirit leveling and astronomical leveling. Astronomical leveling with recently developed digital zenith camera systems is capable of providing the geometry of equipotential surfaces of the gravity field accurate to a few 0.1 mm per km. This is comparable to the accuracy of spirit leveling. Consequently, geometric-astronomical leveling yields accurate ellipsoidal height differences that may serve as an independent check on GNSS height measurements at local scales. A test was performed in a local geodetic network near Hanover. GPS observations were simultaneously carried out at five stations over a time span of 48 h and processed considering state-of-the-art techniques and sophisticated new approaches to reduce station-dependent errors. The comparison of GPS height differences with those from geometric-astronomical leveling shows a promising agreement of some millimeters. The experiment indicates the currently achievable accuracy level of GPS height measurements and demonstrates the practical applicability of the proposed approach for the validation of GNSS height measurements as well as the evaluation of GNSS height processing strategies

Regional Ground Movement Detection by Analysis and Modeling PSI Observations

Any changes to the Earth’s surface should be monitored in order to maintain and update the spatial reference system. To establish a global model of ground movements for a large area, it is important to have consistent and reliable measurements. However, in dealing with mass data, outliers may occur and robust analysis of data is indispensable. In particular, this paper will analyse Synthetic Aperture Radar (SAR) data for detecting the regional ground movements (RGM) in the area of Hanover, Germany. The relevant data sets have been provided by the Federal Institute for Geo-sciences and Natural Resources (BGR) for the period of 2014 to 2018. In this paper, we propose a data adoptive outlier detection algorithm to preprocess the observations. The algorithm is tested with different reference data sets and as a binary classifier performs with 0.99 accuracy and obtains a 0.95 F1-score in detecting the outliers. The RGMs that are observed as height velocities are mathematically modeled as a surface based on a hierarchical B-splines (HB-splines) method. For the approximated surface, a 95% confidence interval is estimated based on a bootstrapping approach. In the end, the user is enabled to predict RGM at any point and is provided with a measure of quality for the prediction