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

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

On the quality checking of persistent scatterer interferometry by spatial- temporal modelling

[EN] Today, rapid growth in infrastructure development and urbanization process increases the attention for accurate deformation monitoring on a relatively large-scale. Furthermore, such deformation monitoring is of great importance in the assessment and management of natural hazard processes like landslides, earthquakes, and floods. In this study, the Persistent Scatterer Interferometry (PSI) technique is applied using open-source synthetic aperture radar (SAR) data from the satellite Sentinel-1. It allows point-wise deformation monitoring based on time series analysis of specific points. It also enables performing spatio-temporal area-based deformation monitoring. Currently, these data do not have a sophisticated quality assurance process to judge the significance of deformations. To obtain different quality classes of the Persistent Scatterer (PS) data points, the first step is to classify them into buildings and ground types using LoD2 building models. Next, time series analysis of the PS points is performed to model systematic and random errors. It allows estimation of the offset and the deformation rate for each point. Finally, spatio-temporal modelling of neighbourhood relations of the PS points is carried out using local geometric patches which are approximated with a mathematical model, such as, e.g., hierarchical B-Splines. Subsequently, the quality of SAR data from temporal and spatial neighbourhood relations is checked. Having an appropriate spatio-temporal quality model of the PS data, a deformation analysis is performed for areas of interest in the city of Hamburg. In the end, the results of the deformation analysis are compared with the BodenBewegungsdienst Deutschland (Ground Motion Service Germany) provided by the Federal Institute for Geosciences and Natural Resources (BGR), Germany.Omidalizarandi, M.; Mohammadivojdan, B.; Alkhatib, H.; Paffenholz, J.; Neumann, I. (2023). On the quality checking of persistent scatterer interferometry by spatial- temporal modelling. Editorial Universitat Politècnica de València. http://hdl.handle.net/10251/19237