... for the monitoring of large-scale deformations on the earth's surface between 2002 and 2012. In the proposed project the possibilities for the monitoring of subaerial deformations by combining large-scale and long-term levelling campaigns and (differential) SAR interferometry (D-InSAR) shall be investigated. The area of interest is the “Lower Rhine Embayment”, the Lowland, which extends northwards into the Rhenish Massif (German: Rheinisches Schiefergebirge). There are known subaerial deformations in the southern part near Cologne, North Rhine-Westphalia (Germany), which are caused by anthropogenic influences, especially underground mining and accordingly the extraction of underground resources. In a first study Halsig (2012) investigated, how D-InSAR could support conventional methods by the determination of surface deformation. Therefore, he compared ERS D- InSAR data with levelling measurements in the same time-span between 1993 and 2001. As there are also levelling data between 2001 and 2009 available, the idea of this project is to extend the investigation by using ENVISAT data between 2002 and 2012.

The satellite mission GOCE is dedicated to the precise modeling of the Earth's gravity field from satellite gravity gradiometry (SGG) and high-low satellite-to-satellite tracking (hl-SST) observations. Scientific data analysis will be carried out under ESA contract by a consortium of 10 European university and research institutes (EGG-C). In the framework of this contract, the Sub-Processing Facility (SPF) 6000, a co-operation of TU Graz, Austrian Academy of Sciences, University of Bonn, and TU Munich under the lead of TU Graz is responsible for the computation of an Earth's gravity field model from the GOCE data. The determination of approx. 70,000 parameters from several hundred million observations is a huge numerical task. For the rigorous solution of these large systems, the Core Solver, being based on parallel strategies on a PC cluster, is applied. Additionally, for the purpose of a quality assessment of the GOCE solution in parallel of the mission, the Quick-Look Gravity Field Analysis (QL-GFA) is applied.

The main goal of the project is the generation of a combined global gravity field model, by combining GOCE data with complementary data from the gravity field missions CHAMP and GRACE, and also other external data sets (terrestrial, air-borne, altimetry, etc.). Correspondingly, the proposed project primarily contributes to the determination of global and regional models of the Earth’s gravity field with high spatial resolution and accuracy, by further improving the GOCE-only gravity field model both with respect to accuracy and spatial resolution. The key tasks are the processing of GOCE, GRACE and CHAMP normal equations, the adequate treatment of complementary terrestrial gravity field information, and their fusion based on the addition of normal equations. Special concern is put on theoretical and methodological considerations concerning the optimum combination of different gravity field data types and their homogenization, including the problem of reference frames, standards, the optimum weighting of the individual contributions, and regularization issues. The project will be performed by a joint Austrian, Swiss and German research team, being composed of the Graz University of Technology (PI), the University of Bonn, the Technical University Munich and the University of Bern.

The main goal is to compute global Earth gravity field models and their (co)variance information on the basis of calibrated measurements from the GOCE satellite. To reach the high accuracy, GOCE combines to different sensor concepts. On the one hand, the low frequency of the signal is determined by satellite-to-satellite tracking where the orbit perturbance is determined by a GPS tracking of the satellite. On the other hand the high resolution part of the gravity field signal is determined from the satellite-gravity-gradiometry observations, where the gradiometer measures the second derivative of the potential via differential accelerations directly. As the main characteristics of the proposed procedure, the GOCE data are processed sequentially on a parallel computer system, iteratively via application of the method of preconditioned conjugate gradient multiple adjustment, and in situ via development of the functionals at the actual location and orientation of the gradiometer.