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Optimally combined regional geoid models for the realization of height systems in de-veloping countries

Subject Area Geodesy, Photogrammetry, Remote Sensing, Geoinformatics, Cartography
Term from 2016 to 2021
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 315916464
 
Final Report Year 2022

Final Report Abstract

The original objectives of this project are to develop methods for the optimal combination of heterogeneous gravity data sets and the derivation of realistic error estimates as well as to establish height systems in developing or newly industrializing countries. To fulfill these objectives, DGFI-TUM and APG have developed procedures and strategies based on the methods of SRBF and LSC, respectively. At DGFI-TUM, different types of SRBFs and their performance in regional gravity field modeling have been studied. A new regularization method has been developed by the combination of VCE for the relative weighting of the measurement techniques and the L-curve criterion for defining the regularization parameter in one single adjustment model. Another remarkable development is the spectral combination by exploiting the MRR based on wavelet theory and sequential parameter estimation to benefit from the individual strengths of the different measurement techniques in an optimal manner. It was demonstrated that the application of the MRR for data combination is particularly beneficial when the high-resolution observations (e.g., terrestrial data) do not have full coverage over the study area, e.g., in developing or newly industrializing regions. At APG, the LSC has been further developed to RLSC. In comparison to the standard LSC procedure, RLSC includes stochastic information on the reduction model. By this methodological extension, RLSC is able to model a location-dependent and inhomogeneous gravity field, which is beneficial for the modeling of the Earth’s gravity field at high spatial resolutions. Accordingly, RLSC provides better results and realistic estimation of the output accuracy, e.g., the gravity potential at the Earth’s surface. RLSC is then applied to real gravity observations, and a concept to consistently include low-pass filtered airborne gravity observations to the calculation is developed. Thereby, RLSC can result in an optimal combination of satellite, terrestrial and airborne gravity information, which is always considered as a main challenge in regional gravity field determination. The methods developed at DGFI-TUM and APG are applied for the height system realization in Colorado, as a replacement to the originally planned case study area Saudi Arabia, since the “1-cm geoid experiment” is considered as an essential step towards the realization of the IHRS. The participation in the “1-cm geoid experiment” also makes the validation of the developed procedures possible, as thirteen groups internationally contributed to this experiment with different modeling methodologies. To deal with the high-frequency noise of the airborne gravity data provided in this experiment, a new technique for low-pass filtering the airborne observations is developed at APG. At DGFI-TUM, the strategy of applying an SRBF with smoothing features as a low-pass filter is proposed. The comparison between all the thirteen solutions in the “1-cm geoid experiment” shows that DGFI-TUM and APG deliver two of the best results, which indicates the validity of the developed methods and procedures within this project. The computation details for the height system establishment in Colorado have been documented, and the calculated geoid and quasi-geoid models have been published. The output of this project is closely linked to the DFG-funded project “Enhanced geopotential field modeling as basis for the establishment of precise height systems (Geo-H)”, which could be regarded as a continuation of ORG4heights. The main objective of Geo-H is to develop the methodological foundation for the realization of modern geopotential-based height systems in agreement with the definitions of a global IHRS as well as a comprehensive error quantification. Thus, the developed procedures, the gained knowledge, and the identified potential improvements in methodologies within this project will further serve as a significant input to the new project Geo-H.

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