Optimally combined regional geoid models for the realization of height systems in developing countries (ORG4Heights)

The main objective is the formulation of a general scientific concept for the realization and establishment of height systems in countries with a low-quality terrestrial data basis, such as developing or newly industrializing countries, based on regionally enhanced gravity field models. This goal involves and requires two basic elements:

Objective 1:

Optimal combination of heterogeneous gravity data sets and derivation of realistic error estimates: We will develop methods and software which links new gravity satellite mission data and (low-quality) terrestrial data with the goal of an optimal spectral combination of different data sets utilizing the highest measure of information out of each observation technique. Further, the main error sources, such as omission errors of satellite gravity models and their impact on the definition of a physical height system, will be analysed. Numerical case studies for two test regions in Saudi Arabia (see Figure) and South America with different influencing factors such as poor or undefined terrestrial data quality, sparse and/or inhomogeneous data distribution as well as roughness of topography (and thus high amplitudes of high-frequency gravity field signals) shall be performed. The project aims at a comprehensive understanding and further development of methodology for a consistent combination of terrestrial and satellite gravity data, with special emphasis on specific limiting conditions imposed by the real world, but also the availability of new global gravity observation types such as GOCE gravity gradients.

Objective 2:

Establishment of height systems in developing countries: The achievable accuracy of a national/regional height system, consistently integrated into a globally uniform height system, shall be evaluated on the basis of case studies for the two test regions Saudi Arabia and South America, applying the GBVP and making use of available GPS and tide gauge records and an optimally combined regional gravity field model. The individual error sources shall be identified, quantified and propagated to the final product. The impact of the new satellite information shall be assessed in detail. The results shall be validated both internally as well as externally by making use of external data sources. Based on the results of the case studies and several test scenarios, a generalized scientific concept towards an optimal regional gravity solution and correspondingly the establishment or improvement of a physical height system and its integration into a global vertical reference frame shall be derived, with special emphasis on the constraints, limitations and specific boundary conditions of developing countries. Hereby, all methodological and practical aspects concerning processing strategies for data validation and combination shall be included. This generalized concept can then be used as guideline for further use in science and administration. Therefore, the project will combine fundamental, methodological development with a practical application with high socio-economic impact.

In summary, the proposed project includes a number of innovative key aspects:

  • scientific study on height system realization in developing countries
  • methodological development of regional combined gravity field determination for data-critical regions including uncertainty quantification
  • systematic investigation of omission errors for height system realization
  • quantification and treatment of systematic errors in practical realization of height systems
  • further development and practical realization of pyramidal algorithm in the frame of Multi-Resolution-Representation
  • recommendations for height system realization in developing and newly industrialized countries as guidelines for science and administration.
Multi-resolution representation of geoid heights in Saudi Arabia from simulated terrestrial data. The approximation signal of the highest level j = 11 is successively smoothed down to level j = 8 (low-pass filtering). Adding the related detail signals leads back to the original signal.