On the Estimation of Uncertainties and Fusion of Multi-Platform Geodetic Data
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The main purpose of this thesis is to explore the synergies that exist between multi-platform geodetic data. Focus is placed on gravity and topography datasets which are obtained from satellite, airborne and terrestrial platforms. The assessment of uncertainties in these datasets is of prime importance in order to identify useful fusion algorithms and models. Today, geodetic satellite and airborne missions are often incorporated as part of observational survey campaigns and produce spatially homogeneous coverage of the Earth’s gravity field and topography. However, the accuracy of the data and the spatial resolution are often inferior compared to data acquired through conventional terrestrial survey methods. Thus, terrestrially-based measurements remain a valuable source of information. In this thesis, fusion of gravity data involves combination schemes, in the measurement domain, of gravity data acquired from satellite, airborne and terrestrial means. The resulting fused gravity-field models are of importance in the fields of geodesy and geophysics, as they enable centimeter-level geoid modeling (essential for accurate GPS-leveling) and improved modeling of the Earth’s crust and lithosphere (important for better understanding geodynamic processes), and aid geological interpretation (important for exploration geophysics). Uncertainty estimation is twofold and focused on estimating elevation errors in satellite-based digital elevation models (DEMs) and system measurement errors in airborne light detection and ranging (LiDAR) surveys. The quality of topographic information is useful for reliable quantitative analyses in applications such as hydrology, flood and inundation modeling and multi-temporal topographic elevation comparisons (e.g., erosion monitoring, rockslides and landslides). The main results of this research include (i) the determination of the relevance of airborne gravity data to fused multi-platform gravity-field models, (ii) the investigation of the role of ground control points for the quality assessment of DEMs, and (iii) the impact of a refined stochastic model for airborne LiDAR measurements in practical applications. Overall, this research provides a much needed guide on the challenges of working with multi-platform geodetic data measurements and the benefit of identifying the synergies between satellite, airborne and terrestrial platforms, leading to improved fused gravity field models and improved uncertainty estimations of topographic data.