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dc.contributor.authorBolkas, Dimitrios
dc.contributor.otherQueen's University (Kingston, Ont.). Theses (Queen's University (Kingston, Ont.))en
dc.date2015-08-14 12:07:44.663en
dc.date.accessioned2015-08-19T22:07:54Z
dc.date.available2015-08-19T22:07:54Z
dc.date.issued2015-08-19
dc.identifier.urihttp://hdl.handle.net/1974/13509
dc.descriptionThesis (Ph.D, Geological Sciences & Geological Engineering) -- Queen's University, 2015-08-14 12:07:44.663en
dc.description.abstractThe 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.en_US
dc.languageenen
dc.language.isoenen_US
dc.relation.ispartofseriesCanadian thesesen
dc.rightsQueen's University's Thesis/Dissertation Non-Exclusive License for Deposit to QSpace and Library and Archives Canadaen
dc.rightsProQuest PhD and Master's Theses International Dissemination Agreementen
dc.rightsIntellectual Property Guidelines at Queen's Universityen
dc.rightsCopying and Preserving Your Thesisen
dc.rightsCreative Commons - Attribution - CC BYen
dc.rightsThis publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.en
dc.subjectWaveletsen_US
dc.subjectGOCEen_US
dc.subjectVariance component estimationen_US
dc.subjectLiDARen_US
dc.subjectMulti platform geodetic dataen_US
dc.subjectAccuracy assessment of topographic dataen_US
dc.subjectDigital elevation modelen_US
dc.subjectGravity data fusionen_US
dc.titleOn the Estimation of Uncertainties and Fusion of Multi-Platform Geodetic Dataen_US
dc.typethesisen_US
dc.description.degreePh.Den
dc.contributor.supervisorFotopoulos, Georgiaen
dc.contributor.departmentGeological Sciences and Geological Engineeringen


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