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Modelling geoid height errors for local areas based on data of global models

  • Stepan Savchuk ORCID logo , Alina Fedorchuk ORCID logo EMAIL logo and Dorota Marjanska ORCID logo
Published/Copyright: October 2, 2024
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Journal of Applied Geodesy
From the journal Journal of Applied Geodesy Volume 19 Issue 2

Abstract

The development of global geoid models became feasible following the launch of specialised satellite missions. Today, the root mean square deviation of the heights in global models of high degree & order varies from centimetres to decimetres across different countries. In countries where the accuracy of such models is lower, there is potential to enhance their precision by applying specific corrections. This study presents a novel methodology for locally modelling the height errors of high degree & order global geoid models using levelling sub-benchmarks for GNSS stations. The methodology is based on a combination of optimal interpolation methods, filtering, and the concept of data weighting by gravity anomaly differences. The methodology is aimed at creating a hybrid model that aligns with the local characteristics of the geoid (or quasi-geoid) derived from the traditional levelling network. The advantage of this methodology lies in its ability to reduce the residual height errors of the EGM2008 and EIGEN6C4 models to less than 1 cm when using only four control points. Such results exceed the initial values of the systematic height errors of these models by 90–96 %. For the GECO model, the residual errors are around 2 cm, while for the XGM2019e_2159 model, they reach 3 cm. These results indicate that this methodology can be applied to all global models of high degree & order, although its effectiveness may vary depending on the specifics of a particular model.

Keywords: global models; GNSS/levelling; height errors; weights coefficient; modelling
Corresponding author: Alina Fedorchuk, Institute of Geodesy, Department of Geodesy and Astronomy, Lviv Polytechnic National University, Lviv, Ukraine, E-mail: 

Acknowledgments

The authors thank the ICGEM (International Centre for Global Earth Models) for the data of the heights and gravity anomaly; the BGI (Bureau Gravimetrique International) for the data of the free-air gravity anomaly by the WGM2012 model (World Gravity Map); the Head Office of Geodesy and Cartography of Poland for the data of heights anomaly by the quasi-geoid PLgeoid2021; the service of the Reference stations network of Poland (VRSNET, ASG-EUPOS) for the provided coordinates of GNSS stations.

  1. Research ethics: Not applicable.

  2. Author contributions: S.S. and A.F. conceived and designed the study; A.F. developed the methodology, software, and visualised the results; S.S. and A.F. conducted the formal analysis; S.S. and D.M. oversaw the project and provided the resources. S.S., A.F., and D.M. contributed to the writing – original draft, review, and editing. All authors read and approved the final manuscript.

  3. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  4. Competing interests: The authors state no conflict of interest.

  5. Research funding: None declared.

  6. Data availability: The raw data can be obtained accessed using links provided in this article.

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Received: 2024-06-18
Accepted: 2024-09-16
Published Online: 2024-10-02
Published in Print: 2025-04-28

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/jag-2024-0054
Keywords for this article
global models; GNSS/levelling; height errors; weights coefficient; modelling

Articles in the same Issue

  1. Frontmatter
  2. Original Research Articles
  3. Locally robust Msplit estimation
  4. Extending geodetic networks for geo-monitoring by supervised point cloud matching
  5. Evaluation and homogenization of a marine gravity database from shipborne and satellite altimetry-derived gravity data over the coastal region of Nigeria
  6. Modelling geoid height errors for local areas based on data of global models
  7. Unmanned aerial vehicle-based aerial survey of mines in Shanxi Province based on image data
  8. Ionospheric TEC and its irregularities over Egypt: a comprehensive study of spatial and temporal variations using GOCE satellite data
  9. Monitoring of volcanic precursors using satellite data: the case of Taftan volcano in Iran
  10. Modeling of temperature deformations on the Dnister HPP dam (Ukraine)
  11. Impact of temporal resolution in global ionospheric models on satellite positioning during low and high solar activity years of solar cycle 24
  12. Comparative performance of PPP software packages in atmospheric delay estimation using GNSS data
  13. Assessment and fitting of high/ultra resolution global geopotential models using GNSS/levelling over Egypt
  14. An efficient ‘P1’ algorithm for dual mixed-integer least-squares problems with scalar real-valued parameters
  15. Spatio-temporal trajectory alignment for trajectory evaluation
  16. Monitoring of networked RTK reference stations for coordinate reference system realization and maintenance – case study of the Czech Republic
  17. Crustal deformation in East of Cairo, Egypt, induced by rapid urbanization, as seen from remote sensing and GNSS data
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