Startseite Assessment and fitting of high/ultra resolution global geopotential models using GNSS/levelling over Egypt
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Assessment and fitting of high/ultra resolution global geopotential models using GNSS/levelling over Egypt

  • Abdelaty Mohammed Zayed EMAIL logo , Ahmed Saber , Mostafa Hamama , Mostafa Rabah und Ahmed Zaki ORCID logo
Veröffentlicht/Copyright: 20. November 2024
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Abstract

This study conducts an evaluation of the performance of seven ultra-high-degree Global Geopotential Models (GGMs) across Egypt, utilizing GNSS/leveling data as a basis for assessment. The models under investigation include SGG-UGM-2, XGM2019e_2159, SGG-UGM-1, GECO, EIGEN-6C4, EGM2008, and GGMplus. The evaluation procedure comprises three principal steps: an absolute assessment, the implementation of Residual Terrain Modelling (RTM), and the fitting of GGMs to GNSS/leveling data. Among the models assessed, GECO exhibited the highest performance in the absolute assessment, achieving a standard deviation (STD) of 0.310 m, while SGG-UGM-1 recorded the largest STD at 0.353 m. Given Egypt’s predominantly flat topography, the application of RTM yielded only modest benefits. Nonetheless, all models demonstrated significant enhancements in accuracy through the fitting process, with EIGEN-6C4 emerging as the most successful model, attaining an STD of 0.116 m in external assessment. The accuracy improvements following the fitting procedure ranged from 49 % to 63 % across all models assessed.


Corresponding author: Abdelaty Mohammed Zayed, Mining Engineering Department, Faculty of Petroleum and Mining Engineering, Suez University, Suez, Egypt, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions (for double- anonymized journals: please use initials): All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

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

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Not applicable.

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Received: 2024-08-10
Accepted: 2024-09-26
Published Online: 2024-11-20
Published in Print: 2025-04-28

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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