Factors affecting the fitting of a global geopotential model to local geodetic datasets over local areas in Egypt using multiple linear regression approach

Gomaa Dawod; Ghada Haggag

doi:10.1515/jag-2024-0102

Article

Factors affecting the fitting of a global geopotential model to local geodetic datasets over local areas in Egypt using multiple linear regression approach

Gomaa Dawod and Ghada Haggag

Published/Copyright: January 8, 2025

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From the journal Journal of Applied Geodesy Volume 19 Issue 3

Abstract

The increasing accuracy of the recently released Global Geopotential Models (GGMs) make them a reasonable geoid models, particularly in developing countries. Incorporating local geodetic datasets into a GGM could enhance its performance significantly. However, such integration requires appropriate mathematical modelling. The current research investigates the factors influencing the fitting of a GGM to heterogeneous geodetic data over local areas. The Multiple Linear Regression (MLR) approach is performed with variable independent factors to model the GGM discrepancies over two study areas in Egypt. Observed Global Navigation Satellite Systems (GNSS)/levelling and measured terrestrial gravity anomalies are investigated, among other independent variables, in the regression modelling. Based on the available data and attained findings, it has been demonstrated that MLR approach could produce a good fitting of a specific GGM’s geoid undulations, namely the XGM2019e_2159 model, locally with a coefficient of determination of more than 0.99. The regression equation has decreased the standard deviation of the investigated GGM-based undulations from ±0.130 m to ±0.046 m. Accordingly, the accuracy of a particular GGM has been enhanced considerably with improvements achieved 99 % and 64 % over the investigated two case study regions in Egypt.

Keywords: GGM; GNSS/Levelling; MLR; gravity; geoid; fitting

Corresponding author: Gomaa Dawod, Survey Research Institute, National Water Research Center, 308 Al-Ahram St., Talbia 11211, Giza, Egypt, E-mail: dawod_gomaa@yahoo.com

Research ethics: Not applicable.
Informed consent: Not applicable.
Author contributions: Gomaa Dawod has, reviewed the first manuscript, review the findings, finalize the conclusions, and prepare the final version. Ghada Haggag has prepared the first draft, collect the required datasets and participate in preparing the final version.
Use of Large Language Models, AI and Machine Learning Tools: None declared.
Conflict of interest: The authors state no conflict of interest.
Research funding: The authors declare that no funds were allocated to the current study.
Data availability: The data belongs to the Survey Research Institute and might be available by sending an email to: sri.nwrc_eg@yahoo.com.

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Received: 2024-11-24

Accepted: 2024-12-20

Published Online: 2025-01-08

Published in Print: 2025-07-28

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Articles in the same Issue

https://doi.org/10.1515/jag-2024-0102

Keywords for this article

GGM; GNSS/Levelling; MLR; gravity; geoid; fitting