Startseite Unificative methodology for determining recent dynamic parameters of tectonic plates based on GNSS data
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Unificative methodology for determining recent dynamic parameters of tectonic plates based on GNSS data

  • Ihor Savchyn ORCID logo EMAIL logo
Veröffentlicht/Copyright: 17. November 2025
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Journal of Applied Geodesy
Aus der Zeitschrift Journal of Applied Geodesy

Abstract

This study presents a unificative methodology for determining the latest dynamic parameters of tectonic plates, including moment of inertia, angular momentum, and kinetic energy, using data from continuous GNSS stations combined with information on crustal thickness and density from the CRUST1.0 model. The methodology treats the tectonic plate as a system of discrete volume cells, each with a defined mass and distance to the axis of rotation, which allows for accurate calculation of dynamic parameters. The approach has been tested on 7 large, 7 medium, and 3 microplates using data from 3169 GNSS stations for the period 2002–2021. The methodology provides an uncertainty of parameter estimation of less than 5.5 %, offering a new tool for detailed assessment of lithospheric dynamics and understanding the distribution of rotational energy in the Earth’s plates.


Corresponding author: Ihor Savchyn, Lviv Polytechnic National University, Lviv, Ukraine, E-mail:

Acknowledgments

This research was carried out within the framework of the Doctor of Science dissertation «Differentiation of the Kinematics of Tectonic Structures Based on GNSS Measurements». Open-access data and open-source software were employed, while licensed software was provided by Lviv Polytechnic National University. The author gratefully acknowledges the support and valuable discussions with colleagues from the Institute of Geodesy, Lviv Polytechnic National University, and expresses sincere gratitude to the reviewers for their constructive comments, which helped improve the manuscript.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The author has 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 author states no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: The author is willing to provide all intermediate data, calculation results, and analyses upon request for comparison and further research.

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Received: 2025-08-12
Accepted: 2025-10-21
Published Online: 2025-11-17

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Heruntergeladen am 23.11.2025 von https://www.degruyterbrill.com/document/doi/10.1515/jag-2025-0080/html
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