Experimental Assessment of the Stability of Velocity Vectors From Short-Term Campaign Gnss Observations Using Continuous Gnss Stations
Keywords:
Campaign GNSS, GAMIT/GLOBK, velocity vector, formal uncertaintyAbstract
This study aims to assess the stability and reliability of velocity vectors derived from short-term campaign GNSS observations. Data from the continuous GNSS station TVQS, installed on bedrock, and the MINT and KIT3 stations, located in sedimentary formations, were used in the experiment. To simulate campaign surveys using continuous observations, only epochs corresponding to days of year (DOY) 001, 090, 180, 270, and 360 of 2024 and DOY 090 and 180 of 2025 were selected; all intermediate days were excluded from the processing. The selected data were processed using the GAMIT/GLOBK software package, and six independent approximately 3-month solutions as well as cumulative 3-, 6-, 9-, 12-, 15-, and 18-month velocity solutions were estimated. The results show pronounced changes in both the magnitude and direction of the VE and VN components over 3-month intervals, whereas the velocity vectors progressively stabilize as the observation span increases, accompanied by an 83.3–85.3% reduction in formal uncertainties. The findings demonstrate that velocities derived from short-term campaign GNSS observations should be interpreted with caution when used as estimates of tectonic or technogenic deformationrates.
References
Blewitt G & Lavallée D (2002). Effect of annual signals on geodetic velocity. Journal of Geophysical Research: Solid Earth, 107(B7), ETG 9-1–ETG 9-11. https://doi.org/10.1029/2001JB000570
Fazilova D, Tukhtameshov F, Rakhimberdieva M, Kazakov A & Magdiev K (2025). GNSS-based subsidence monitoring of Shurtan's gas reservoir in Uzbekistan. Acta IMEKO, 14(1), 1–6. https://doi.org/10.21014/actaimeko.v14i1.1866
Herring T A, King R W, Floyd M A & McClusky S C (2018). Introduction to GAMIT/GLOBK, Release 10.7. Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology. https://geoweb.mit.edu/gg/
Lian X, Shi L, Kong W, Han Y & Fan H (2024). Residual subsidence time series model in mountain area caused by underground mining based on GNSS online monitoring. International Journal of Coal Science & Technology, 11, Article 27. https://doi.org/10.1007/s40789-024-00685-x
Mao A, Harrison C G A & Dixon T H (1999). Noise in GPS coordinate time series. Journal of Geophysical Research: Solid Earth, 104(B2), 2797–2816. https://doi.org/10.1029/1998JB900033
Nguyen H V, Pham K C, Nguyen D B & Nguyen L Q (2024). Application of the GNSS Method in the Monitoring of Mine Surface Displacement: A Systemic Review. Inżynieria Mineralna, 3(2). https://doi.org/10.29227/IM-2024-02-96
Şafak Ş, Tiryakioğlu İ, Erdoğan H, Solak H İ & Aktuğ B (2020). Determination of parameters affecting the accuracy of GNSS station velocities. Measurement, 164, 108003. https://doi.org/10.1016/j.measurement.2020.108003
Turen Y & Sanli D U (2019). Accuracy of Deformation Rates from Campaign GPS Surveys Considering Extended Observation Session and Antenna Set-Up Errors. Remote Sensing, 11(10), 1225. https://doi.org/10.3390/rs11101225
Williams S D P, Bock Y, Fang P, Jamason P, Nikolaidis R M, Prawirodirdjo L, Miller M & Johnson D J (2004). Error analysis of continuous GPS position time series. Journal of Geophysical Research: Solid Earth, 109(B3). https://doi.org/10.1029/2003JB002741
