Quality analysis of reference GPS stations in Ecuador
-
Richard Serrano-Agila
,
Rosendo Romero-Andrade
Abstract
Since 2008, Ecuador has established a Permanent Geodetic Network (REGME), to support geodetic research in the country. The REGME network plays a critical role in monitoring tectonic activity and crustal deformation throughout Ecuador. However, no comprehensive quality analysis has been conducted for REGME stations. The network has provided data from 70 continuous GPS stations across Ecuador, covering a period of 16 years. Shell scripts were developed on UNIX to manage and process REGME raw data. The data were converted from HATANAKA to RINEX format using CRX2RNX, and the sampling rate was standardized to 30 s using TEQC software. Only GPS signals were selected due to variations in the stations’ capabilities to track different signals. This study establishes a crucial foundation for future research on crustal deformation and geophysical phenomena in the region, offering valuable insights that will enhance both local and global geodetic efforts.
Acknowledgments
We thank to Ecuador Military Geographic Institute for getting access to REGME data. This research was supported by Universidad Técnica Particular de Loja, Ecuador, through Temporal Variations in Geodetic Positions Project.
-
Research ethics: Not applicable.
-
Informed consent: Not applicable.
-
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
-
Use of Large Language Models, AI and Machine Learning Tools: None declared.
-
Conflict of interest: The authors state no conflict of interest.
-
Research funding: None declared.
-
Data availability: https://www.geoportaligm.gob.ec/portal/.
References
1. Metzger, S, Ischuk, A, Deng, Z, Ratschbacher, L, Perry, M, Kufner, SK, et al.. Dense GNSS profiles across the Northwestern tip of the India-Asia collision zone: triggered slip and westward flow of the peter the first range, Pamir, into the Tajik depression. Tectonics 2020;39:1–20. https://doi.org/10.1029/2019tc005797.Search in Google Scholar
2. Sharma, G, Kannaujiya, S, Gautam, PKR, Taloor, AK, Champatiray, PK, Mohanty, S. Crustal deformation analysis across Garhwal Himalaya: part of western Himalaya using GPS observations. Quat Int 2021;575–576:153–9. https://doi.org/10.1016/j.quaint.2020.08.025.Search in Google Scholar
3. García-Armenteros, JA. Topo-Iberia CGPS network: a new 3D crustal velocity field in the Iberian Peninsula and Morocco based on 11 years (2008–2019). GPS Solut 2023;27:155. https://doi.org/10.1007/s10291-023-01484-8.Search in Google Scholar
4. Tsakiri, M, Sioulis, A, Piniotis, G. The use of low-cost, single-frequency GNSS receivers in mapping surveys. Surv Rev 2018;50:46–56. https://doi.org/10.1080/00396265.2016.1222344.Search in Google Scholar
5. Sharma, G, Champati ray, PK, Mohanty, S, Kannaujiya, S. Ionospheric TEC modelling for earthquakes precursors from GNSS data. Quat Int 2017;462:65–74. https://doi.org/10.1016/j.quaint.2017.05.007.Search in Google Scholar
6. Sharma, G, Romero-Andrade, R, Taloor, AK, Ganeshan, G, Sarma, KK, Aggarwal, SP. 2 – D ionosphere TEC anomaly before January 28 , 2020 , Cuba earthquake observed from a network of GPS observations data. Arabian J Geosci 2022;15:1–11. https://doi.org/10.1007/s12517-022-10605-5.Search in Google Scholar
7. Kaloop, MR, Yigit, CO, Dindar, AA, Elsharawy, M, Hu, JW. Evaluation of the high-rate GNSS-PPP method for vertical structural motion. Surv Rev 2020;52:159–71. https://doi.org/10.1080/00396265.2018.1534362.Search in Google Scholar
8. Romero-Andrade, R, Trejo-Soto, ME, Acosta-González, LE, Hernández-Andrade, D, Nayak, K, Hernández-Columbie, V, et al.. Displacements study of a dam using low-cost GNSS receivers, high precision leveling and Finite Element Model. Adv Geodesy and Geoinf 2024:55. [Internet] Available from: https://journals.pan.pl/dlibra/publication/150684/edition/133869/content.10.24425/agg.2024.150684Search in Google Scholar
9. Manandhar, S, Meng, YS. Analysis on the effect of different elevation cut-off angles on GPS time transfer. Meas Sens 2021;18:100196. https://doi.org/10.1016/j.measen.2021.100196.Search in Google Scholar
10. Angrisano, A, Ascione, S, Cappello, G, Gioia, C, Gaglione, S. Application of “Galileo high accuracy Service” on single-point positioning. Sensors 2023;23:4223. https://doi.org/10.3390/s23094223.Search in Google Scholar PubMed PubMed Central
11. Souto, MS. Análisis de calidad y preprocesamiento de datos GNSS de la estación permanente UCOR (Córdoba, Argentina). Rev Fac Ciencias Exactas Fis Nat 2014;1:91. [Internet] Available from: https://revistas.unc.edu.ar/index.php/FCEFyN/article/view/6971.Search in Google Scholar
12. Hernández-Andrade, D, Romero-Andrade, R, Sharma, G, Trejo-Soto, ME, Cabanillas-Zavala, JL. Quality assessment of continuous operating reference stations (CORS) – GPS stations in Mexico. Geod Geodyn 2022;13:275–87. https://doi.org/10.1016/j.geog.2021.12.003.Search in Google Scholar
13. Hu, Y, Cheng, L, Wang, X. Quality analysis of the campaign GPS stations observation in Northeast and North China. Geod Geodyn 2016;7:87–94. [Internet]. https://doi.org/10.1016/j.geog.2016.03.008.Search in Google Scholar
14. Quan, Y, Lau, L, Roberts, GW, Meng, X. Measurement signal quality assessment on all available and new signals of multi-GNSS (GPS, GLONASS, Galileo, BDS, and QZSS) with real data. J Navig 2016;69:313–34. https://doi.org/10.1017/s0373463315000624.Search in Google Scholar
15. Cole, B, Awange, JL, Saleem, A. Environmental spatial data within dense tree cover: exploiting multi-frequency GNSS signals to improve positional accuracy. Int J Environ Sci Technol 2020;17:2697–706. https://doi.org/10.1007/s13762-020-02634-y.Search in Google Scholar
16. Lee, D, Cho, J, Suh, Y, Hwang, J, Yun, H. A new window-based program for quality control of GPS sensing data. Rem Sens (Basel). 2012;4:3168–83. https://doi.org/10.3390/rs4103168.Search in Google Scholar
17. Franco-Patiño, DM, Seco-Granados, G, Dovis, F. Signal quality checks for multipath detection in GNSS. In: 2013 International Conference on Localization and GNSS, ICL-GNSS 2013. Turin, Italy; 2013:1–6 pp.10.1109/ICL-GNSS.2013.6577268Search in Google Scholar
18. Vázquez-Becerra, GE, Grejner-Brzeziska, DA. A case of study for pseudorange multipath estimation and analysis: TAMDEF GPS network. Geofis Int 2012;51:63–72. https://doi.org/10.22201/igeof.00167169p.2012.51.1.146.Search in Google Scholar
19. Vázquez, GE, Bennett, R, Spinler, J. Assessment of pseudorange multipath at continuous GPS stations in Mexico. Positioning 2013;04:253–65. https://doi.org/10.4236/pos.2013.43025.Search in Google Scholar
20. Xiao, Y, Yao, MH, Tang, SH, Liu, HF, Xing, PW, Zhang, Y. Data quality check and visual analysis of Cors station based on Anubis software. ISPRS – Int Arch Photogram, Rem Sens Spatial Inf Sci 2020;XLII-3/W10(November 2019):1295–300. https://doi.org/10.5194/isprs-archives-xlii-3-w10-1295-2020.Search in Google Scholar
21. Puskas, CM, Meertens, CM, Phillips, DA, Blume, F, Rost, M, UNAVCO. Introduction to Anubies software for GNSS quality control in the GAGE facility and NOTA. UNAVCO. UNAVCO; 2019. [Internet] Available from: https://www.unavco.org/data/gps-gnss/derived-products/docs/Poster_2019_SAGE-GAGE_Workshop_Puskas_Introduction-to-Anubis-software-for-GNSS-quality-control-in-the-GAGE-Facility-and-NOTA.pdf.Search in Google Scholar
22. Estey, LH, Meertens, CM. TEQC: the multi-purpose toolkit for GPS/GLONASS data. GPS Solut 1999;3:42–9. https://doi.org/10.1007/pl00012778.Search in Google Scholar
23. García-Armenteros, JA. Quality assessment of the Topo-Iberia CGPS stations and data quality’s effects on postfit ionosphere-free phase residuals. Geod Geodyn 2023;15:189–99. [Internet]. https://doi.org/10.1016/j.geog.2023.07.006.Search in Google Scholar
24. García-Armenteros, JA. Monitorización Y control de calidad de las estaciones de La red Cgps Topo-Iberia-UJA. Eur Sci J 2020;16:1. https://doi.org/10.19044/esj.2020.v16n24p1.Search in Google Scholar
25. Hernández-Andrade, D, Romero-Andrade, R, Cabanillas-Zavala, JL, Ávila-Cruz, M, Trejo-Soto, ME, Vega-Ayala, A. Análisis de calidad de las observaciones GPS en estaciones de operación continua de libre acceso en México. Eur Sci J 2020;16:332. https://doi.org/10.19044/esj.2020.v16n33p332.Search in Google Scholar
26. Lau, L, Tai, KW. A data quality assessment approach for high-precision GNSS continuously operating reference stations (CORS) with case studies in Hong Kong and Canada/USA. Rem Sens (Basel). 2023;15:1925. https://doi.org/10.3390/rs15071925.Search in Google Scholar
27. Hatanaka, Y. A compression format and tools for GNSS observation data. In: Bulletin of the geographical survey institute. 2008, vol 55:21–30 pp. Available from: https://www.gsi.go.jp/ENGLISH/Bulletin55.html.Search in Google Scholar
28. Gurtner, W. Innovation: RINEX--The receiver independent exchange format. GPS World 1994;5:48–53.Search in Google Scholar
29. Bradke, M, Ruddick, R, Rebischung, P, Steigenberger, P, Söhne, W, Maggert, D. Guidelines for continuously operating reference stations in the IGS. International GNSS Service. USA: IGS; 2023:1–9 pp.Search in Google Scholar
30. Llanes-Hernández, RM, Romero-Andrade, R, Guzmán-Galindo, TD, Santiago-Sánchez, LG, Serrano-Agila, RG. Control de calidad de las observaciones GPS de la Red Geodésica Nacional Activa en México del periodo 2020-2023. Eur Sci J, ESJ 2024;20:1. https://doi.org/10.19044/esj.2024.v20n21p1.Search in Google Scholar
31. Kamatham, Y., analysis and prediction of multipath error for static GNSS applications. In: 2018 Conference on Signal Processing and Communication Engineering Systems. SPACES, Vijayawada, India; 2018:62–5 pp.10.1109/SPACES.2018.8316317Search in Google Scholar
© 2025 Walter de Gruyter GmbH, Berlin/Boston
