Opportunities for Optimising the CORS Network in Uzbekistan: Proposals Based on Bibliometric Analysis
DOI:
https://doi.org/10.23917/forgeo.13569Keywords:
CORS network, GNSS optimization, Geodetic infrastructure, Uzbekistan, Coverage analysis, Bibliometric analysisAbstract
This study examines the optimisation of Continuously Operating Reference Station (CORS) networks through a combined bibliometric and spatial analysis approach, with particular reference to Uzbekistan as an illustrative case. A total of 522 publications were reviewed, of which 53 were identified as most relevant for detailed thematic analysis, as they provided insights into global research trends, methodological approaches, and applications in geodetic network design. To demonstrate how these approaches can be applied in practice, a simplified GIS-based spatial analysis was conducted in ArcGIS Pro to evaluate the distribution of existing CORS stations in Uzbekistan. A 40 km geodetic buffer was used as a representative distance derived from commonly reported baseline ranges in the literature (30-70 km). It should be emphasised that such a buffer-based approach only reflects spatial coverage and does not account for positioning accuracy, network geometry, or GNSS error sources. The results indicate uneven spatial coverage, with relatively dense station distribution in central and eastern regions, while western areas remain less represented. This finding is presented as a preliminary spatial observation rather than a validated assessment of network performance. Overall, the study does not aim to define optimal station spacing, or to provide a full technical evaluation, but rather to synthesise existing knowledge and demonstrate how simplified spatial methods can support initial planning. Future work should focus on integrating these insights with empirical GNSS data and advanced optimisation techniques for more robust network design.
Downloads
References
Abd Allah, A., & Wang, Z. (2022). Optimizing the geodetic networks based on the distances between the net points and the project border. Scientific Reports, 12(1). doi: 10.1038/s41598-021-04566-0
Abdallah, A., & Agag, T. (2022). Reliability of CSRS-PPP for Validating the Egyptian Geodetic Cors Networks. In Arti-ficial Satellites, 57(1), 58–76. doi: 10.2478/arsa-2022-0004
Al Shouny, A. (2025). Second-order design of GNSS networks with different constraints using particle swarm optimiza-tion and genetic algorithms. Open Engineering, 15(1), 20250109. doi: 10.1515/eng-2025-0109
Alluhaybi, A., Psimoulis, P., & Remenyte-Prescott, R. (2024). An Evaluation of Optimization Algorithms for the Opti-mal Selection of GNSS Satellite Subsets. Remote Sensing, 16(10). doi: 10.3390/rs16101794
Amiri-Simkooei, A. R., Asgari, J., Zangeneh-Nejad, F., & Zaminpardaz, S. (2012). Basic Concepts of Optimization and Design of Geodetic Networks. Journal of Surveying Engineering, 138(4), 172–183. doi: 10.1061/(ASCE)SU.1943-5428.0000081
Atiz, O. F., Konukseven, C., Ogutcu, S., & Alcay, S. (2022). Comparative analysis of the performance of Multi-GNSS RTK: A case study in Turkey. International Journal of Engineering and Geosciences, 7(1), 67–80. doi: 10.26833/ijeg.878236
Ayodele, E. G., Okolie, C. J., Ezeigbo, C. U., & Fajemirokun, F. A. (2020). Evaluating the Stability and Adequacy of NIGNET for the Definition of Nigerian Geodetic Reference Frame. Nigerian Journal of Technological Devel-opment, 17(1), 1–12. doi: 10.4314/njtd.v17i1.1
Bartonek, D., Bures, J., & Svabensky, O. (2017). Optimized GNSS RTK measurement planning for effective point occu-pation via heuristic analysis. Engineering Computations, 34(1), 90–104. doi: 10.1108/EC-11-2015-0352
Baselga, S., Klein, I., Suraci, S. S., de OLIVEIRA, L. C., Matsuoka, M. T., & Rofatto, V. F. (2020). Performance compari-son of least squares, iterative and global L1 norm minimization and exhaustive search methods for outlier de-tection in leveling networks. Acta Geodynamica et Geomaterialia, 17(4), 425–438). doi: 10.13168/AGG.2020.0031
Benoit, L., Briole, P., Martin, O., Thom, C., Malet, J.-P., & Ulrich, P. (2015). Monitoring landslide displacements with the Geocube wireless network of low-cost GPS. Engineering Geology, 195, 111–121. doi: 10.1016/j.enggeo.2015.05.020
Berné, J., & Baselga, S. (2004). First-order design of geodetic networks using the simulated annealing method. Journal Of Geodesy, 78(1–2), 47–54. doi: 10.1007/s00190-003-0365-y
Bevly, D., Cao, X., Gordon, M., Özbilgin, G., Kari, D., Nelson, B., Woodruff, J., Barth, M., Murray, C., & Kurt, A. (2016). Lane change and merge maneuvers for connected and automated vehicles: A survey. IEEE Transactions on In-telligent Vehicles, 1(1), 105–120. doi: 10.1109/TIV.2015.2503342
Bostanci, B., & Karaağaç, A. (2019). Investigating the shortest survey route in a GNSS traverse network. Tehnicki Vjesnik, 26(2), 355–362. doi: 10.17559/TV-20170924174221
Castaldo, R., de Nardis, R., De Novellis, V., Ferrarini, F., Lanari, R., Lavecchia, G., Pepe, S., Solaro, G., & Tizzani, P. (2018). Coseismic Stress and Strain Field Changes Investigation Through 3-D Finite Element Modeling of DInSAR and GPS Measurements and Geological/Seismological Data: The L’Aquila (Italy) 2009 Earthquake Case Study. Journal of Geophysical Research: Solid Earth, 123(5), 4193–4222. doi: 10.1002/2017JB014453
Chen, X., Ge, M., Hugentobler, U., & Schuh, H. (2022). A new parallel algorithm for improving the computational effi-ciency of multi-GNSS precise orbit determination. GPS Solutions, 26(3). doi: 10.1007/s10291-022-01266-8
Chhetri, I., Dechen Tshomo, Dawa Tshering, & Thinley Namgay. (2024). Evaluating the Positional Stability Status of the Druk Corsnet: A Preliminary Study. Journal of Applied Engineering, Technology and Management, 4(1), 49–59. doi: 10.54417/jaetm.v4i1.119
Dao, T., Harima, K., Carter, B., Currie, J., McClusky, S., Brown, R., Rubinov, E., & Choy, S. (2022). Regional Ionospher-ic Corrections for High Accuracy GNSS Positioning. Remote Sensing, 14(10). doi: 10.3390/rs14102463
Dardanelli, G., Lo Brutto, M., & Pipitone, C. (2020). GNSS cors network of the University of Palermo: Design and first analysis of data. Geographia Technica, 15 (1), 43–69. doi: 10.21163/GT_2020.151.05
Devi̇Ren, M. N., & Arikan, F. (2018). IONOLAB-MAP: An automatic spatial interpolation algorithm for total electron content. Turkish Journal of Electrical Engineering and Computer Sciences, 26(4), 1933–1945. doi: 10.3906/elk-1611-231
Eker, R., Alkan, E., & Aydın, A. (2021). A Comparative Analysis of UAV-RTK and UAV-PPK Methods in Mapping Dif-ferent Surface Types. European Journal of Forest Engineering, 7(1), 12–25. Scopus. doi: 10.33904/ejfe.938067
ESRI. (2022). ArcGIS Pro 3.0: Spatial Analysis and Geoprocessing [Computer software]. REtrieved From https://www.esri.com/arcgis-blog/products/arcgis-pro/
ESRI. (2023). ArcGIS Dashboards: Authoring and Visualization Guide [Computer software]. Retrieved From https://doc.arcgis.com/en/dashboards/
Farhan, M., Gomaa, M., & Sedeek, A. (2022). Optimization of baseline configuration in a GNSS network (Nile Delta network, Egypt) A case study. Journal Of Applied Geodesy, 16(4), 341–350. doi: 10.1515/jag-2022-0010
Fazilova, D. (2017). The review and development of a modern GNSS network and datum in Uzbekistan. In Geodesy and Geodynamics, 8(3), 187–192. doi: 10.1016/j.geog.2017.02.006
Fazilova, D., Magdiev, H., & Sichugova, L. (2021). GNSS network of Uzbekistan: Achievements, prospects and chal-lenges. doi: 10.5194/egusphere-egu21-842
Feng, Y., & Li, B. (2008). A benefit of multiple carrier gnss signals: Regional scale network-based RTK with doubled inter-station distances. In Journal of Spatial Science, 53(2), 135–147. doi: 10.1080/14498596.2008.9635154
Garbuglia, F., Spina, D., Deschrijver, D., Couckuyt, I., & Dhaene, T. (2023). Bayesian Optimization for Microwave De-vices Using Deep GP Spectral Surrogate Models. IEEE Transactions on Microwave Theory and Techniques, 71(6), 2311–2318. doi: 10.1109/TMTT.2022.3228951
Ghaffari Razin, M. R., & Voosoghi, B. (2016). Wavelet neural networks using particle swarm optimization training in modeling regional ionospheric total electron content. Journal of Atmospheric and Solar-Terrestrial Physics, 149, 21–30. doi: 10.1016/j.jastp.2016.09.005
Ghaffari Razin, M.-R., & Voosoghi, B. (2017). Ionosphere tomography using wavelet neural network and particle swarm optimization training algorithm in Iranian case study. GPS Solutions, 21(3), 1301–1314. doi: 10.1007/s10291-017-0614-9
Gokdas, O., & Ozludemir, M. T. (2021). Effect of altitude and distance on zenith tropospheric delay and integrated wa-ter vapour estimations in a local GNSS CORS network. Journal of Geodesy and Geoinformation, 8(1), 72–83. doi: 10.9733/JGG.2021R0006.E
Gökdaş, Ö., & Özlüdemir, M. T. (2022). Effects of the Continuously Operating Reference Station (CORS) network on the accuracy, precision, and Time to Fix Ambiguity (TTFA) performance; [Efectos de una red de Estaciones de Referencia de Operación Continua en exactitud, precisión y desempeño de la Resolución de Ambigüedades]. In Earth Sciences Research Journal, 26(2), 131–138. Universidad Nacional de Colombia. doi: 10.15446/esrj.v26n2.89819
Grafarend, E. W., & Sansò, F. (Eds.). (1985). Optimization and Design of Geodetic Networks. Springer Berlin Heidel-berg. doi: 10.1007/978-3-642-70659-2
Ibrahim Naibbi, A., & S. Ibrahim, S. (2014). An Assessment of the Existing Continuously Operating Reference Stations (CORS) in Nigeria: An Exploration Using Geographical Information System (GIS). Scientific & Academic Pub-lishing, 3(4), 147–157.
Kinoshita, Y., & Furuta, R. (2024). Slow slip event displacement on 2018 offshore Boso Peninsula detected by Senti-nel-1 InSAR time-series analysis with numerical weather model assistance. Geophysical Journal International, 237(1), 75–89. doi: 10.1093/gji/ggae028
Konstantzos, I., Tzempelikos, A., & Chan, Y.-C. (2015). Experimental and simulation analysis of daylight glare proba-bility inoffices with dynamic window shades. Building and Environment, 87, 244–254. doi: 10.1016/j.buildenv.2015.02.007
Kuang, S., & Chrzanowski, A. (1992). Multi-objective optimization design of geodetic networks. Manuscripta Geodae-tica, 17(4), 233–244. doi: 10.1007/BF03655487
Kudas, D., & Wnȩk, A. (2020). Validation of the number of tie vectors in post-processing using the method of frequency in a centric cube. Open Geosciences, 12(1), 242–255. doi: 10.1515/geo-2020-0057
Li, L., Zhang, H., Yuan, Y., Aichinger-Rosenberger, M., & Soja, B. (2024). On the real-time tropospheric delay estimates using low-cost GNSS receivers and antennas. Gps Solutions, 28(3). doi: 10.1007/s10291-024-01655-1
Łuszczek, P., Sid-Lakhdar, W. M., & Dongarra, J. (2023). Combining multitask and transfer learning with deep Gaussian processes for autotuning-based performance engineering. International Journal of High Performance Compu-ting Applications, 37(3–4), 229–244. doi: 10.1177/10943420231166365
MacNeil, M., & Bodur, M. (2022). Integer Programming, Constraint Programming, and Hybrid Decomposition Ap-proaches to Discretizable Distance Geometry Problems. INFORMS Journal on Computing, 34(1), 297–314. doi: 10.1287/ijoc.2020.1039
Madimarova, G. S., Nurpeissova, T., Kairatov, D., Suleimenova, D. N., & Zhantyeva, S. A. (2024). Inspection and carry-ing out GNSS monitoring of points of the state geodetic network in the territory of Kazakhstan. News of the National Academy of Sciences of the Republic of Kazakhstan, Series of Geology and Technical Sciences, 1, 179–189. doi: 10.32014/2024.2518-170X.374
Mahboub, V., Ebrahimzadeh, S., Baghani, A., Rastegar, A., & Zanganeh, M. (2024). L1-norm optimisation of rank defi-cient GNSS networks by an improved Grey Wolf method. Survey Review, 56(399), 582–588. doi: 10.1080/00396265.2024.2327124
Mahdi, H. A., & Ahmed, E. A. (2024). Assessment of the GNSS Data Collected at the Main Continuously Operating Reference Stations (CORS) of the Iraqi Geodetic Network. Journal of Engineering, 30(8), 120–135. doi: 10.31026/j.eng.2024.08.08
Maksimović, J., Kuzmić, T., Batilović, M., Sušić, Z., Bulatović, V., & Kanović, Ž. (2019). Rojektovanje geodetskih mreža primenom globalnih optimizacionih metoda. Zbornik radova Građevinskog fakulteta, 35, 975–984. doi: 10.14415/konferencijaGFS2019.090
Michal, O., & Štroner, M. (2024). A New Automated Algorithm for Optimization of Measurements for Achieving the Required Accuracy of a Geodetic Network. Applied Sciences (Switzerland), 14(11). doi: 10.3390/app14114890
Miranda, P. M. A., Adams, D. K., Tome, R., Fernandes, R., & Mateus, P. (2023). Optimizing Boundary Conditions in GNSS Tomography: A Continuous 7-Month Case Study in the Amazon. Geophysical Research Letters, 50(22). doi: 10.1029/2023GL105030
Miranda, P. M. A., & Mateus, P. (2022). Improved GNSS Water Vapor Tomography With Modified Mapping Functions. Geophysical Research Letters, 49(18). doi: 10.1029/2022GL100140
Ndirangu, D. M., Kenduiywo, B. K., & Waithaka, E. H. (2020). A web-based gis portal for simulating geodetic control networks in republic of Kenya. Geodesy and Cartography (Vilnius), 46(4), 170–181. doi: 10.3846/gac.2020.11211
Odam, D. S., Doma, M. I., El-Din Fawzy, H. I., Sedeek, A. A., & Farhan, M. H. (2023). Design of global positioning sys-tem (GPS) networks using different artificial intelligence techniques. Journal of Engineering Research (Ku-wait), 11(1), 14–25. doi: 10.36909/jer.10587
Odziemczyk, W. (2024). Comparison of selected reliability optimization methods in application to the second order design of geodetic network. Journal Of Applied Geodesy, 18(2), 223–236. (WOS:001061740200001). doi: 10.1515/jag-2023-0024
Pipitone, C., Maltese, A., Lo Brutto, M., & Dardanelli, G. (2023). A Review of Selected Applications of GNSS CORS and Related Experiences at the University of Palermo (Italy). Remote Sensing, 15(22). Multidisciplinary Digi-tal Publishing Institute (MDPI). https://doi.org/10.3390/rs15225343
Postek, P. (2021). New Computer Simulation Method for First-Order Design of Geodetic Network: Aiming for Low Cost. Journal of Surveying Engineering, - ASCE, 147(1). Scopus. doi: 10.1061/(ASCE)SU.1943-5428.0000334
Prochniewicz, D., Szpunar, R., Kozuchowska, J., Szabo, V., Staniszewska, D., & Walo, J. (2020). Performance of Net-work-Based GNSS Positioning Services in Poland: A Case Study. Journal of Surveying Engineering, 146(3), 05020006. doi: 10.1061/(ASCE)SU.1943-5428.0000316
Rahman, N. A. A., Musa, T. A., Wan Aris, W. A., & Omar, A. H. (2023). Proposed strategy to obtain optimum inter-station distance for GPS CORS development scenario. The International Archives of the Photogrammetry, Re-mote Sensing and Spatial Information Sciences, XLVIII-4/W6-2022, 431–437. doi: 10.5194/isprs-archives-XLVIII-4-W6-2022-431-2023
Rahmani, M., Nafisi, V., Asgari, J., & Nadimi, A. (2023). Crustal deformatıon ın NW Iran: Insıghts from dıfferent ın-varıant and varıant components of geodetıc straın rate tensors. In M. Delavar, R. Abbaspour, & S. Farzaneh (Eds.), University of Isfahan, 631–637. (WOS:001185799100090). doi: 10.5194/isprs-annals-X-4-W1-2022-631-2023
Ruziev, A., Yusupjonov, O., Földváry, L., Okhunov, Z., Rakhimov, S., Rakhmonov, S., & Yakubov, G. (2024). Devel-opment stages of the geodetic network in Tashkent city. E3S Web of Conferences, 590, 03006. doi: 10.1051/e3sconf/202459003006
Sathiakumar, S., Barbot, S. D., & Agram, P. (2017). Extending Resolution of Fault Slip With Geodetic Networks Through Optimal Network Design. In Journal of Geophysical Research: Solid Earth, 122(12), 10,538-10,558. doi: 10.1002/2017JB014326
Savanovic, M., Savanovic, R., Ninkov, T., & Sabados, I. (2015). Proposed Design Of Local 2d Geodetic Network For The Construction Of The Tunnel Part Of The Belgrade Metro. Geodetski Vestnik, 59(3), 564–576. (Wos:000368352700009).
Schmitt, G. (1982). Optimization of geodetic networks. Reviews of Geophysics, 20(4), 877–884. doi: 10.1029/RG020i004p00877
Schwieger, V., Lilje, M., & Sarib, R. (2019). GNSS CORS - Reference Frames and Services. International Federation of Surveyors.
Snay, R. A., & Soler, T. (2008). Continuously Operating Reference Station (CORS): History, Applications, and Future Enhancements. Journal of Surveying Engineering, 134(4), 95–104. doi: 10.1061/(ASCE)0733-9453(2008)134:4(95)
Suyunov, A., Urakov, O., Mirzaev, A., & Mullodjanova, G. (2023). The results of the analysis of the accuracy of the permanent satellite state geodetic network in the Republic of Uzbekistan. In A. Gibadullin & S. Sadullozoda (Eds.), 2nd International Conference on Computer Applications for Management and Sustainable Develop-ment of Production and Industry (CMSD-II-2022), 53. doi: 10.1117/12.2669915
Tang, M. (2015). A Memetic Algorithm for the Location-Based Continuously Operating Reference Stations Placement Problem in Network Real-Time Kinematic. In IEEE Transactions on Cybernetics, 45(10), 2214–2223. doi: 10.1109/TCYB.2014.2367499
Tuna, H., Arikan, O., & Arikan, F. (2015). Regional model-based computerized ionospheric tomography using GPS measurements: IONOLAB-CIT. Radio Science, 50(10), 1062–1075. doi: 10.1002/2015RS005744
Wang, G. (2023). Seasonal Subsidence and Heave Recorded by Borehole Extensometers in Houston. Journal of Survey-ing Engineering, - ASCE, 149(1). doi: 10.1061/JSUED2.SUENG-1369
Wang, H., H Souri, A., González Abad, G., Liu, X., & Chance, K. (2019). Ozone Monitoring Instrument (OMI) Total Column Water Vapor version 4 validation and applications. Atmospheric Measurement Techniques, 12(9), 5183–5199. doi: 10.5194/amt-12-5183-2019
Wanninger, L. (2002). Virtual Reference Stations for Centimeter-Level Kinematic Positioning. 1400--1407.
Xiao, L., Si, C., Ye, X., Zhang, B., & Qin, G. (2022). Analysis of the influence caused by UPD on GNSS positioning us-ing SDCP measurements. In L. Y & C. C (Eds.), Proceedings of SPIE - The International Society for Optical Engineering, 12260. doi: 10.1117/12.2637397
Yang, F., Meng, X., Guo, J., Yuan, D., & Chen, M. (2021). Development and evaluation of the refined zenith tropospher-ic delay (ZTD) models. In Satellite Navigation, 2(1). doi: 10.1186/s43020-021-00052-0
Yang, Y., Liu, Y., Sun, D., Xu, T., Xue, S., Han, Y., & Zeng, A. (2020). Seafloor geodetic network establishment and key technologies. Science China Earth Sciences, 63(8), 1188–1198. doi: 10.1007/s11430-019-9602-3
Yetkin, M., & Inal, C. (2015). Optimal Design of Deformation Monitoring Networks Using the Global Optimization Methods. In H. Kutterer, F. Seitz, H. Alkhatib, & M. Schmidt (Eds.), The 1st International Workshop on the Quality of Geodetic Observation and Monitoring Systems (QuGOMS’11), 140, 27–31. doi: 10.1007/978-3-319-10828-5_5
Yu, C., Li, Z., Penna, N. T., & Crippa, P. (2018). Generic Atmospheric Correction Model for Interferometric Synthetic Aperture Radar Observations. In Journal of Geophysical Research: Solid Earth, 123(10), 9202–9222. doi: 10.1029/2017JB015305
Yu, C., Penna, N. T., & Li, Z. (2020). Optimizing Global Navigation Satellite Systems network real-time kinematic in-frastructure for homogeneous positioning performance from the perspective of tropospheric effects. Proceed-ings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 476(2242), 20200248. doi: 10.1098/rspa.2020.0248
Yu, H., Sosnica, K., & Shen, Y. (2020). Separation of geophysical signals in the LAGEOS geocentre motion based on singular spectrum analysis. In Geophysical Journal International, 225(3), 1755–1770. doi: 10.1093/gji/ggab063
Yurdakul, Ö., & Kalayci, İ. (2022). The effect of GLONASS on position accuracy in CORS-TR measurements at differ-ent baseline distances. International Journal of Engineering and Geosciences, 7(3), 229–246. doi: 10.26833/ijeg.975204
Zekollari, H., Huss, M., & Farinotti, D. (2019). Modelling the future evolution of glaciers in the European Alps under the EURO-CORDEX RCM ensemble. Cryosphere, 13 (4), 1125–1146. doi: 10.5194/tc-13-1125-2019
Zhang, S., Foerster, S., Medeiros, P., de Araújo, J. C., Motagh, M., & Waske, B. (2016). Bathymetric survey of water res-ervoirs in north-eastern Brazil based on TanDEM-X satellite data. Science of the Total Environment, 571, 575–593. doi: 10.1016/j.scitotenv.2016.07.024
Zheng, Y., Wang, S., & Wang, S. (2019). Effective efficiency advantage assessment of information filter for convention-al kalman filter in gnss scenarios. Sensors, 19(18). doi: 10.3390/s19183858
Downloads
Submitted
Accepted
Published
Issue
Section
License
Copyright (c) 2026 Dilshoda Norboeva
This work is licensed under a Creative Commons Attribution 4.0 International License.
