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.
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Copyright (c) 2026 Dilshoda Norboeva, Rukhiddin Turaev, Aziz Inamov, Khojiakbar Khasanov, Jasur Lapasov, Sanjarbek Safaev

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