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A Python-Based Framework for the Transformation and Visualization of GNSS Data in Engineering and Geospatial Applications.

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Title: A Python-Based Framework for the Transformation and Visualization of GNSS Data in Engineering and Geospatial Applications.
Authors: Bălă, Alina Corina1 (AUTHOR) alina.bala@upt.ro, Brebu, Floarea-Maria1 (AUTHOR) floarea.brebu@upt.ro
Source: Journal of Applied Engineering Sciences. Dec2025, Vol. 15 Issue 2, p207-212. 6p.
Subjects: Python programming language, Software frameworks, Geographic information systems, Open source software, Visualization, Global Positioning System, Data transformations (Statistics)
Abstract: Global Navigation Satellite System (GNSS) observables are standardized in RINEX files, but most existing tools for position extraction are fragmented and require manual intervention. This paper introduces a Python-based framework that automates the processing of RINEX 2.11 observation files by extracting approximate receiver positions, transforming them into the WGS84 system, filtering invalid data, and exporting results in structured formats. The workflow produces multi-format outputs (CSV, KML, interactive maps), enabling direct integration with engineering and geospatial applications. Implemented in Google Colab with open-source libraries, the framework was validated on real datasets, demonstrating reproducibility, modularity, and scalability. The proposed approach supports diverse applications, including surveying, cadastral mapping, geodetic monitoring, and spatial data science. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Applied Engineering Sciences is the property of Paradigm Publishing Services and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: A Python-Based Framework for the Transformation and Visualization of GNSS Data in Engineering and Geospatial Applications.
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  Data: <searchLink fieldCode="AR" term="%22Bălă%2C+Alina+Corina%22">Bălă, Alina Corina</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> alina.bala@upt.ro</i><br /><searchLink fieldCode="AR" term="%22Brebu%2C+Floarea-Maria%22">Brebu, Floarea-Maria</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> floarea.brebu@upt.ro</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Applied+Engineering+Sciences%22">Journal of Applied Engineering Sciences</searchLink>. Dec2025, Vol. 15 Issue 2, p207-212. 6p.
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  Data: <searchLink fieldCode="DE" term="%22Python+programming+language%22">Python programming language</searchLink><br /><searchLink fieldCode="DE" term="%22Software+frameworks%22">Software frameworks</searchLink><br /><searchLink fieldCode="DE" term="%22Geographic+information+systems%22">Geographic information systems</searchLink><br /><searchLink fieldCode="DE" term="%22Open+source+software%22">Open source software</searchLink><br /><searchLink fieldCode="DE" term="%22Visualization%22">Visualization</searchLink><br /><searchLink fieldCode="DE" term="%22Global+Positioning+System%22">Global Positioning System</searchLink><br /><searchLink fieldCode="DE" term="%22Data+transformations+%28Statistics%29%22">Data transformations (Statistics)</searchLink>
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  Data: Global Navigation Satellite System (GNSS) observables are standardized in RINEX files, but most existing tools for position extraction are fragmented and require manual intervention. This paper introduces a Python-based framework that automates the processing of RINEX 2.11 observation files by extracting approximate receiver positions, transforming them into the WGS84 system, filtering invalid data, and exporting results in structured formats. The workflow produces multi-format outputs (CSV, KML, interactive maps), enabling direct integration with engineering and geospatial applications. Implemented in Google Colab with open-source libraries, the framework was validated on real datasets, demonstrating reproducibility, modularity, and scalability. The proposed approach supports diverse applications, including surveying, cadastral mapping, geodetic monitoring, and spatial data science. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Journal of Applied Engineering Sciences is the property of Paradigm Publishing Services and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.2478/jaes-2025-0024
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      – Code: eng
        Text: English
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        PageCount: 6
        StartPage: 207
    Subjects:
      – SubjectFull: Python programming language
        Type: general
      – SubjectFull: Software frameworks
        Type: general
      – SubjectFull: Geographic information systems
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      – SubjectFull: Open source software
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      – SubjectFull: Visualization
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      – SubjectFull: Global Positioning System
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      – SubjectFull: Data transformations (Statistics)
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            – D: 01
              M: 12
              Text: Dec2025
              Type: published
              Y: 2025
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