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<p>Bridges require data-driven management systems to ensure their prolonged operation, as such frameworks support the maintenance of transportation infrastructure. The entire lifecycle of a bridge depends on Geographic Information Systems (GIS), which utilize spatial analysis to perform essential functions. This review scrutinizes 600 publications indexed in Scopus from 2006 to 2023, aiming to investigate GIS applications in bridge management. The selection process was designed to be reproducible, utilizing searches within the Scopus database in January 2024 with the query TITLE-ABS-KEY ((“geographic information system*” OR GIS) AND bridge*), to retrieve relevant publications from titles, abstracts, and keywords. The focus was on peer-reviewed articles, reviews, and conference papers written in English within pertinent fields. The timeframe from 2006 to 2023 was selected due to its reflection of GIS technology’s evolution into an indispensable tool for civil infrastructure operations. VOSviewer software generated two types of networks, unveiling five thematic clusters: spatial data collection methods, geospatial analysis and decision-support systems, visualization techniques, Building Information Modeling (BIM), Structural Health Monitoring (SHM), and remote sensing integration. The results indicate a growing scholarly interest in bridge management, as evidenced by an increase in publications, and highlight leading researchers and institutions, alongside the expansion of international research collaborations. Moreover, the study identifies three significant knowledge gaps: AI-based spatial modeling, GNSS-based real-time monitoring, and IoT-based predictive maintenance systems. Currently, the literature lacks a dedicated bibliometric or scientometric analysis of GIS applications in bridge management, as most reviews concentrate on BIM–GIS or SHM systems rather than GIS-based workflows for bridge management. This research provides valuable insights into the intellectual landscape, while also emphasizing unexplored areas and proposing practical pathways to enhance bridge asset management through data-intensive methodologies.</p>

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Bibliometric analysis of GIS studies for bridge management: Trends, challenges, and future directions

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月29日

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  • Basim Younus Mohammed,
  • Nasradeen Ali Khalifa,
  • Seyed Jamalaldin Seyed Hakim,
  • Shahiron Bin Shahidan,
  • Sanaa Ali

摘要

Bridges require data-driven management systems to ensure their prolonged operation, as such frameworks support the maintenance of transportation infrastructure. The entire lifecycle of a bridge depends on Geographic Information Systems (GIS), which utilize spatial analysis to perform essential functions. This review scrutinizes 600 publications indexed in Scopus from 2006 to 2023, aiming to investigate GIS applications in bridge management. The selection process was designed to be reproducible, utilizing searches within the Scopus database in January 2024 with the query TITLE-ABS-KEY ((“geographic information system*” OR GIS) AND bridge*), to retrieve relevant publications from titles, abstracts, and keywords. The focus was on peer-reviewed articles, reviews, and conference papers written in English within pertinent fields. The timeframe from 2006 to 2023 was selected due to its reflection of GIS technology’s evolution into an indispensable tool for civil infrastructure operations. VOSviewer software generated two types of networks, unveiling five thematic clusters: spatial data collection methods, geospatial analysis and decision-support systems, visualization techniques, Building Information Modeling (BIM), Structural Health Monitoring (SHM), and remote sensing integration. The results indicate a growing scholarly interest in bridge management, as evidenced by an increase in publications, and highlight leading researchers and institutions, alongside the expansion of international research collaborations. Moreover, the study identifies three significant knowledge gaps: AI-based spatial modeling, GNSS-based real-time monitoring, and IoT-based predictive maintenance systems. Currently, the literature lacks a dedicated bibliometric or scientometric analysis of GIS applications in bridge management, as most reviews concentrate on BIM–GIS or SHM systems rather than GIS-based workflows for bridge management. This research provides valuable insights into the intellectual landscape, while also emphasizing unexplored areas and proposing practical pathways to enhance bridge asset management through data-intensive methodologies.