A Review of Ground Penetrating Radar for Underground Utility Detection and Subsurface Profiling: Challenges, Strategies and a Future-Oriented Framework

Paul, A, Jayapal, UM ORCID: 0000-0002-0550-4334 and Ayothiraman, R (2025) A Review of Ground Penetrating Radar for Underground Utility Detection and Subsurface Profiling: Challenges, Strategies and a Future-Oriented Framework. Indian Geotechnical Journal. pp. 1-22. ISSN 0971-9555

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Abstract

Urban underground environment is an intricate maze of utility lines and highly unpredictable geological conditions, making efficient space utilization a challenge. While the direct investigation techniques offer accuracy, their time-intensive and intrusive nature limits applicability in congested cityscapes. Nondestructive geophysical tools like ground-penetrating radar (GPR) has gained prominence for utility detection and subsurface characterization. However, GPR still faces persistent challenges affecting data quality, interpretability and overall survey reliability. This study aims to systematically identify, categorize and address the key challenges of implementing GPR for underground utility detection and subsurface profiling and develop a challenge-solution framework. Drawing on the comprehensive systematic literature review (spanning 2000–2024), bibliometric and scientometric analysis and firsthand observations from site visits to underground pipeline and metro projects, this study identifies fifty-one specific challenges, such as signal attenuation in clay-rich soils, clutter from overlapping utilities, productivity and workflow inefficiencies. These are synthesized into nine overarching categories—pertaining to technical limitations, data analysis issues, antenna-specific problems and more. Further, corresponding mitigation strategies and possible solutions are organized under seven actionable themes and a structured challenge-solution framework is developed, supporting practical implementation. The study concludes with a forward-looking roadmap, emphasizing the potential developments like multi-sensor fusion, machine learning algorithms, IoT integration and strategic trade-offs, to offer a holistic perspective to the researchers working to improve underground space diagnostics and planning.

Item Type:	Article
Additional Information:	This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://doi.org/10.1007/s40098-025-01378-1
Uncontrolled Keywords:	4005 Civil Engineering; 40 Engineering; 11 Sustainable Cities and Communities
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Civil Engineering and Built Environment
Publisher:	Springer Science and Business Media LLC
Date of acceptance:	7 August 2025
Date Deposited:	20 Oct 2025 10:25
Last Modified:	20 Oct 2025 10:30
DOI or ID number:	10.1007/s40098-025-01378-1
URI:	https://researchonline.ljmu.ac.uk/id/eprint/27377

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