Abstract

With urban growth accelerating, cities increasingly need precise 3D information about their underground service networks to support sustainability goals and digital systems. Older 2D maps are often outdated, incomplete, and misaligned, making them difficult to use within 3D GIS environments. Moreover, conventional surveying tools may fall short in accuracy, struggle to reach buried assets, and require high costs when dealing with existing utilities. This thesis aims to develop and evaluate a field to 3D methodology for mapping underground utilities in Dubai, integrating multi-sensor and surveying approaches, and GIS 3D models in alignment with ASCE 38-22(American Society of Civil, 2022a), PAS 128(British Standards, 2022b), ASCE 75-22(American Society of Civil, 2022b), and CityGML Utility ADE(Kolbe et al., 2021). The study asks: (1) Can multi-sensor fusion improve positional accuracy, attribute completeness, and network consistency compared to legacy records? (2) How can international standards and semantic/exchange models be operationalized in a municipal context? (3) What workflow and QA practices are critical for reliable outcomes? (4) How can outputs be made twin-ready to support staged maturity (descriptive, reflective and predictive)? This study explores modern techniques for locating and documenting buried utility networks, with a focus on using laser-based and radar-based sensing tools to detect elements that are difficult to access directly. It outlines practical strategies for producing detailed 3D representations of subsurface assets and proposes a structured workflow for dependable utility mapping. A real project “Dubai Municipality’s Survey of Underground Utilities: Phase 1” is used to demonstrate how these methods perform in the field and how they support decision making during data capture. The research assesses various field collection practices, identifies gaps within the current utility records, and highlights the technical issues that arise when combining data from multiple sources. The thesis then highlights that implementing an integrated sensing and data management workflow resulted in substantial quality enhancements. The positional error was reduced to around 5 cm, and the completeness of descriptive attributes for wet utility elements reached full coverage. Topology errors, which were common in legacy data, were also greatly minimized. Improvements, however, differed between utility types: stormwater assets showed the strongest gains through chamber-based laser scans; sewer networks required low frequency radar and iii denser transects in saline or high groundwater areas; and irrigation features improved with detailed high frequency GPR. Standards were successfully operationalized, including PAS 128 accuracy bands, ASCE 38-22 quality levels, and ASCE 75-22 exchange structures, which underpinned the quality. Additionally, CityGML Utility ADE enabled semantic export for twin integration. The study concludes that combining several sensing technologies within a unified, standards- based workflow can reliably enhance the spatial accuracy and consistency of underground utility records in Dubai Municipality. Recording the method of capture, data lineage, and confidence for every mapped asset supports transparent quality checks, selective resurveying, and more informed approval decisions. The resulting 3D utility dataset forms a practical foundation for building subsurface digital twins starting with accurate representation, progressing to condition awareness, and eventually enabling scenario-based analysis as live inspection and operational data are added. Finally, the research identifies several challenges that still affect performance, such as reduced GPR penetration in areas with high salinity or moisture, GNSS signal disruptions, and limited access to chambers due to safety or operational constraints. Future work should compare positional accuracy across different utility types and soil environments, develop open training datasets for AI/ML tasks such as radargram interpretation and pipe classification, and test robotic or inertial tools for hard-to-reach pipelines. Integrating inspection or SCADA information will further support predictive digital twins, while trials in other international cities can help confirm wider applicability and guide updates to global standards.

Publication Date

12-2025

Document Type

Thesis

Student Type

Graduate

Degree Name

Professional Studies - City Sciences (MS)

Department, Program, or Center

Graduate Programs & Research

Advisor

Sanjay SM Modak

Advisor/Committee Member

Philippe PB Bouvier

Campus

RIT Dubai

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