Multicriteria Statistical Optimization of GPR Survey and Processing for Underground Utility Mapping: Case Study of the Leica DS2000 System

Urbanization of cities demands efficient spatial management. The construction of utility lines significantly alters the spatial landscape. The subsurface space is often neglected, resulting in outdated or absent records of underground utility infrastructure. This clearly underscores the need and importance of maintaining accurate utility records. Modern non-destructive techniques for underground utility detection, such as ground penetrating radar (GPR), can enhance the documentation and mapping of subsurface infrastructure. The subject of this paper is the optimization of GPR survey and processing workflows to improve the accuracy of underground utility detection when using the Leica DS2000. The research comprises both theoretical and experimental analyses, including the application of various GPR data collection methods on test sites. The experimental component of the research was conducted using the Leica DS2000 GPR system. The geospatial data were processed using several software applications, including uNext Advanced, IQMaps, and Geolitix. Based on the multicriteria analysis of these results and an assessment of detection accuracy, an optimal workflow (decision diagram) was defined for the detection of underground utility infrastructure using Leica DS2000 under favorable soil conditions. This study explored the feasibility of efficiently updating the cadastral database of public utility infrastructure through non-invasive technologies, thereby contributing to the improvement of subsurface utility infrastructure management.