Accuracy Assessment of GPR Data for Buried Objects with Different Pipes and Soil-Based Conditions

Abstract

In terms of accuracy and speed, Ground Penetrating Radar (GPR) is the best approach for detecting and identifying underground utilities. This technology can precisely find a wide range of underground utilities, including both metallic and non-metallic materials. It analyses the ground by emitting a signal from an antenna at various frequencies of electromagnetic (EM) pulses. However, undesirable echoes caused by heterogeneous materials, such as the wide range of soil properties and utilities, are always present in these reflected signals. The site's soil composition has a direct influence on the accuracy of the GPR signal image. Thus, this study is carried out to evaluate the accuracy of GPR data for buried objects with different types of pipes between PVC and iron pipe in different soil characteristics: fine sand, topsoil and silt soil. The objective is to interpret the resolution of radargram images on different soil types due to different soil based characteristics and to evaluate the accuracy of depth values between GPR and conventional survey data sets for different pipes and soils using the RMSE formula. GPR Electronic TriVue with high frequency (1GHz) was employed, and the resolution of the resulting radargram image was post-processed in ReflexW software to yield promising depth results. Based on this research, the radargram obtained shows different textures that provides different presentations of each soil on the radargram image. Accuracy assessment from RMSE depth difference for Iron pipe depth for the three different soil types are: topsoil is 0.025 m, silt soil is 0.032 m, and fine sand is 0.087 m. While for PVC pipe topsoil is 0.035 m, silt soil is 0.038 m, and fine sand is 0.093 m. These differences show that iron pipe is more accurate compared with PVC in terms of tendency and fine sand is suitable soil in detection compared with topsoil and silt soil. In conclusion, the type of pipe play role in the choice of utility and soil properties (texture, moisture, and electrical conductivity) that impact the most on the accuracy assessment of GPR Data.