4.4 Article

Analyses of GPR signals for characterization of ground conditions in urban areas

Journal

JOURNAL OF APPLIED GEOPHYSICS
Volume 152, Issue -, Pages 65-76

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jappgeo.2018.03.005

Keywords

Electromagnetic impedance; Ground penetrating radar; Reflection coefficient; Relative permittivity; Subsidence

Funding

  1. National Research Council of Science & Technology (NST) - Korea government (MSIP) [CRC-14-02-ETRI]

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Ground penetrating radar (GPR) is applied for the characterization of the ground conditions in urban areas. In addition, time domain reflectometry (TDR) and dynamic cone penetrometer (DCP) tests are conducted for the accurate analyses of the GPR images. The GPR images are acquired near a ground excavation site, where a ground subsidence occurred and was repaired. Moreover, the relative permittivity and dynamic cone penetration index (DCPI) are profiled through the TDR and DCP tests, respectively. As the ground in the urban area is kept under a low-moisture condition, the relative permittivity, which is inversely related to the electromagnetic impedance, is mainly affected by the dry density and is inversely proportional to the DCPI value. Because the first strong signal in the GPR image is shifted 180 degrees from the emitted signal, the polarity of the electromagnetic wave reflected at the dense layer, where the reflection coefficient is negative, is identical to that of the first strong signal. The temporal-scaled GPR images can be accurately converted into the spatial-scaled GPR images using the relative permittivity determined by the TDR test. The distribution of the loose layer can be accurately estimated by using the spatial-scaled GPR images and reflection characteristics of the electromagnetic wave. Note that the loose layer distribution estimated in this study matches well with the DCPI profile and is visually verified from the endoscopic images. This study demonstrates that the GPR survey complemented by the TDR and DCP tests, may be an effective method for the characterization of ground conditions in an urban area. (C) 2017 Elsevier B.V. All rights reserved.

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