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In this paper, we present an efficient kinematic ground-penetrating radar (GPR) surveying setup using a self- tracking total station (TTS). This setup combines the ability of modern GPR systems to interface with Global Positioning System (GPS) and the capability of the employed TTS system to immediately make the positioning information available in a standardized GPS data format. Wireless communication between the GPR and the TTS system is established by using gain variable radio modems. Such a kinematic surveying setup faces two major potential limitations. First, possible crosstalk effects between the GPR and the positioning system have to be evaluated. Based on multiple walkaway experiments, we show that, for reasonable field setups, instrumental crosstalk has no significant impact on GPR data quality. Second, we investigate systematic latency (i.e., the time delay between the actual position measurement by TTS and its fusion with the GPR data) and its impact on the positional precision of kinematically acquired 2-D and 3-D GPR data. To quantify latency for our kinematic survey setup, we acquired forward-reverse profile pairs across a well-known subsurface target. Comparing the forward and reverse GPR images using three fidelity measures allows determining the optimum latency value and correcting for it. Accounting for both of these potential limitations allows us to kinematically acquire high- quality and high-precision GPR data using off-the-shelf instrumentation without further hardware modifications. Until now, these issues have not been investigated in detail, and thus, we believe that our findings have significant implications also for other geophysical surveying approaches.
We have collected magnetic, 3D ground-penetrating-radar (GPR), and topographic data at an archaeological site within the Palace Garden of Paretz, Germany. The survey site covers an area of approximately 35 x 40 m across a hill structure (dips of up to 15 degrees) that is partly covered by trees. The primary goal of this study was to detect and locate the remains of ancient architectural elements, which, from historical records, were expected to be buried in the subsurface at this site. To acquire our geophysical data, we used a recently developed surveying approach that combines the magnetic and GPR instrument with a tracking total station (TTS). Besides efficient data acquisition, this approach provides positional information at an accuracy within the centimeter range. At the Paretz field site, this information was critical for processing and analyzing our geophysical data (in particular, GPR data) and enabled us to generate a high-resolution digital terrain model (DTM) of the surveyed area. Integrated analysis and interpretation based on composite images of the magnetic, 3D GPR, and high-resolution DTM data as well as selected attributes derived from these data sets allowed us to outline the remains of an artificial grotto and temple. Our work illustrates the benefit of using multiple surveying technologies, analyzing and interpreting the resulting data in an integrated fashion. It further demonstrates how modern surveying solutions allow for efficient, accurate data acquisition even in difficult terrain.
Three-dimensional (3D) ground-penetrating radar (GPR) represents an efficient high-resolution geophysical surveying method allowing to explore archaeological sites in a non-destructive manner. To effectively analyze large 3D GPR data sets, their combination with modern visualization techniques (e.g., 3D isoamplitude displays) has been acknowledged to facilitate interpretation beyond classical time-slice analysis. In this study, we focus on the application of data attributes (namely energy, coherency, and similarity), originally developed for petroleum reservoir related problems addressed by reflection seismology, to emphasize temporal and spatial variations within GPR data cubes. Based on two case studies, we illustrate the potential of such attribute based analyses towards a more comprehensive 3D GPR data interpretation. The main goal of both case studies was to localize and potentially characterize tombs inside medieval chapels situated in the state of Brandenburg, Germany. By comparing the calculated data attributes to the conventionally processed data cubes, we demonstrate the superior interpretability of the coherency and the similarity attribute for target identification and characterization.