Data processing issues in large‐area GPR surveys

Correcting trace misalignments, edge discontinuities and striping

Bibliographic Data

ID12429620
AuthorsEileen G Ernenwein (0000-0003-0190-4688, University of Arkansas at Fayetteville, corresponding author), Kenneth L Kvamme (0000-0002-9094-0156, University of Arkansas at Fayetteville)
Year2008
Volume15
Issue2
Pages133-149
Publication date2008-04-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueArchaeological Prospection (JOURNAL)
Journal identifiersISSN: 1075-2196 • E-ISSN: 1099-0763
PublisherWiley (PUBLISHER • GB)
DOI10.1002/arp.331
OpenAlexW2064844194
LanguageEN
Citations received6
References cited24

Ground‐penetrating radar (GPR) lags behind other archaeogeophysical methods in terms of speed, efficiency and ability to produce clean site‐wide composites owing to complex and time‐consuming data processing requirements. Two North American case studies illustrate problems that occur when survey is conducted over long and short periods of time. Some GPR defects have been blamed on differential solar heating of antennae and battery power levels but we show these effects to be negligible. Major problems include gradual changes over time in ground moisture and low‐level background noise, which can create discontinuities between adjacent survey blocks when data are collected at different times. These problems are often remedied by globally aligning traces using a stable trace position. Variations in ground moisture through time also cause differences in reflection amplitudes, necessitating different range gain curves to match amplitudes between survey blocks. In some cases changes in ground moisture cause noticeable differences in velocity between survey blocks requiring time‐scales to be converted to depths to correctly match the data. These problems must be remedied before horizontal slicing can be considered. Subsequent image processing may also be necessary to generate a seamless mosaic and eliminate striping artefacts commonly seen in slice maps. The latter are probably caused by antenna lift and tilt and can be removed by a de‐striping algorithm that uses a one‐dimensional low‐pass filter to characterize stripes followed by their subtraction from the data. Copyright © 2008 John Wiley & Sons, Ltd

Amplitude · Classification of discontinuities · Data striping · Ground-Penetrating Radar · Optics · Physics · Radar · Remote sensing · Telecommunications · Computer Science · Geophysical and Geoelectrical Methods · Geophysical Methods and Applications · Mathematics · Seismic Waves and Analysis · Geology

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