1887
  1. Home
  2. Conferences
  3. Conference Proceedings
  4. 18th International Conference on Geoinformatics - Theoretical and Applied Aspects
  5. Conference paper

Abstract

Summary

Ground Penetrating Radar (GPR) is a geophysical technique which is widely used to collect the data from near-surface part of underground. The use of GPR in the research and applications has been increasing recently. GPR data allow users to detect, analyze, visualize and interpret the underground structures easily and accurately. GPR is used for solving many problems related to the ground surveys, tunnels, archaeological excavations, geophysical applications, mining research, etc. The collected GPR data are made appropriate for interpretation of the underground structures by using different data processing techniques. The aim of this study is to propose the methodology to detect and visualize the anomalies based on GPR data. The proposed methodology was implemented on real GPR data. The obtained results showed that the proposed methodology allows users to detect and visualize underground anomalies with high accuracy.

© EAGE Publications BV
Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201902094
2019-05-15
2024-04-26

  • From This Site

    /content/papers/10.3997/2214-4609.201902094
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Annan, A.P.
    2009. Electromagnetic Principles of Ground Penetrating Radar. In Ground Penetrating Radar: Theory and Applications, edited by Harry M.Jol, pp. 3–40. Elsevier, Amsterdam.
     [Google Scholar]
  2. Cassidy, N.J.
    , 2009. Electrical and Magnetic Properties of Rocks, Soils and Fluids. In Ground Penetrating Radar: Theory and Applications, edited by Harry M.Jol, pp. 41–72. Elsevier, Amsterdam.
     [Google Scholar]
  3. Dojack, L.
    2012. Ground Penetrating Radar Theory, Data Collection, Processing, and Interpretation: A Guide for Archaeologists, 7–9.
     [Google Scholar]
  4. Lee, J.B., Sahai, S.K., Paxton, S.T. and Hadaway, S.
    2005. Ground Penetrating Radar In Sedimentary Rocks. 36th Annual Lunar and Planetary Science Conference, March 14–18, 2005.
     [Google Scholar]
  5. Li, W., Wen, J., Xiao, Z., & Xu, S.
    , 2018. Application of ground-penetrating radar for detecting internal anomalies in tree trunks with irregular contours. Sensors, Vol. 18(2), pp. 649.
     [Google Scholar]
  6. Neubauer, W., Eder-Hinterleitner, A., Seren, S., and Melichar, P.
    2002. Georadar in the Roman civil town Carnuntum, Austria: an approach for archaeological interpretation of GPR data. Archaeological Prospection, 9 (3), 135–156.
     [Google Scholar]
  7. Orlando, Luciana
    2007. Georadar Data Collection, Anomaly Shape and Archaeological Interpretation-a case study from Central Italy. Archaeological Prospection14, 213–225.
     [Google Scholar]
  8. Ozkan, M. and Samet, R.
    , 2017. Interpolation Techniques to Recover the Incomplete GPR Data. In: The 16th International Conference Geoinformatics, Kiev, Ukraine.
     [Google Scholar]
  9. Samet, R. and Ozkan, M.
    , 2017. An approach for 3D visualization of GPR data. In: The 16th International Conference Geoinformatics, Kiev, Ukraine.
     [Google Scholar]
  10. SametR., ÇelikE., TuralS., ŞengönülE., ÖzkanM., DamcıE.
    , 2017. Using interpolation techniques to determine the optimal profile interval in ground-penetrating radar applications. Vol. 140, pp. 154–167.
     [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201902094
Loading
An Approach to Detect and Visualize the Anomalies based on GPR Data
Conference Proceedings 2019, 1 (2019); https://doi.org/10.3997/2214-4609.201902094
/content/papers/10.3997/2214-4609.201902094
/content/papers/10.3997/2214-4609.201902094
Loading

Data & Media loading...

Most Cited This Month Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error