Advertisement

Pure and Applied Geophysics

, Volume 173, Issue 8, pp 2737–2751 | Cite as

Texture Attribute Analysis of GPR Data for Archaeological Prospection

  • Wenke Zhao
  • Emanuele Forte
  • Michele Pipan
Article

Abstract

We evaluate the applicability and the effectiveness of texture attribute analysis of 2-D and 3-D GPR datasets obtained in different archaeological environments. Textural attributes are successfully used in seismic stratigraphic studies for hydrocarbon exploration to improve the interpretation of complex subsurface structures. We use a gray-level co-occurrence matrix (GLCM) algorithm to compute second-order statistical measures of textural characteristics, such as contrast, energy, entropy, and homogeneity. Textural attributes provide specific information about the data, and can highlight characteristics as uniformity or complexity, which complement the interpretation of amplitude data and integrate the features extracted from conventional attributes. The results from three archaeological case studies demonstrate that the proposed texture analysis can enhance understanding of GPR data by providing clearer images of distribution, volume, and shape of potential archaeological targets and related stratigraphic units, particularly in combination with the conventional GPR attributes. Such strategy improves the interpretability of GPR data, and can be very helpful for archaeological excavation planning and, more generally, for buried cultural heritage assessment.

Keywords

Archaeological prospection gray-level co-occurrence matrix (GLCM) ground-penetrating radar (GPR) texture attribute analysis 

Notes

Acknowledgments

We gratefully acknowledge the support of the International Centre for Theoretical Physics (ICTP, Trieste, Italy) Training on Research in Italian Laboratories (TRIL) programme, which sponsored the scholarship of the first author. We also thank dGB Earth Sciences for the OpendTect open source seismic data analysis software, and two anonymous reviewers for providing thoughtful and useful suggestions.

References

  1. Angelo, S.M., Matos, M., Marfurt, K.J. (2009). Integrated seismic texture segmentation and clustering analysis to improved delineation of reservoir geometry. In 2009 SEG Annual Meeting. Society of Exploration Geophysicists.Google Scholar
  2. Annan, A. P. (2003). Ground penetrating radar applications principles, procedures and applications. Mississauga: Sensors & Software Inc.Google Scholar
  3. Bini, M., Fornaciari, A., Ribolini, A., Bianchi, A., Sartini, S., & Coschino, F. (2010). Medieval phases of settlement at Benabbio castle, Apennine mountains, Italy: evidence from ground penetrating radar survey. Journal of Archaeological Science, 37(12), 3059–3067.CrossRefGoogle Scholar
  4. Böniger, U., & Tronicke, J. (2010). Integrated data analysis at an archaeological site: a case study using 3D GPR, magnetic, and high-resolution topographic data. Geophysics, 75(4), B169–B176.CrossRefGoogle Scholar
  5. Cavalier, M. (1981). Stromboli: villaggio preistorico di S. Vincenzo. Scavi Giugno 1980. Sicilia Archeologica Trapani, 14(46–47), 27–54.Google Scholar
  6. Chopra, S., & Alexeev, V. (2006). Applications of texture attribute analysis to 3D seismic data. The Leading Edge, 25(8), 934–940.CrossRefGoogle Scholar
  7. Chopra, S., & Marfurt, K.J. (2007). Seismic attributes for prospect identification and reservoir characterization: SEG/EAGE. (p. 464).Google Scholar
  8. Conyers, L. B. (2013). Ground-penetrating radar for archaeology (3rd ed., p. 258). Latham: Alta Mira Press.Google Scholar
  9. Conyers, L. B., & Leckebusch, J. (2010). Geophysical archaeology research agendas for the future: some ground-penetrating radar examples. Archaeological Prospection, 17(2), 117–123.Google Scholar
  10. Creasman, P. P., Sassen, D., Koepnick, S., & Doyle, N. (2010). Ground-penetrating radar survey at the pyramid complex of Senwosret III at Dahshur, Egypt, 2008: search for the lost boat of a Pharaoh. Journal of Archaeological Science, 37(3), 516–524.CrossRefGoogle Scholar
  11. de Matos, M. C., Yenugu, M., Angelo, S. M., & Marfurt, K. J. (2011). Integrated seismic texture segmentation and cluster analysis applied to channel delineation and chert reservoir characterization. Geophysics, 76(5), P11–P21.CrossRefGoogle Scholar
  12. Deiana, D. (2008). A texture analysis of 3D GPR images. Doctoral dissertation, TU Delft, Delft University of Technology, p. 71.Google Scholar
  13. Eichkitz, C. G., Amtmann, J., & Schreilechner, M. G. (2013). Calculation of grey level co-occurrence matrix-based seismic attributes in three dimensions. Computers and Geosciences, 60, 176–183.CrossRefGoogle Scholar
  14. Forte, E., & Pipan, M. (2008). Integrated seismic tomography and ground-penetrating radar (GPR) for the high-resolution study of burial mounds (tumuli). Journal of Archaeological Science, 35(9), 2614–2623.CrossRefGoogle Scholar
  15. Forte, E., Pipan, M., Casabianca, D., Di Cuia, R., & Riva, A. (2012). Imaging and characterization of a carbonate hydrocarbon reservoir analogue using GPR attributes. Journal of Applied Geophysics, 81, 76–87.CrossRefGoogle Scholar
  16. Gao, D. (2003). Volume texture extraction for 3D seismic visualization and interpretation. Geophysics, 68(4), 1294–1302.CrossRefGoogle Scholar
  17. Gao, D. (2011). Latest developments in seismic texture analysis for subsurface structure, facies, and reservoir characterization: a review. Geophysics, 76(2), W1–W13.CrossRefGoogle Scholar
  18. Goodman, D., Nishimura, Y., & Rogers, J. D. (1995). GPR time slices in archaeological prospection. Archaeological prospection, 2, 85–90.Google Scholar
  19. Grasmueck, M. (1996). 3-D ground-penetrating radar applied to fracture imaging in gneiss. Geophysics, 61(4), 1050–1064.CrossRefGoogle Scholar
  20. Hall-Beyer, M. (2007). GLCM texture tutorial, 2007. University of Calgary, 21 (Online document).Google Scholar
  21. Haralick, R. M., Shanmugam, K., & Dinstein, I. H. (1973). Textural features for image classification. IEEE Transactions on Systems, Man and Cybernetics, 6, 610–621.CrossRefGoogle Scholar
  22. Kaizer, H. (1955). A quantification of textures on aerial photographs. M.S. thesis, Boston University.Google Scholar
  23. Kokelaar, P., & Romagnoli, C. (1995). Sector collapse, sedimentation and clast population evolution at an active island-arc volcano: stromboli, Italy. Bulletin of Volcanology, 57(4), 240–262.CrossRefGoogle Scholar
  24. Leckebusch, J., & Peikert, R. (2001). Investigating the true resolution and three-dimensional capabilities of ground-penetrating radar data in archaeological surveys: measurements in a sand box. Archaeological Prospection, 8(1), 29–40.CrossRefGoogle Scholar
  25. Love, P. L., & Simaan, M. (1984). Segmentation of stacked seismic data by the classification of image texture. SEG Technical Program Expanded Abstracts, 3, 480–482.Google Scholar
  26. Lualdi, M., & Lombardi, F. (2014). Effects of antenna orientation on 3-D ground penetrating radar surveys: an archaeological perspective. Geophysical Journal International, 196(2), 818–827.CrossRefGoogle Scholar
  27. McClymont, A. F., Green, A. G., Streich, R., Horstmeyer, H., Tronicke, J., Nobes, D. C., et al. (2008). Visualization of active faults using geometric attributes of 3D GPR data: an example from the Alpine Fault Zone, New Zealand. Geophysics, 73(2), B11–B23.CrossRefGoogle Scholar
  28. Moysey, S., Knight, R. J., & Jol, H. M. (2006). Texture-based classification of ground-penetrating radar images. Geophysics, 71(6), K111–K118.CrossRefGoogle Scholar
  29. Patel, D., Giertsen, C., Thurmond, J., Gjelberg, J., & Grller, E. (2008). The seismic analyzer: interpreting and illustrating 2d seismic data. IEEE Transactions on Visualization and Computer Graphics, 14(6), 1571–1578.CrossRefGoogle Scholar
  30. Pérez-Gracia, V., Caselles, J. O., Clapes, J., Osorio, R., Martínez, G., & Canas, J. A. (2009). Integrated near-surface geophysical survey of the Cathedral of Mallorca. Journal of Archaeological Science, 36(7), 1289–1299.CrossRefGoogle Scholar
  31. Pipan, M., Baradello, L., Forte, E., & Finetti, I. (2001). Ground penetrating radar study of iron age tombs in southeastern Kazakhstan. Archaeological Prospection, 8(3), 141–155.CrossRefGoogle Scholar
  32. Pipan, M., Baradello, L., Forte, E., Prizzon, A., & Finetti, I. (1999). 2-D and 3-D processing and interpretation of multi-fold ground penetrating radar data: a case history from an archaeological site. Journal of Applied Geophysics, 41(2), 271–292.CrossRefGoogle Scholar
  33. Piro, S., Goodman, D., & Nishimura, Y. (2003). The study and characterization of Emperor Traiano’s Villa (Altopiani di Arcinazzo, Roma) using high-resolution integrated geophysical surveys. Archaeological Prospection, 10(1), 1–25.CrossRefGoogle Scholar
  34. Piro, S., Peloso, D., & Gabrielli, R. (2007). Integrated geophysical and topographical investigation in the territory of Ancient Tarquinia (Viterbo, central Italy). Archaeological Prospection, 14(3), 191–201.CrossRefGoogle Scholar
  35. Pitas, I., & Kotropoulos, C. (1992). A texture-based approach to the segmentation of seismic images. Pattern Recognition, 25(9), 929–945.CrossRefGoogle Scholar
  36. Randen, T., Monsen, E., Signer, C., Abrahamsen, A., Hansen, J.O., Sæter, T., Schlaf, J., Sønneland, L. (2000). Three-dimensional texture attributes for seismic data analysis. In 70th Annual International Meeting, Society of Exploration Geophysics Expanded Abstracts, Calgary, Canada, 668–671.Google Scholar
  37. Reed, T. R., & Dubuf, J. H. (1993). A review of recent texture segmentation and feature extraction techniques. CVGIP: Image understanding, 57(3), 359–372.CrossRefGoogle Scholar
  38. Reed, T. B., & Hussong, D. (1989). Digital image processing techniques for enhancement and classification of SeaMARC II side scan sonar imagery. Journal of Geophysical Research: Solid Earth (1978–2012), 94(B6), 7469–7490.CrossRefGoogle Scholar
  39. Rosi, M., Bertagnini, A., & Landi, P. (2000). Onset of the persistent activity at Stromboli volcano (Italy). Bulletin of volcanology, 62(4–5), 294–300.CrossRefGoogle Scholar
  40. Sassen, D. S., & Everett, M. E. (2009). 3D polarimetric GPR coherency attributes and full-waveform inversion of transmission data for characterizing fractured rock. Geophysics, 74(3), J23–J34.CrossRefGoogle Scholar
  41. Tavano, S. (1986). Aquileia e Grado: storia, arte e cultura, Ed. LINT, Trieste (in Italian).Google Scholar
  42. Trinks, I., Johansson, B., Gustafsson, J., Emilsson, J., Friborg, J., Gustafsson, C., et al. (2010). Efficient, large-scale archaeological prospection using a true three-dimensional ground-penetrating radar array system. Archaeological Prospection, 17, 175–186.CrossRefGoogle Scholar
  43. Urban, T. M., Rowan, Y. M., & Kersel, M. M. (2014). Ground-penetrating radar investigations at Marj Rabba, a Chalcolithic site in the lower Galilee of Israel. Journal of Archaeological Science, 46, 96–106.CrossRefGoogle Scholar
  44. Van der Baan, M., & Jutten, C. (2000). Neural networks in geophysical applications. Geophysics, 65(4), 1032–1047.CrossRefGoogle Scholar
  45. Vaughan, C. J. (1986). Ground-penetrating radar surveys used in archaeological investigations. Geophysics, 51(3), 595–604.CrossRefGoogle Scholar
  46. Verdonck, L., Vermeulen, F., Docter, R., Meyer, C., & Kniess, R. (2013). 2D and 3D ground-penetrating radar surveys with a modular system: data processing strategies and results from archaeological field tests. Near Surface Geophysics, 11(2), 239–252.Google Scholar
  47. West, B. P., May, S. R., Eastwood, J. E., & Rossen, C. (2002). Interactive seismic facies classification using textural attributes and neural networks. The Leading Edge, 21(10), 1042–1049.CrossRefGoogle Scholar
  48. Yenugu, M., Marfurt, K. J., & Matson, S. (2010). Seismic texture analysis for reservoir prediction and characterization. The Leading Edge, 29(9), 1116–1121.CrossRefGoogle Scholar
  49. Zhang, Z., & Simaan, M. (1987). A rule-based interpretation system for segmentation of seismic images. Pattern Recognition, 20(1), 45–53.CrossRefGoogle Scholar
  50. Zhao, W., Forte, E., Pipan, M., & Tian, G. (2013a). Ground penetrating radar (GPR) attribute analysis for archaeological prospection. Journal of Applied Geophysics, 97, 107–117.CrossRefGoogle Scholar
  51. Zhao, W., Tian, G., Wang, B., Forte, E., Pipan, M., Lin, J., et al. (2013b). 2D and 3D imaging of a buried prehistoric canoe using GPR attributes: a case study. Near Surface Geophysics, 11(4), 457–464.Google Scholar
  52. Zhao, W., Forte, E., Levi, S. T., Pipan, M., & Tian, G. (2015a). Improved high-resolution GPR imaging and characterization of prehistoric archaeological features by means of attribute analysis. Journal of Archaeological Science, 54, 77–85.CrossRefGoogle Scholar
  53. Zhao, W., Tian, G., Forte, E., Pipan, M., Wang, Y., Li, X., et al. (2015b). Advances in GPR data acquisition and analysis for archaeology. Geophysical Journal International, 202(1), 62–71.CrossRefGoogle Scholar
  54. Zhao, W., Forte, E., Colucci, R. R., & Pipan, M. (2016). High-resolution glacier imaging and characterization by means of GPR attribute analysis. Geophysical Journal International, 206, 1366–1374.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing 2016

Authors and Affiliations

  1. 1.Department of Mathematics and GeosciencesUniversity of TriesteTriesteItaly
  2. 2.School of Earth SciencesZhejiang UniversityHangzhouChina

Personalised recommendations