Advanced search
1 file | 13.71 MB

Making sense of anomalies : practices and challenges in the archaeological interpretation of geophysical data

Lieven Verdonck (UGent) , Philippe De Smedt (UGent) and Jeroen Verhegge (UGent)
Author
Organization
Abstract
Geophysical data are an important source from which to study the human past, but need to be interpreted before they can be transformed into archaeological knowledge. The archaeological interpretation is affected by the complex relationship between buried features and measured anomalies. Most importantly, the presence of contrasts in physical properties between archaeological features and surrounding soil is essential. Furthermore, the interpretation is complicated by factors such as non-uniqueness and noise. It is also a subjective process, dependent on the prior knowledge of the interpreter. Notwithstanding these issues, the potential offered by geophysical data can be exploited more fully. In this chapter, four directions are proposed that can contribute to this. First of all, there is need for a more intensive debate about how geophysics can enhance archaeological understanding, and where its greatest potential lies. Secondly, it is illustrated how careful data acquisition and processing can result in a more reliable archaeological interpretation. Thirdly, we demonstrate how archaeological interpretation can be constrained, and uncertainty reduced, by combining different geophysical or remote sensing data, as well as results from field walking, coring and excavations, through side by side analysis or integration into a single image. Finally, the focus is on computer-aided object detection, which will likely assist the human interpreter increasingly when analysing ever growing data volumes, while also enabling a more objective interpretation. Two such approaches are discussed more in detail: template matching and object-based image analysis.
Keywords
archaeological prospection, geophysical survey, archaeological interpretation, uncertainty, data combination, data integration, object detection, computer vision, template matching, object-based image analysis

Downloads

  • (...).pdf
    • full text
    • |
    • UGent only
    • |
    • PDF
    • |
    • 13.71 MB

Citation

Please use this url to cite or link to this publication:

Chicago
Verdonck, Lieven, Philippe De Smedt, and Jeroen Verhegge. 2019. “Making Sense of Anomalies : Practices and Challenges in the Archaeological Interpretation of Geophysical Data.” In Innovation in Near-surface Geophysics : Instrumentation, Application, and Data Processing Methods, ed. Raffaele Persico, Salvatore Piro, and Neil Linford, 151–194. Amsterdam, The Netherlands: Elsevier.
APA
Verdonck, Lieven, De Smedt, P., & Verhegge, J. (2019). Making sense of anomalies : practices and challenges in the archaeological interpretation of geophysical data. In R. Persico, S. Piro, & N. Linford (Eds.), Innovation in near-surface geophysics : instrumentation, application, and data processing methods (pp. 151–194). Amsterdam, The Netherlands: Elsevier.
Vancouver
1.
Verdonck L, De Smedt P, Verhegge J. Making sense of anomalies : practices and challenges in the archaeological interpretation of geophysical data. In: Persico R, Piro S, Linford N, editors. Innovation in near-surface geophysics : instrumentation, application, and data processing methods. Amsterdam, The Netherlands: Elsevier; 2019. p. 151–94.
MLA
Verdonck, Lieven, Philippe De Smedt, and Jeroen Verhegge. “Making Sense of Anomalies : Practices and Challenges in the Archaeological Interpretation of Geophysical Data.” Innovation in Near-surface Geophysics : Instrumentation, Application, and Data Processing Methods. Ed. Raffaele Persico, Salvatore Piro, & Neil Linford. Amsterdam, The Netherlands: Elsevier, 2019. 151–194. Print.
@incollection{8577064,
  abstract     = {Geophysical data are an important source from which to study the human past, but need to be interpreted before they can be transformed into archaeological knowledge. The archaeological interpretation is affected by the complex relationship between buried features and measured anomalies. Most importantly, the presence of contrasts in physical properties between archaeological features and surrounding soil is essential. Furthermore, the interpretation is complicated by factors such as non-uniqueness and noise. It is also a subjective process, dependent on the prior knowledge of the interpreter. Notwithstanding these issues, the potential offered by geophysical data can be exploited more fully. In this chapter, four directions are proposed that can contribute to this. First of all, there is need for a more intensive debate about how geophysics can enhance archaeological understanding, and where its greatest potential lies. Secondly, it is illustrated how careful data acquisition and processing can result in a more reliable archaeological interpretation. Thirdly, we demonstrate how archaeological interpretation can be constrained, and uncertainty reduced, by combining different geophysical or remote sensing data, as well as results from field walking, coring and excavations, through side by side analysis or integration into a single image. Finally, the focus is on computer-aided object detection, which will likely assist the human interpreter increasingly when analysing ever growing data volumes, while also enabling a more objective interpretation. Two such approaches are discussed more in detail: template matching and object-based image analysis.},
  author       = {Verdonck, Lieven and De Smedt, Philippe and Verhegge, Jeroen},
  booktitle    = {Innovation in near-surface geophysics : instrumentation, application, and data processing methods},
  editor       = {Persico, Raffaele and Piro, Salvatore and Linford, Neil},
  isbn         = {9780128124291},
  language     = {eng},
  pages        = {151--194},
  publisher    = {Elsevier},
  title        = {Making sense of anomalies : practices and challenges in the archaeological interpretation of geophysical data},
  url          = {http://dx.doi.org/10.1016/B978-0-12-812429-1.00006-4},
  year         = {2019},
}

Altmetric
View in Altmetric