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Hyperspectral Sensors for the Characterization of Cultural Heritage Surfaces

  • Mara CamaitiEmail author
  • Marco Benvenuti
  • Pilario Costagliola
  • Francesco Di Benedetto
  • Sandro Moretti
Chapter
Part of the Geotechnologies and the Environment book series (GEOTECH, volume 16)

Abstract

The characterization of artistic and historical surfaces in a wide, fast, low-expense, and noninvasive way is a necessity for the conservation of these cultural assets. Hyperspectral sensors having bands in the visible-near infrared and short-wave infrared (VNIR-SWIR) regions are commonly used for determining the characteristics and properties of many materials (such as soils, minerals, rocks, water, vegetation) because of their ability to provide information in a fast and nondestructive way. Among the existing VNIR-SWIR techniques, field spectroscopy and imaging spectroscopy (remote sensing) have a crucial part in the characterization of different kinds of surfaces. In this work, the potentialities of hyperspectral sensors (working in the range 0.35–2.5 μm) for cultural heritage applications are discussed. The attention is focused both on field spectroscopy as a method for accurate characterization of small, confined, and highly heterogeneous surfaces and on imaging spectrometry obtained through field sensors. A few case studies where both techniques were employed are also reported.

Keywords

Imaging Spectroscopy Calcium Oxalate Painted Surface Black Crust Binding Medium 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors wish to thank the teams that have worked on the collection of many field and laboratory data, namely, Silvia Vettori, Elena Pecchioni, Teresa Salvatici, Leandro Chiarantini, Francesca Serraglini, Diletta Zecchi, and Cong Wang. A part of this work was supported by Regione Toscana in the framework of the agreement for Research and Technological transfer to productive system between the Italian Government and Regione Toscana (SKY-EYE project).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Mara Camaiti
    • 1
    Email author
  • Marco Benvenuti
    • 2
  • Pilario Costagliola
    • 2
  • Francesco Di Benedetto
    • 2
  • Sandro Moretti
    • 2
  1. 1.CNR-Institute of Geosciences and Earth ResourcesFlorenceItaly
  2. 2.Department of Earth SciencesUniversity of FlorenceFlorenceItaly

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