Hyperspectral Sensors for the Characterization of Cultural Heritage Surfaces

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


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.


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.



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).


  1. Agapiou A, Hadjimitsis DG (2011) Vegetation indices and field spectral-radiometric measurements for validation of buried architectural remains: verification under area surveyed with geophysical campaigns. J Appl Remote Sens 5(1):053554–053551. doi: 10.1117/1.3645590 CrossRefGoogle Scholar
  2. Agapiou A, Hadjimitsis DG, Alexis D et al (2012) Osservatory validation of Neolithic tells (“Megoules”) in the Thessalian plain, central Greece, using hyperspectral spectroradiometric data. J Archaeol Sci 35(5):1499–1512CrossRefGoogle Scholar
  3. Agapiou A, Hadjimitsis DG, Sarris A et al (2013) Optimum temporal and spectral window for monitoring crop marks over archaeological remains in the Mediterranean region. J Archaeol Sci 40:1479–1492CrossRefGoogle Scholar
  4. Alexakis D D, Agapiou A, Hadjimitsis D G et al (2012) Remote sensing applications in archaeological research. doi:  10.5772/37668
  5. Aloupi E, Karydas AG, Paradellis T (2000) Pigment analysis of wall paintings and ceramics from Greece and Cyprus: the optimum use of X-ray spectrometry on specific archaeological issues. X-Ray Spectrom 29(1):18–24CrossRefGoogle Scholar
  6. Alparone L et al (2011) Hyperspectral instruments as potential tools for monitoring decay processes of historical building surfaces. In: Fioravanti M, Mecca S (eds) Proceedings of the safeguard of cultural heritage—a challenge from the past for the Europe of tomorrow, Florence, 2011Google Scholar
  7. Bacci M (1995) Fibre optics applications to works of art. Sensor Actuat B 29:190–196CrossRefGoogle Scholar
  8. Bacci M, Casini A, Cucci C et al (2003) Non-invasive spectroscopic measurements on the Il ritratto della figliastra by Giovanni Fattori: identification of pigments and colourimetric analysis. J Cult Herit 4:329–336CrossRefGoogle Scholar
  9. Balas C, Papadakis V, Papadakis N et al (2003) A novel hyper-spectral imaging apparatus for the non-destructive analysis of objects of artistic and historic value. J Cult Herit 4:330s–337sCrossRefGoogle Scholar
  10. Benvenuti M et al (2009) A portable hyperspectral device for monitoring the chemical and mineralogical composition of historical buildings surfaces. Paper presented at the 4th International Congress on Science and Technology for the safeguard of cultural heritage in the Mediterranean Basin, Cairo, Egypt, 6–8 December 2009Google Scholar
  11. Camaiti M, Benvenuti M, Chiarantini L et al (2011) Hyperspectral sensor for gypsum detection on monumental buildings. J Geophys Eng 8:S126–S131CrossRefGoogle Scholar
  12. Camaiti M et al (2013) Monitoring of chemical and physical characteristics of stone surfaces by a portable spectroradiometer. In: Geophysical Research Abstracts of EGU General Assembly 2013, Wien, 7–12 April 2013, vol 15, p 13552Google Scholar
  13. Campbell JB (2002) Introduction to remote sensing, third edn. Taylor & Francis, LondonGoogle Scholar
  14. Clark RN (1999) Spectroscopy of rocks and minerals, and principles of spectroscopy. In: Rencz A (ed) Manual of remote sensing. Wiley, New York, pp 1–63Google Scholar
  15. Clark RN, King TVV, Klejwa M et al (1990) High spectral resolution reflectance spectroscopy of minerals. J Geophys Res 95(B8):12653–12680CrossRefGoogle Scholar
  16. Craig N, Speakman RJ, Popelka-Filcoff RS et al (2007) Comparison of XRF and PXRF for analysis of archaeological obsidian from Southern Perú. J Archaeol Sci 34(12):2012–2024CrossRefGoogle Scholar
  17. Cucci C et al (2015) Hyperspectral remote sensing techniques applied to the non invasive investigation of mural paintings: a feasibility study carried out on a wall painting by Beato Angelico in Florence. In: Pezzati L, Targowski P (eds) Proceedings SPIE 9527: Optics for Arts, Architecture, and Archaeology V, Munich, June 2015. doi: 10.1117/12.2184743
  18. Di Benedetto F et al (2014) Hyperspectral monitoring of marble in buildings: a case study of the Santa Maria del Fiore (Florence, Italy) facades. In: Abstracts of the 21st general meeting of the International Mineralogical Association (IMA 2014), Sandton, Johannesburg, 1–5 September 2014Google Scholar
  19. Doehene E, Price CA (2010) Stone conservation: an overview of current research, second edition. Getty Publications, The Getty Conservation Institute, Los AngelesGoogle Scholar
  20. Dolske DA (1995) Deposition of atmospheric pollutants to monuments, statues, and buildings. Sci Total Environ 167:15–31CrossRefGoogle Scholar
  21. Favaro M, Mendichi R, Ossola F et al (2007) Evaluation of polymers for conservation treatments of outdoor exposed stone monuments. Part II: Photo-oxidative and salt-induced weathering of acrylic silicone mixtures. Polym Degrad Stab 92:335–351CrossRefGoogle Scholar
  22. Frediani P, Manganelli del Fá C, Matteoli U et al (1982) Use of perfluoropolyethers as water repellents: study of their behaviour on Pietra Serena, a fiorentine building stone. Stud Conserv 27:31–37CrossRefGoogle Scholar
  23. Gauri K L, Holdren G C Jr (1981) Pollutant effects on stone monuments. Environ Sci Technol 15(4):386–390Google Scholar
  24. Haneef SJ, Johnson JB, Dickinson C et al (1992) Effect of dry deposition of NOx and SO2 gaseous pollutants on the degradation of calcareous building stones. Atmos Environ A Gen 26(16):2963–2974CrossRefGoogle Scholar
  25. Kerr A, Rafuse H, Sparkes G et al (2011) Visible/infrared spectroscopy (VIRS) as a research tool in economic geology: background and pilot studies from Newfoundland and Labrador. Curr Res Rep 11(1):145–166Google Scholar
  26. Kruse FA (2012) Mapping surface mineralogy using imaging spectrometry. Geomorphology 137:41–56CrossRefGoogle Scholar
  27. Kubik M (2007) Hyperspectral imaging: a new technique for the non-invasive study of artworkks. In: Creagh D, Bradley D (eds) Physical techniques in the study of art, archeology and cultural heritage, vol 2. Elsevier, Amsterdam, pp 200–259Google Scholar
  28. Lluveras A, Boularand S, Andreotti A et al (2010) Degradation of azurite in mural paintings: distribution of copper carbonate, chlorides and oxalates by SRFTIR. Appl Phys A Mater 99(2):363–375CrossRefGoogle Scholar
  29. Magendran T, Sanjeevi S, Bhattacharya A K et al (2011) Hyperspectral radiometry to estimate the grades of iron ores of Noamundi, India: a preliminary study. In: 31st Asian Association on Remote Sensing 2010, Hanoi, 1–5 November 2010. Curran Associates, New York, pp 1–6Google Scholar
  30. Melani A et al (2010) Hyperspectral data processing activities and applications with SIM-GA. In: Proceedings of the IEEE Gold Remote Sensing Conference, Livorno, 20–30 April 2010Google Scholar
  31. Miliani C, Rosi F, Brunetti BG et al (2010) In situ noninvasive study of artworks: the MOLAB multitechnique approach. ACC Chem Res 43(6):758–738CrossRefGoogle Scholar
  32. Milton EJ (1987) Principles of field spectroscopy. Int J Remote Sens 8(12):1807–1827CrossRefGoogle Scholar
  33. Montecchi A (2013) Development of a methodology for monitoring surfaces of historic buildings using hyperspectral portable instrument (in Italian). Dissertation, University of FlorenceGoogle Scholar
  34. Mugnaini S, Bagnoli A, Bensi P et al (2006) Thirteenth century wall paintings under the Siena Cathedral (Italy). Mineralogical and petrographic study of materials, painting techniques and state of conservation. J Cult Herit 7(3):171–185CrossRefGoogle Scholar
  35. Petrovic A, Khan SD, Thurmond AK (2012) Integrated hyperspectral remote sensing, geochemical and isotopic studies for understanding hydrocarbon-induced rock alterations. Mar Pet Geol 35(1):292–308CrossRefGoogle Scholar
  36. Raimondi V, Cecchi G, Pantani L et al (1998) Fluorescence LiDAR monitoring of historic buildings. Appl Opt 37:1089–1098CrossRefGoogle Scholar
  37. Ramakrishnan D, Bharti R (2015) Hyperspectral remote sensing and geological applications. Curr Sci 108(5):879–891Google Scholar
  38. Ramakrishnan D, Nithya M, Singh KD et al (2013) A field technique for rapid lithological discrimination and ore mineral identification: results from Mamandar polymetal deposit, India. J Earth Syst Sci 122(1):1–14CrossRefGoogle Scholar
  39. Ricci C, Miliani C, Brunetti BG et al (2006) Non-invasive identification of surface materials on marble artifacts with fiber optic mid-FTIR reflectance spectroscopy. Talanta 69:1221–1226CrossRefGoogle Scholar
  40. Rosi F, Daveri A, Miliani C et al (2009) Non-invasive identification of organic materials in wall paintings by fiber optic reflectance infrared spectroscopy: a statistical multivariate approach. Anal Bioanal Chem 395:2097–2106. doi: 10.1007/s00216-009-3108-y CrossRefGoogle Scholar
  41. Sarris A, Papadopoulos N, Agapiou A et al (2013) Integration of geophysical surveys, ground hyperspectral measurements, aerial and satellite imagery for archaeological prospection of prehistoric sites: the case study of Vésztő-Mágor Tell, Hungary. J Archaeol Sci 40:1454–1470CrossRefGoogle Scholar
  42. Serraglini F (2010) Verifica dell’efficacia di tecniche di restauro su marmo con sensori iperspettrali. Dissertation, University of FlorenceGoogle Scholar
  43. Siegesmund S, Weiss T, Vollbrecht A (2002) Natural stone, weathering phenomena, conservation strategies and case studies. Geological Society Special Publications No. 205. The Geological Society, LondonGoogle Scholar
  44. Striegel MF, Bede Guin E et al (2003) Air pollution, coatings, and cultural resources. Prog Org Coat 48:281–288CrossRefGoogle Scholar
  45. Suzuki A (2014) Study for the calibration of the hyperspectral FieldSpec Pro instrument for the characterization of carbonatic stone surfaces affected by saline efflorescences (in Italian). Dissertation, University of FlorenceGoogle Scholar
  46. Tangestani MH, Validabadi K (2014) Mineralogy and geochemistry of alteration induced by hydrocarbon seepage in an evaporite formation; a case study from the Zagros Fold Belt, SW Iran. Appl Geochem 41:189–195CrossRefGoogle Scholar
  47. Tsakalof A, Manoudis P, Karapanagiotis I et al (2007) Assessment of synthetic polymeric coatings for the protection and preservation of stone monuments. J Cult Herit 8:69–72CrossRefGoogle Scholar
  48. Vandenabeele P, Lambert K, Matthys S et al (2005) In situ analysis of mediaeval wall paintings: a challenge for mobile Raman spectroscopy. Anal Bioanal Chem 383:702–712CrossRefGoogle Scholar
  49. Vettori S, Benvenuti M, Camaiti M et al (2008) Assessment of the deterioration status of historical buildings by hyperspectral imaging techniques. In: Tiano P, Pardini C (eds) SMS/08 Congress on in situ monitoring of monumental surfaces. Edifir, Firenze, p 55Google Scholar
  50. Vettori S et al (2012) Portable hyperspectral device as a valuable tool for the detection of protective agents applied on historical buildings. In: Geophysical Research abstracts of EGU general assembly 2012, Wien, 22–27 April 2012, vol 14, p 9459Google Scholar
  51. Wang C (2015) Hyperspectral sensor: a new approach for evaluating the efficacy of laser cleaning in the removal of varnishes and overpaintings. Dissertation, University of BolognaGoogle Scholar
  52. Xinyue G (2013) Numerical elaboration of hyperspectral monitoring of the marble surface of Santa Maria del Fiore Cathedral (in Italian). Dissertation, University of FlorenceGoogle Scholar
  53. Zadeh MH, Tangestani MH, Roldan FV et al (2014) Sub-pixel mineral mapping of a porphyry copper belt using EO-1 Hyperion data. Adv Space Res 53(3):440–451CrossRefGoogle Scholar
  54. Zecchi D (2013) Portable hyperspectral technique for detecting protective treatments on architectural stone materials (in Italian). Dissertation, University of FlorenceGoogle Scholar

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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