Digital Technology and Mechatronic Systems for the Architectural 3D Metric Survey

  • Marco Giorgio Bevilacqua
  • Gabriella Caroti
  • Andrea Piemonte
  • Alessandro Ariel Terranova
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 92)


Over the last decade, we have seen the widespread use of digital survey technologies that have made the three-dimensional (3D) metric survey within reach of all. In the past, lengthy training was needed to use total stations and classical photogrammetry. Today, laser scanning and “new photogrammetry” allow operators with little training to produce 3D models with high spatial density in real time. These systems have therefore made 3D metric survey available to a wide audience of professionals, and have also allowed surveys to be performed with little economic investment in instrumentation. Although this evolution in survey methodologies has certainly brought great benefits, the use of these methods by operators with limited training poses some risk. The proliferation of imprecise processed 3D data, however, constitutes a digital archive of documentation which, by its nature, should be semi-automatically integrated. Issues related to reference systems, scale of representation, accuracy, and related metadata therefore become highly relevant. This paper aims to describe, by means of several case studies, the laser scanner and “new photogrammetry” survey methodologies in light of the aforementioned issues. In addition, the use of “new photogrammetry” in combination with UAV systems will be presented. The integration and miniaturization of positioning systems, attitude measuring systems, and survey instruments (cameras, laser scanners, thermal and multispectral cameras, etc.) allow, by drone flight, the creation of 3D surveys, something that was impossible several years ago without a substantial budget for the use of conventional aircraft.


Architectural survey Laser scanning Structure from motion UAV 


  1. 1.
    Bevilacqua M, Piemonte A, Caroti G, Martínez-Espejo Zaragoza I (2015) An analysis of the evolution of architectural survey by comparison of two surveys of Porta all’Arco (Volterra, Italy): from 1996 to 2014. In: Proceedings of 7th international conference on contemporary problems of architecture and construction, Fabbrica della Conoscenza, vol 58, pp 573–578. ISSN 2464-9678, ISBN 978-88-6542-431-5Google Scholar
  2. 2.
    Bolognesi M, Furini A, Russo V, Pellegrinelli A, Russo P (2014) Accuracy of cultural heritage 3D models by RPAS and terrestrial. In: The international archives of the photogrammetry, remote sensing and spatial information sciences, vol XL-5, ISPRS technical commission V symposium, pp 113–119.
  3. 3.
    Bevilacqua MG, Caroti G, Zaragoza IM-E, Piemonte A (2016) Frescoed vaults: accuracy controlled simplified methodology for planar development of three-dimensional textured models. Remote Sens 8(3), 239.
  4. 4.
    Capriuoli F, Colangelo D, Curto L, Fileri D, Guariglia A, Sansanelli VM, Santarsiero P (2015) La ricostruzione 3D in realtà virtuale del Piano Nobile del Palazzo del Quirinale. Geomedia no 2, pp 26–28. ISSN 1128-8132Google Scholar
  5. 5.
    Caroti G, Franconi A, Piemonte A (2012) Metodologia di elaborazione dati laser scanner per la generazione di modelli utili al calcolo strutturale. In: Proceedings of 16a Conferenza Nazionale ASITA, pp 383–390. ISBN 978-88-903132-7-1Google Scholar
  6. 6.
    Caroti G, Martínez-Espejo Zaragoza I, Piemonte A (2015) Range and image based modelling: a way for frescoed vault texturing optimization. Int Arch Photogramm Remote Sens Spat Inf Sci—ISPRS Archives 40(5W4):285–290.
  7. 7.
    Caroti G, Martínez-Espejo Zaragoza I, Piemonte A (2015) Accuracy assessment in structure from motion 3D reconstruction from UAV-born images: the influence of the data processing methods. Int Arch Photogramm Remote Sens Spat Inf Sci—ISPRS Archives 40(1W4):103–109.
  8. 8.
    Chiabrando F, Donadio E, Rinaudo F (2015) SfM for orthophoto generation: a winning approach for cultural heritage knowledge. Int Arch Photogramm Remote Sens Spat Inf Sci—ISPRS Archives XL-5/W7:91–98.
  9. 9.
    Cignoni P, Montani C, Scopigno R (1998) A comparison of mesh simplification algorithms. Comput Graph 22(1):37–54. ISSN 0097-8493Google Scholar
  10. 10.
    Colomina I, Molina P (2014) Unmanned aerial systems for photogrammetry and remote sensing: a review. ISPRS J Photogramm Remote Sens 92:79–97.
  11. 11.
    Eisenbeiss H (2009) UAV photogrammetry. Dissertation ETH No.18515, Institute of Geodesy and Photogrammetry, ETH Zurich, Switzerland, Mitteilungen 105Google Scholar
  12. 12.
    Gonizzi Barsanti S, Caruso G, Micoli LL, Covarrubias Rodriguez M, Guidi G (2015) 3D visualization of cultural heritage artefacts with virtual reality devices. Int Arch Photogramm Remote Sens Spat Inf Sci—ISPRS Archives XL-5/W7: 165–172.
  13. 13.
    Guidi G, Remondino F (2012) 3D modelling from real data. In: Modeling and simulation in engineering, pp 69–102. ISBN 978–953-51-0012-6. https//
  14. 14.
    Hoppe H (1996) Progressive meshes. In: Proceedings of SIGGRAPH96, pp 99–108. ISBN 0-201-94800-1Google Scholar
  15. 15.
    Kraus K (1993) Photogramm, vol.1, p 397. ISBN: 3427786846Google Scholar
  16. 16.
    Lowe D (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vision 60:91–110CrossRefGoogle Scholar
  17. 17.
    Nex F, Remondino F (2014) UAV for 3D mapping applications: a review. Appl Geomat 6:1–15.
  18. 18.
    Remondino F, Spera MG, Nocerino E, Menna F, Nex F (2014) State of the art in high density image matching. The Photogramm Rec 29(146):144–166.
  19. 19.
    Robleda PG, Caroti G, Martínez-Espejo ZI, Piemonte A (2016) Computational vision in UV-Mapping of textured meshes coming from photogrammetric recovery: unwrapping frescoed vaults. Int Arch Photogramm Remote Sens Spat Inf Sci—ISPRS Archives 41:391–398Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Marco Giorgio Bevilacqua
    • 1
  • Gabriella Caroti
    • 2
  • Andrea Piemonte
    • 2
  • Alessandro Ariel Terranova
    • 1
  1. 1.DESTEC, University of PisaPisaItaly
  2. 2.DICI, University of PisaPisaItaly

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