, Volume 22, Issue 2, pp 463–477 | Cite as

Close range photogrammetry with tablet technology in post-earthquake scenario: Sant’Agostino church in Amatrice

  • Paolo Dabove
  • Vincenzo Di Pietra
  • Andrea Maria Lingua


In recent years, numerous natural disaster affected the Italian territory, growing the demand of secure on-field procedures able to accomplish the task of reconnaissance, inspection and survey of instable infrastructure and cultural heritage. During the early-impact there are numerous first response figures, like firefighters, civil protection, geotechnical inspectors and surveyors, that have to operate nearby damaged structure putting at risk their lives in case of possible collapses. Most of these operators work in heavy conditions, so they need tools and procedures that allow them to rush into decisions. These procedures must be rapid, easy to use and must allow the possibility to conduct the task with a certain distance of the instable or not easily accessible structures. This paper deals with the use of tablet devices for rapid close range photogrammetry in post-earthquake scenario, following the close range photogrammetry approach. Starting from images acquired by tablets during speditive surveys, the authors show how is possible to reconstruct the environment starting from data acquired by low cost devices. The case-study considered in this work is the Sant’Agostino Church in Amatrice (Italy), a cultural heritage highly damaged by the 6.0 magnitude earthquake occurred on 24 August 2016 in the central part of Italy.


Low-cost sensors Close range photogrammetry Rapid mapping Tablet Earthquake Cultural heritage 



The Authors want to acknowledge all members (students and professors) of the Direct Team and Paolo Maschio for his help and support. Moreover, we appreciate the insightful and constructive comments and suggestions by the anonymous reviewers that helped improve the quality of the manuscript.

Compliance with ethical standards

Conflicts of interest

The authors declare no conflict of interest.


  1. 1.
    Gomez C, Purdie H (2016) UAV-based photogrammetry and Geocomputing for hazards and disaster risk monitoring–a review. Geoenvironmental Disasters 3(1):23. CrossRefGoogle Scholar
  2. 2.
    Schöps T, Sattler T, Häne C, Pollefeys M, 3D modeling on the go: Interactive 3d reconstruction of large-scale scenes on mobile devices. 3D Vision (3DV), 2015 International Conference on IEEE, pp 291–299Google Scholar
  3. 3.
    Fritsch D, Syll M, Photogrammetric 3D reconstruction using mobile imaging. SPIE/IS&T Electronic Imaging, International Society for Optics and Photonics, 94110C-94110CGoogle Scholar
  4. 4.
    Klontz JC, Jain AK, A case study of automated face recognition: the Boston marathon bombings suspects. Computer 46(11):91–94Google Scholar
  5. 5.
    Schurr N, Marecki J, Tambe M, Scerri P, Kasinadhuni N, Lewis JP (2005) The future of disaster response: humans working with multiagent teams using DEFACTO. Proc. AAAI Symp., AI Technol. Homeland Secur. 9–16Google Scholar
  6. 6.
    Kumar S, Rathy RK, Pandey D (2009) Design of an ad-hoc network model for disaster recovery scenario using various routing protocols. Proc. ACM Int. Conf. Adv. Comput.,Commun.Control (ICAC3), p 100–105Google Scholar
  7. 7.
    Aicardi I, Lingua A, Piras M (2014) "Evaluation of mass market devices for the documentation of the cultural heritage." The international archives of photogrammetry. Remote Sensing and Spatial Information Sciences 40(5):17Google Scholar
  8. 8.
    Dabove P, Ghinamo G, Lingua AM (2015) Inertial sensors for smartphones navigation. SpringerPlus 4(1):834. CrossRefGoogle Scholar
  9. 9.
    Dabove P, Manzino AM (2016) Accurate real-time GNSS positioning assisted by tablets: an innovative method for positioning and mapping. GEAM Geoingegneria Ambientale E Mineraria 148(2):17–22Google Scholar
  10. 10.
    Peipe J, Stephani M (2003) Performance evaluation of a 5 megapixel digital metric camera for use in architectural photogrammetry. International Archives of Photogrammetry Remote Sensing And Spatial Information Sciences 34(5/W12):259–261Google Scholar
  11. 11.
    El-Hakim SF, Beraldin JA, Picard M, Godin G (2004) Detailed 3D reconstruction of large-scale heritage sites with integrated techniques. IEEE Comput Graph Appl 24(3):21–29. CrossRefGoogle Scholar
  12. 12.
    Pavlidis G, Koutsoudis A, Arnaoutoglou F, Tsioukas V, Chamzas C (2007) Methods for 3D digitization of cultural heritage. J Cult Herit 8(1):93–98. CrossRefGoogle Scholar
  13. 13.
    Bruno F, Bruno S, De Sensi G, Luchi ML, Mancuso S, Muzzupappa M (2010) From 3D reconstruction to virtual reality: a complete methodology for digital archaeological exhibition. J Cult Herit 11(1):42–49. CrossRefGoogle Scholar
  14. 14.
    Sequeira V, Ng K, Wolfart E, Gonçalves JG, Hogg D (1999) Automated reconstruction of 3D models from real environments. ISPRS J Photogramm Remote Sens 54(1):1–22. CrossRefGoogle Scholar
  15. 15.
    Niem W, Wingbermuhle J (1997). Automatic reconstruction of 3D objects using a mobile monoscopic camera. In: 3-D digital imaging and modeling, 1997. Proceedings., international conference on recent advances in IEEE, pp 173–180Google Scholar
  16. 16.
    Piras M, Lingua A, Dabove P, Aicardi I (2014) Indoor navigation using smartphone technology: a future challenge or an actual possibility? In: Position, Location and Navigation Symposium-PLANS 2014, 2014 IEEE/ION. IEEE, pp 1343-1352Google Scholar
  17. 17.
    Tang R, Fritsch D (2013) Correlation analysis of camera self-calibration in close range photogrammetry. Photogramm Rec 28(141):86–95. CrossRefGoogle Scholar
  18. 18.
    Clarke TA, Fryer JG (1998) The development of camera calibration methods and models. Photogramm Rec 16(91):51–66. CrossRefGoogle Scholar
  19. 19.
    Luhmann T, Robson S, Kyle S, Harley I (2007) Close range photogrammetry. Wiley, HobokenGoogle Scholar
  20. 20.
    AgiSoft PhotoScan Professional (Version 1.4.0) (Software) (2017) Retrieved from
  21. 21.
    Deseilligny, M Pierrot, Clery I (2011) Apero, an open source bundle adjusment software for automatic calibration and orientation of set of images. Proceedings of the ISPRS Symposium, 3DARCH11. Vol. 269277Google Scholar
  22. 22.
    CloudCompare (version 2.9) [GPL software] (2017) Retrieved from

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Politecnico di Torino, Geomatics Group, Department of Environment, Land, and Infrastructure EngineeringTurinItaly

Personalised recommendations