Skip to main content
SpringerLink
Log in

A Fixed Terrestrial Photogrammetric System for Landslide Monitoring

  • Chapter
  • First Online:
Modern Technologies for Landslide Monitoring and Prediction

Part of the book series: Springer Natural Hazards ((SPRINGERNAT))

Abstract

Though landslide alert is based on monitoring systems capable of high frequency, highly accurate, continuous-operation photogrammetry has been used since long time to periodically control the evolution of landslides. In this chapter, a fixed terrestrial stereo photogrammetric system is presented. It has been developed to monitor landslides and, in general, changes in digital surface model (DSM) of the scene framed by the cameras. The system is made of two single-lens reflex (SLR) cameras, each contained in a sealed box and controlled by a computer that periodically shoots an image and sends it to a host computer. Once an image pair is received, the DSM of the scene is generated by digital image correlation on the host computer and made available for archiving or analysis. The system has been installed and is being tested on the Mont de la Saxe landslide, where several monitoring systems are active and provide reference data. Instability of the camera attitude has been noticed and corrected with an automated procedure by image resampling. First comparisons with interferometric synthetic aperture radar data show a good agreement of the displacements over time.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Abellán, A., Oppikofer, T., Jaboyedoff, M., Rosser, N. J., Lim, M., & Lato, M. J. (2014). Terrestrial laser scanning of rock slope instabilities. Earth Surface Processes and Landforms, 39, 80–97.

    Article  Google Scholar 

  • Angeli, M., Pasuto, A., & Silvano, S. (2000). A critical review of landslide monitoring experiences. Engineering Geology, 55, 133–147.

    Article  Google Scholar 

  • Aspert, N., Santa-Cruz, D., & Ebrahimi, T. (2002). MESH: Measuring errors between surfaces using the Hausdorff distance. In IEEE International Conference in Multimedia and Expo (ICME) 2002 (Vol. 1, pp. 705–708), Lausanne, Switzerland, August 26–29, 2002.

    Google Scholar 

  • Barazzetti, L., Forlani, G., Remondino, F., Roncella, R., & Scaioni, M. (2011). Experiences and achievements in automated image sequence orientation for close-range photogrammetric projects. In Proceedings of International Conference ‘Videometrics, Range Imaging, and Applications XI’, Proceedings of SPIE (Vol. 8085, p. 13), Munich, Germany, May 23–26, 2011. Paper No. 80850F. doi:10.1117/12.890116.

  • Barazzetti, L., Previtali, M., & Scaioni, M. (2013). Stitching and processing gnomonic projections for close-range photogrammetry. Photogrammetric Engineering and Remote Sensing, 79(6), 573–582.

    Article  Google Scholar 

  • Barbarella, M., & Fiani, M. (2013). Monitoring of large landslides by terrestrial laser scanning techniques: Field data collection and processing. European Journal of Remote Sensing, 46, 126–151.

    Article  Google Scholar 

  • Bay, H., Ess, A., Tuytelaars, T., & Van Gool, L. (2008). Speeded-up robust features (SURF). Computer Vision and Image Understanding, 110(3), 346–359.

    Article  Google Scholar 

  • Bertacchini, E., Capra, A., Castagnetti, C., & Corsini, A. (2011). Atmospheric corrections for topographic monitoring systems in landslides. In Proceedings FIG Working Week 2011 ‘Bridging the Gap between Cultures’ (p. 15), Marrakech, Morocco, May 18–22, 2011.

    Google Scholar 

  • Birgisson, B., Montepara, A., Romeo, E., Roncella, R., Roque, R., & Tebaldi, G. (2009). An optical strain measurement system for asphalt mixtures. Materials and Structures, 42(4), 427–441.

    Article  Google Scholar 

  • Bitelli, G., Dubbini, M., & Zanutta, A. (2004). Terrestrial laser scanning and digital photogrammetry techniques to monitor landslide bodies. International Archives of The Photogrammetry, Remote Sensing and Spatial Information Sciences, 38(7B), 246–251.

    Google Scholar 

  • Brown, D. (1971). Close-range camera calibration. Photogrammetric Engineering, 37(8), 855–866.

    Google Scholar 

  • Cardenal, J., Mata, E., Perez-Garcia, J., Delgado, J., Andez, M., Gonzales, A., et al. (2008). Close range digital photogrammetry techniques applied to landslide monitoring. International Archives of The Photogrammetry, Remote Sensing and Spatial Information Sciences, 37(B8), 235–240.

    Google Scholar 

  • Casson, B., Baratoux, D., Delacourt, C., & Allemand, P. (2003). La Clapière landslide motion observed from aerial differential high resolution DEM. Engineering Geology, 68, 123–139.

    Article  Google Scholar 

  • Cignoni, P., Rocchini, C., & Scopigno, R. (1998). Metro: Measuring error on simplified surfaces. In Proceedings Computer Graphics Forum (Vol. 17, No.2, pp. 167–174) June 1198.

    Google Scholar 

  • Corominas, J., Moya, A., Lloret, J., Gili, A., Angeli, M. G., Pasuto, A., et al. (2000). Measurement of landslide displacements using a wire extensometer. Engineering Geology, 55, 149–166.

    Article  Google Scholar 

  • Crosetto, M., Monserrat, O., Luzi, G., Cuevas-Gonzáles, M., & Devanthéry, N. (2014). Discontinuous GBSAR deformation monitoring. ISPRS Journal of Photogrammetry and Remote Sensing, 93, 136–141.

    Article  Google Scholar 

  • Crosta, G., et al. (2012). Chasing a complete understanding of a rapid moving rock slide: The La Saxe landslide. In Proceedings of EGU General Assembly 2012. Vienna, Austria.

    Google Scholar 

  • Feng, T., Liu, X., Scaioni, M., Lin, X., & Li, R. (2012). Real-time landslide monitoring using close-range stereo image sequences analysis. In Proceedings of 2012 International Conference on Systems and Informatics (ICSAI 2012) (pp. 249–253), Yantai, P.R. China, May 19–21, 2012.

    Google Scholar 

  • Fischler, M., & Bolles, R. (1981). Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM, 24(6), 381–395.

    Article  Google Scholar 

  • Forlani, G., & Pinto, L. (1994). Experiences of combined block adjustment with GPS data. International Archives of Photogrammetry and Remote Sensing, 30(3/1), 219–226.

    Google Scholar 

  • Forlani, G., & Pinto, L. (2007) GPS-assisted adjustment of terrestrial blocks. In Proceedings of 5th International Symposium on ‘Mobile Mapping Technology (MMT’07)’ (pp. 1–7). Padova, Italy.

    Google Scholar 

  • Fraser, C. S. (1996). Network design. In K. B. Atkinson (Ed.), Close range photogrammetry and machine vision (pp. 256–281). Dunbeath, Caithness, Scotland, UK: Whittles Publishing.

    Google Scholar 

  • Grün, A. (1985). Adaptative least squares correlation: a powerful image matching technique. South African Journal of Photogrammetry, Remote Sensing and Cartography, 14, 175–187.

    Google Scholar 

  • Hartley, R., & Zissermann, A. (2006) Multiple view geometry in computer vision. Cambridge: Cambridge University Press.

    Google Scholar 

  • Intrieri, E., Gigli, G., Casagli, N., & Nadim, F. (2013). Landslide early warning system: Toolbox and general concepts. Natural Hazards and Earth System Science, 13, 85–90.

    Article  Google Scholar 

  • Jaboyedoff, M., Oppikofer, T., Abellán, A., Derron, M. H., Loye, A., Metzger, R., et al. (2012). Use of LIDAR in landslide investigations: A review. Natural Hazards, 61, 1–24.

    Article  Google Scholar 

  • Jacobsen, K. (2004). Direct integrated sensor orientation-pros and cons. International Archives of the Photogrammetry, Remote sensing and Spatial Information Sciences, 35(B3), 829–835.

    Google Scholar 

  • Kraus, K. (2008). Photogrammetry—geometry from images and laser scans. Berlin, Germany: Walter de Gruyter.

    Google Scholar 

  • Luhmann, T., Robson, S., Kyle, S., & Böhm, J. (2013). Close range photogrammetry: 3D imaging techniques (p. 702). Germany: Walter De Gruyter Inc.

    Google Scholar 

  • Monserrat, A., & Crosetto, M. (2008). Deformation measurement using terrestrial laser scanning data and least squares 3D surface matching. ISPRS Journal of Photogrammetry and Remote Sensing, 63, 142–154.

    Article  Google Scholar 

  • Monserrat, O., Crosetto, M., & Luzi, G. (2014). A review of ground-based SAR interferometry for deformation measurement. ISPRS Journal of Photogrammetry and Remote Sensing, 93, 40–48.

    Article  Google Scholar 

  • Mora, P., Baldi, P., Casula, G., Fabris, M., Ghirotti, M., Mazzini, E., et al. (2003). Global Positioning Systems and digital photogrammetry for the monitoring of mass movements: Application to the Ca’ di Malta landslide (northern Apennines, Italy). Engineering Geology, 68, 103–121.

    Article  Google Scholar 

  • Motta, M., Gabrieli, F., Corsini, A., Manzi, V., Ronchetti, F., & Cola, S. (2013). Landslide displacement monitoring from multi-temporal terrestrial digital images: Case of the Valoria landslide site. In C. Margottini, P. Canuti & K. Sassa (Eds.), Landslide science and practice (Vol. 2, pp. 73–78). Heidelberg, Berlin: Springer.

    Google Scholar 

  • Pollefeys, M., Koch, R., & Van Gool, L. (1999). A simple and efficient rectification method for general motion. In Proceedings of ‘7th IEEE International Conference on Computer Vision (ICCV’99)’ (Vol. 1, pp. 496–501).

    Google Scholar 

  • Qiao, G., Lu, P., Scaioni, M., Xu, S., Tong, X., Feng, T., et al. (2013). Landslide investigation with remote sensing and sensor network: From susceptibility mapping and scaled-down simulation towards in situ sensor network design. Remote Sensing, 5(9), 4319–4346.

    Article  Google Scholar 

  • Raguse, K., & Heipke, C. (2009). Synchronization of image sequences—a photogrammetric method. Photogrammetric Engineering and Remote Sensing, 75(4), 535–546.

    Article  Google Scholar 

  • Scaioni, M., Roncella, R., & Alba, M. (2013). Change detection analysis in point clouds: Application to rock face monitoring. Photogrammetric Engineering and Remote Sensing, 78(5), 441–455.

    Article  Google Scholar 

  • Scaioni, M., Longoni, L., Melillo, V., & Papini, M. (2014a). Remote sensing for landslide investigations: An overview on recent achievements and perspectives. Remote Sensing, 6(10), 9600–9652. doi:10.3390/rs6109600.

  • Scaioni, M., Feng, T., Lu, P., Qiao, G., Tong, X., Li, R., et al. (2014b). Close-range photogrammetric techniques for deformation measurement: Applications to landslides. In M. Scaioni (Ed.), Modern technologies for landslide investigation and prediction (pp. 13–41). Berlin Heidelberg: Springer.

    Google Scholar 

  • Szeliski, R. (2010). Computer vision: Algorithms and applications. Berlin Heidelberg: Springer.

    Google Scholar 

  • Travelletti, J., Delacourt, C., Allemand, P., Malet, J. P., Schmittbuhl, J., Toussaint., R. et al. (2012). Correlation of multi-temporal ground-based optical images for landslide monitoring: Application, potential and limitations. ISPRS Journal of Photogrammetry and Remote Sensing, 70, 39–55.

    Article  Google Scholar 

  • Wallis, K. F. (1974). Seasonal adjustment and relations between variables. Journal of the American Statistical Association, 69(345), 18–31.

    Article  Google Scholar 

  • Wasowski, J., & Bovenga, F. (2014). Investigating landslides and unstable slopes with satellite multi temporal interferometry: Current issues and future perspectives. Engineering Geology, 174, 103–138.

    Article  Google Scholar 

Download references

Acknowledgments

This research was supported by the Italian Ministry of University and Research within the project FIRB—Futuro in Ricerca 2010 (No. RBFR10NM3Z).

Author information

Authors and Affiliations

  1. Department of Civil, Environmental, Land Management Engineering and Architecture, University of Parma, via Parco Area delle Scienze, 181/a, 43124, Parma, Italy

    Riccardo Roncella & Gianfranco Forlani

Authors
  1. Riccardo Roncella
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gianfranco Forlani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Riccardo Roncella .

Editor information

Editors and Affiliations

  1. College of Surveying & Geo-Informatics, Department of Architecture, Built Environment and Construction Engineering,, Tongji University, Shanghai, Politecnico di Milano, Italy, China

    Marco Scaioni

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Roncella, R., Forlani, G. (2015). A Fixed Terrestrial Photogrammetric System for Landslide Monitoring. In: Scaioni, M. (eds) Modern Technologies for Landslide Monitoring and Prediction. Springer Natural Hazards. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45931-7_3

Download citation

Publish with us

Policies and ethics

Search

Navigation