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Open image in new windowSensor Data Integration for Landslide Monitoring—the LEMONADE Concept

  • Romy Schlögel
  • Benni Thiebes
  • Isabella Toschi
  • Thomas Zieher
  • Mehdi Darvishi
  • Christian Kofler
Conference paper

Abstract

The project LEMONADE (LandslidE MOnitoriNg And Data intEgration) aims to combine different techniques investigating their benefits and drawbacks. We present the different techniques used to monitor the active Corvara landslide located in the Italian Dolomites. Satellite remote sensing products allow covering the whole landslide providing 1D displacement measurements while proximal and terrestrial techniques can provide 3D information. In this paper, preliminary results considering each individual method applied are discussed and a first estimation of landslide displacements for the period considered is given.

Keywords

Landslide monitoring Remote sensing 3D imaging techniques Data integration 

Notes

Acknowledgements

This work is financed by the Europaregion Euregio Science Fund first Call for Interregional Project Network (IPN). UAV flights were done by A. Mejia Aguilar and E. Tomelleri (EURAC, Bolzano, Italy). We also thank M. Rutzinger and J. Peiffer (IGF-ÖAW, Innsbruck, Austria) for their help in TLS data acquisition and F. Remondino (FBK, Trento, Italy) as project coordinator. We also acknowledge the geological services of the Autonomous provinces of Trento and Bolzano as well as the Department of Geoinformation of the Federal State of Tyrol.

References

  1. Aicardi I, Dabove P, Lingua AM, Piras M (2012) Integration between TLS and UAV photogrammetry techniques for forestry applications. iForest 009:1–7Google Scholar
  2. Berardino P, Fornaro G, Lanari R, Member S, Sansosti E (2002) A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Trans Geosci Remote Sens 40(11):2375–2383CrossRefGoogle Scholar
  3. Borgatti L, Ravazzi C, Donegana M, Corsini A, Marchetti M, Soldati M (2007) A lacustrine record of early Holocene watershed events and vegetation history, Corvara in Badia, Dolomites (Italy). J Quat Sci 22(2):173–189CrossRefGoogle Scholar
  4. Corsini A, Pasuto A, Soldati M, Zannoni A (2005) Field monitoring of the Corvara landslide (Dolomites, Italy) and its relevance for hazard assessment. Geomorphology 66(1–4):149–165CrossRefGoogle Scholar
  5. EUREGIO partners (2016) LEMONADE—LandslidE MOnitoriNg And Data intEgration project. URL: http://lemonade.mountainresearch.at/. Last accessed 17 Oct 2016
  6. Lichti DD, Skaloud J (2010) Registration and calibration. In: Vosselman G, Maas HG (eds) Airborne and terrestrial laser scanning. Whittles Publishing, Caithness, pp 83–133Google Scholar
  7. Mulas M, Petitta M, Corsini A, Schneiderbauer S, Mair FV, Lasio C (2015) Long-term monitoring of a deep-seated, slow-moving landslide by mean of C-band and X-band advanced interferometric products: the Corvara in Badia case study (Dolomites, Italy). ISPRS—International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-7/W3, pp 827–829Google Scholar
  8. Niethammer U, Rothmund S, James MR, Travelletti J, Joswig M (2010) UAV-based remote sensing of landslides. Int Arch Photogram Remote Sens Spat Inf Sci 38(5):496–501Google Scholar
  9. Prokop A, Panholzer H (2009) Assessing the capability of terrestrial laser scanning for monitoring slow moving landslides. Natural Haz Earth Syst Sci 9(6):1921–1928CrossRefGoogle Scholar
  10. Remondino F, Del Pizzo S, Kersten TP, Troisi S (2012) Low-cost and open-source solutions for automated image orientation—a critical overview. In: Ioannides M et al. (eds) Euro-mediterranean conference. Springer, Berlin, pp 40–54Google Scholar
  11. Remondino F, Spera MG, Nocerino E, Menna F, Nex F (2014) State of the art in high density image matching. Photogram Rec 29(146):144–166CrossRefGoogle Scholar
  12. SARMAP (2012) SARScape: Technical description. SwitzerlandGoogle Scholar
  13. Scaioni M, Longoni L, Melillo VMP (2014) Remote Sensing for Landslide Investigations: an overview of recent achievements and perspectives. Remote Sens 6:1–26CrossRefGoogle Scholar
  14. Schädler W, Borgatti L, Corsini A, Meier J, Ronchetti F, Schanz T (2015) Geomechanical assessment of the Corvara earthflow through numerical modelling and inverse analysis. Landslides 12(3):495–510CrossRefGoogle Scholar
  15. Skarlatos D, Kiparissi S (2012) Comparaison of laser scanning, photogrammetry and SFM-MVS pipeline applied in structures and artificial surfaces. ISPRS Ann Photogram Remote Sens Spat Inform Sci 3:299–304CrossRefGoogle Scholar
  16. Stumpf A, Malet JP, Allemand P, Pierrot-Deseilligny M, Skupinski G (2015) Ground-based multi-view photogrammetry for the monitoring of landslide deformation and erosion. Geomorphology 231:130–145CrossRefGoogle Scholar
  17. Thiebes B, Tomelleri E, Aguilar A, Rabanser M, Schlögel R, Mulas M, Corsini A (2016) Assessment of the 2006–2015 Corvara landslide evolution using a UAV-derived DSM and orthophoto. In: Aversa S, Cascini L, Picarelli L, Scavia C (eds) Landslides and engineered slopes. Experience, theory and practice. CRC Press, Naples, Italy, pp 1897–1902Google Scholar
  18. Wasowski J, Bovenga F (2014) Investigating landslides and unstable slopes with satellite multi temporal interferometry: current issues and future perspectives. Eng Geol 174:103–138CrossRefGoogle Scholar
  19. Zucca F, Remondino F, Zizioli D, Meisina C (2009) Slopes survey and analysis using photogrammetrically derived digital surface models. In: Proceedings of RSPSoc 2009 annual conference, 8–11 September, Leicester, UK, pp 494–500Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Romy Schlögel
    • 1
  • Benni Thiebes
    • 1
  • Isabella Toschi
    • 2
  • Thomas Zieher
    • 3
  • Mehdi Darvishi
    • 1
  • Christian Kofler
    • 1
  1. 1.European Academy of Bolzano/BozenInstitute for Applied Remote SensingBolzanoItaly
  2. 2.3D Optical Metrology Unit, Bruno Kessler FoundationPovo-TrentoItaly
  3. 3.Institute of Interdisciplinary Mountain ResearchAustrian Academy of SciencesInnsbruckAustria

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