Integration of Remote Sensing Techniques in Different Stages of Landslide Response

  • Paolo Canuti
  • Nicola Casagli
  • Filippo Catani
  • Giacomo Falorni
  • Paolo Farina


Recent advances in remote sensing techniques have yielded numerous new applications which provide benefits for all stages of landslide management. This paper describes how the data produced from different types of sensors and platforms have been used to estimate, model and mitigate landslide risk in sites in Italy and in other parts of the world. EO data have been utilized to update landslide inventories, with the identification of new landslides and the ratification or modification of landslide boundaries and states of activity, and to improve landslide hazard and risk assessment procedures at regional scales. Radar data provided a global topographic dataset that was used to model lahar inundation hazard while an example of the millimetric resolutions attainable from repeat-pass satellite radar data, with its beneficial implications for landslide monitoring, is also illustrated. Ground-based systems are shown to be innovative early warning systems for slow-moving landslides while coupled techniques involving both optical and radar images can provide support for the management of emergencies. The illustration of these case histories demonstrates the increasing importance of remote sensing in all facets of landslide management, with significant advantages for both policy makers and society.


Remote sensing landslides landslide risk landslide management 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Antonello G, Casagli N, Farina P, Leva D, Nico G, Sieber AJ, Tarchi D (2004) Ground-based SAR interferometry for monitoring mass movements. Landslides 1(1):21–28CrossRefGoogle Scholar
  2. Bamler R (1999) The SRTM Mission: A World-wide 30 m Resolution DEM from SAR interferometry in 11 days. Photogrammetric Week 1999:145–154Google Scholar
  3. Berardino P, Costantini M, Franceschetti G, Iodice A, Pietranera L, Rizzo V (2003) Use of differential SAR interferometry in monitorino and modelling large slope instability at Maratea (Basilicata, Italy). Eng Geol 68(1–2):31–51CrossRefGoogle Scholar
  4. Bonham-Carter GF (1994) Geographic information systems for geoscientists: modeling with GIS. Pergamon, Ottawa, 198 pGoogle Scholar
  5. Casagli N, Guerri L, Righini G, Ferretti A, Colombo D, Prati C (2005) Integrated use of PS and very high resolution optical images for supporting landslide risk management. In: URSI, Commission F (ed) Symposium on Microwave Remote Sensing of the Earth, Oceans, Ice and Athmosphere, 20–21 April 2005, Ispra, ItalyGoogle Scholar
  6. Catani F, Casagli N, Ermini L, Righini G, Menduni G (2005a) Landslide hazard and risk mapping at catchment scale in the Arno River Basin. Landslides 2(4):329CrossRefGoogle Scholar
  7. Catani F, Farina P, Moretti S, Nico G, Strozzi T (2005b) On the application of SAR interferometry to geomorphological studies: estimation of landform attributes and mass movements. Geomorphology 66:119–131CrossRefGoogle Scholar
  8. Chung CF, Fabbri AG, van Western CJ (1995) Multivariate regression analysis for landslide hazard zonation. In: Carrara A, Guzzetti F (eds) Geographical information system in assessing natural hazards. Kluwer, Dordrecht, pp 107–142Google Scholar
  9. Colombo D, Farina P, Gontier E, Fumagalli A, Moretti S (2003) Integration of Permanent Scatterers analysis and high resolution optical images within landslide risk analysis. In: Proceedings of FRINGE 2003 Workshop, Advances in SAR interferometry from ERS and ENVISAT missions, ESA-ESRIN, Frascati, ItalyGoogle Scholar
  10. Corsina A, Farina P, Antonello G, Barbieri M., Casagli N, Coren F, Guerri L, Ronchetti F, Sterzai P, Tarchi D (2006) Space-borne and ground-based SAR interferometry as tools for landslide hazard management in civil protection. Int J Rem Sens 27(12):2351–2369CrossRefGoogle Scholar
  11. Crozier MJ (1984) Field assessment of slope instability. In: Brundsen D, Prior D (eds) Slope instability. John Wiley & Sons, Chichester, pp 103–140Google Scholar
  12. Duren R, Wong E, Breckenridge B, Shaffer S, Duncan C, Tubbs E, Salomon P (1998) Metrology, attitude, and orbit determination for spaceborne interferometric synthetic Aperture Radar, in SPIE AeroSense Conference on Acquisition, Tracking and Pointing XII, Orlando, Florida, pp 51–60Google Scholar
  13. Ermini L, Catani F, Casagli N (2005) Artificial neural networks applied to landslide susceptibility assessment. Geomorphology 66:327–343CrossRefGoogle Scholar
  14. Falorni G, Teles V, Vivoni ER, Bras RL, Amaratunga K (2005) Analysis and characterization of the vertical accuracy of digital elevation models from the Shuttle Radar Topography Mission. J Geophys Res-Earth Surface 110(F2)Google Scholar
  15. Farina P, Colombo D, Fumagalli A, Marks F, Moretti S (2006) Remote Sensing techniques for landslide risk analysis: outcomes from the ESA-SLAM project. Eng Geol 88:200–217CrossRefGoogle Scholar
  16. Ferretti A, Prati C, Rocca F (2001) Permanent scatterers in SAR interferometry. IEEE T Geosci Remote 39(1):8CrossRefGoogle Scholar
  17. Fukuzono T (1985) A new method for predicting the failure time of a slope. In: Proceedings of IVth International Conference and Field Workshop on Landslides, Tokyo, 23–31 August, Japan Landslide Society, 1, pp 145–150Google Scholar
  18. Hall O, Falorni G, Bras RL (2005) Characterization and quantification of data voids in Shuttle Radar Topography Mission data. IEEE Geosci Remote Lett 2(2):177–181CrossRefGoogle Scholar
  19. Kretsch JL (2000) Shuttle radar topography mission overview. Applied imagery pattern recognition workshop, Washington, D.C., IEEEGoogle Scholar
  20. Lagmay AMF, Valdivia W (2006) Regional stress influence on the opening direction of crater amphitheaters in Southeast Asian volcanoes. J Volcanol Geotherm Res 158(1–2):139CrossRefGoogle Scholar
  21. Mouginis-Mark PJ, Rowland SK, Garbeil H, Amelung F (2001) Topographic change on volcanoes from SRTM and other interferometric radars. 757 pGoogle Scholar
  22. Soeters R, Van Westen CJ (1996) Slope instability recognition, analysis and zonation. Turner AK, Schuster RL (eds) Landslides: investigation an mitigation. Sp. Rep. 247, Transportation Research Board, National research Council, National Academy Press, Washington, DC, pp 129–177Google Scholar
  23. Strozzi T, Farina P, Corsini A, Ambrosi C, Thuring M, Zilger J, Wiesmann A, Wegmüller U, Werner C (2005) Survey and monitoring of landslide displacements by means of L-band satellite SAR interferometry. Landslides. Journal of International Consortium on Landslides 2(3):193–201Google Scholar
  24. Tarchi D, Casagli N, Fanti R, Leva D, Luzi G, Pasuto A, Pieraccini M, Silvano S (2003a) Landslide monitoring by using ground-based SAR interferometry: an example of application to the Tessina landslide in Italy. Eng Geol 68:15–30CrossRefGoogle Scholar
  25. Tarchi D, Casagli N, Leva D, Moretti S, Sieber AJ (2003b) Monitoring landslide displacements by using ground-based SAR interferometry: application to the Ruinon landslide in the Italian Alps. J Geophys Res 108:2387–2401CrossRefGoogle Scholar
  26. van Zyl JJ (2001) The Shuttle Radar Topography Mission (SRTM): a breakthrough in remote sensing of topography. Acta Astronautica 48(5–12):559–565Google Scholar
  27. Varnes DJ, IAEG Commission on Landslides (1984) Landslide hazard zonation-a review of principles and practice. UNESCO, Paris, p 63Google Scholar
  28. Wieczorek GF (1984) Preparing a detailed landslide-inventory map for hazard evaluation and reduction. IAEG Bull 21(3):337–342Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Paolo Canuti
    • 1
  • Nicola Casagli
    • 1
  • Filippo Catani
    • 1
  • Giacomo Falorni
    • 1
  • Paolo Farina
    • 1
  1. 1.Department of Earth SciencesUniversity of FirenzeFirenzeItaly

Personalised recommendations