TXT-tool 4.039-3.2: How to Assess Landslide Activity and Intensity with Persistent Scatterer Interferometry (PSI): The PSI-Based Matrix Approach

  • Francesca Cigna
  • Silvia Bianchini
  • Nicola Casagli


This paper provides a step-by-step analysis and discussion of the ‘PSI-based matrix approach’, a methodology that exploits ground deformation velocities derived through Persistent Scatterer Interferometry (PSI) for the assessment of the state of activity and intensity of extremely to very slow landslides. Two matrices based on historical and recent PSI data are designed respectively for landslides already mapped in preexisting inventories and for newly identified phenomena. A unique intensity scale is proposed applicable to both cases. An example application in the 14 km2 area of Verbicaro in Northern Calabria (Italy) is presented. For this sample site, PSI data derived from SAR (Synthetic Aperture Radar) images acquired by ERS1/2 and RADARSAT1/2 satellites in the period 1992–2011 are employed. Ground velocities measured along the satellite Line Of Sight (LOS) are projected along the maximum slope directions to derive more reliable deformation rates. An activity threshold of ±5 mm/year is determined by applying the average projected velocity of local slopes to the PSI data precision. The intensity threshold between extremely and very slow phenomena (16 mm/year) is reduced by ~20% to account for temporal and spatial averages, being applied to attribute representative velocities to each landslide. The methodology allows assessing the state of activity and the intensity for 13 of the 24 landslides pre-mapped in the 2007 inventory and for two newly identified phenomena. Results, as well as the major factors influencing the approach, are shown and discussed. Pending issues of the proposed methodology are critically tackled and include the lack of PSI data within the landslide boundaries, temporal coverage of the available estimates, need of field checks, and operative procedures to set the activity and intensity thresholds.


Landslides Persistent scatterer interferometry State of activity Intensity SAR interferometry PSI-based matrix 



This work was carried out within the SAFER (Services and Applications For Emergency Response) project, funded by the European Commission within the 7th Framework Programme under the Global Monitoring for Environment and Security initiative, with Grant Agreement no. 218802.


  1. Amodio Morelli L, Bonardi G, Colonna V, Dietrich D, Giunta G, Ippolito F et al (1976) L′arco Calabro-Peloritano nell′orogene Appenninico- Maghrebide. Mem Soc Geol Ital 17:1–60Google Scholar
  2. Bianchini S, Cigna F, Righini G, Proietti C, Casagli N (2012) Landslide hotspot mapping by means of persistent scatterer interferometry. Environ Earth Sci 67:1155–1172CrossRefGoogle Scholar
  3. Bianchini S, Cigna F, Casagli N (2013) Improving landslide inventories with multi-temporal measures of ground displacements retrieved through Persistent Scatterer Interferometry. In: Proceedings of the second world landslide forum, Rome (Italy), vol 3, pp 7–13Google Scholar
  4. Cascini L, Fornaro G, Peduto D (2010) Advanced low and full resolution DInSAR map generation for slow-moving landslide analysis at different scales. Eng Geol 112:29–42CrossRefGoogle Scholar
  5. Catani F, Casagli N, Ermini L, Righini G, Menduni G (2005) Landslide hazard and risk mapping at catchment scale in the Arno River basin. Landslides 2(4):329–342CrossRefGoogle Scholar
  6. Cigna F, Bianchini S, Casagli N (2013) How to assess landslide activity and intensity with persistent scatterer interferometry (PSI): the PSI-based matrix approach. Landslides 3(10):267–283CrossRefGoogle Scholar
  7. Cigna F, Bianchini S, Righini G, Proietti C, Casagli N (2010). Updating landslide inventory maps in mountain areas by means of Persistent Scatterer Interferometry (PSI) and photo-interpretation: Central Calabria (Italy) case study. In: Malet JP, Glade T, Casagli N (eds) Mountain risks: bringing science to society (572 pp). CERG Editions, Strasbourg, France, pp 3–9Google Scholar
  8. Costantini M, Iodice A, Magnapane L, Pietranera L (2000) Monitoring terrain movements by means of sparse SAR differential interferometric measurements. In: Proceedings of IGARSS 2000, 20th IEEE international geoscience and remote sensing symposium, Honolulu, Hawaii, USA, 24–28 July 2000, pp 3225–3227Google Scholar
  9. Cruden DM, Varnes DJ (1996) Landslide types and processes. In: Turner AK, Schuster RL (eds) Landslides: investigation and mitigation, Sp. Rep. 247, Transportation Research Board, National Research Council. National Academy, Washington DC, pp 36–75Google Scholar
  10. Einstein HH (1988) Landslide risk assessment procedure. In: Special Lecture, Proceedings of 5th international symposium on landslides. Lausanne, Switzerland, Rotterdam, Balkema, vol 2, pp 1075–1090Google Scholar
  11. Farina P, Colombo D, Fumagalli A, Marks F, Moretti S (2006) Permanent scatterers for landslide investigations: outcomes from the ESA-SLAM project. Eng Geol 88:200–217CrossRefGoogle Scholar
  12. Ferretti A, Prati C, Rocca F (2001) Permanent scatterers in SAR interferometry. IEEE Trans Geosci Remote Sens 39(1):8–20CrossRefGoogle Scholar
  13. Frangioni S, Bianchini S, Moretti S (2015) Landslide inventory updating by means of persistent scatterer interferometry (PSI): the Setta basin (Italy) case study. Geomat Nat Hazards Risk 6(5-7):419–438CrossRefGoogle Scholar
  14. Hungr O (1997) Some methods of landslide intensity mapping. In: Cruden D, Fell R (eds) Landslide risk assessment. Proceedings of the international workshop on landslide risk assessment, Honolulu, USA, 19–21 Feb 1997. Balkema, Rotterdam, pp 215–226Google Scholar
  15. IUGS/WGL-International Union of Geological Sciences Working Group on Landslides (1995) A suggested method for describing the rate of movement of a landslide. IAEG Bull 52(75–78):1933–1939Google Scholar
  16. Meisina C, Zucca F, Notti D, Colombo A, Cucchi A, Savio G, Giannico C, Bianchi M (2008) Geological interpretation of PSInSAR data at regional scale. Sensors 8(11):7469–7492CrossRefGoogle Scholar
  17. Notti D, Davalillo JC, Herrera G, Mora O (2010) Assessment of the performance of X-band satellite radar data for landslide mapping and monitoring: Upper Tena Valley case study. Nat Hazards Earth Syst Sci 10:1865–1875CrossRefGoogle Scholar
  18. Notti D, Herrera G, Bianchini S, Meisina C, García-Davalillo JC, Zucca F (2014) A methodology for improving landslide PSI data analysis. Int J Remote Sens 35(6):2186–2214Google Scholar
  19. Righini G, Pancioli V, Casagli N (2012) Updating landslide inventory maps using persistent scatterer interferometry (PSI). Int J Remote Sens 33(7):2068–2096. doi: 10.1080/01431161.2011.605087Google Scholar
  20. WP/WLI—Working Party on World Landslide Inventory (1993) Multilingual glossary for landslides. The Canadian Geotechnical Society, BiTech, Richmond BCGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Francesca Cigna
    • 1
    • 2
  • Silvia Bianchini
    • 1
  • Nicola Casagli
    • 1
  1. 1.Earth Sciences DepartmentUniversity of FirenzeFlorenceItaly
  2. 2.Italian Space Agency (ASI)RomeItaly

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