Natural Hazards

, Volume 78, Issue 1, pp 681–697 | Cite as

Landslide susceptibility modeling assisted by Persistent Scatterers Interferometry (PSI): an example from the northwestern coast of Malta

  • Daniela Piacentini
  • Stefano Devoto
  • Matteo Mantovani
  • Alessandro Pasuto
  • Mariacristina Prampolini
  • Mauro Soldati
Original Paper


Persistent Scatterers Interferometry (PSI) techniques are widely employed in geosciences to detect and monitor landslides with high accuracy over large areas, but they also suffer from physical and technological constraints that restrict their field of application. These limitations prevent us from collecting information from several critical areas within the investigated region. In this paper, we present a novel approach that exploits the results of PSI analysis for the implementation of a statistical model for landslide susceptibility. The attempt is to identify active mass movements by means of PSI and to avoid, as input data, time-/cost-consuming and seldom updated landslide inventories. The study has been performed along the northwestern coast of Malta (central Mediterranean Sea), where the peculiar geological and geomorphological settings favor the occurrence of a series of extensive slow-moving landslides. Most of these consist in rock spreads, evolving into block slides, with large limestone blocks characterized by scarce vegetation and proper inclination, which represent suitable natural radar reflectors for applying PSI. Based on geomorphometric analyses and geomorphological investigations, a series of landslide predisposing factors were selected and a susceptibility map created. The result was validated by means of cross-validation technique, field surveys and global navigation satellite system in situ monitoring activities. The final outcome shows a good reliability and could represent an adequate response to the increasing demand for effective and low-cost tools for landslide susceptibility assessment.


Landslides PSI WoE Susceptibility Malta Mediterranean Sea 



The authors acknowledge European Space Agency for providing ERS and ENVISAT radar images (C1P.7044) and AquaBioTech Group for sharing LiDAR data. The LiDAR survey (HYPERLINK “”) was carried on HawkEye II of the Airborne Hydrography AB company. SAR processing was performed using Gamma software. The research is part of the project “Coupling terrestrial and marine datasets for coastal hazard assessment and risk reduction in changing environments” funded by the EUR-OPA Major Hazards Agreement of the Council of Europe (responsible M. Soldati). We thank the two anonymous reviewers for their significant comments that helped improving the manuscript.


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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Department of Earth, Life and Environment SciencesUniversity of UrbinoUrbinoItaly
  2. 2.Department of Mathematics and GeosciencesUniversity of TriesteTriesteItaly
  3. 3.National Research Council of ItalyResearch Institute for Geo-Hydrological Protection (CNR-IRPI), PaduaPaduaItaly
  4. 4.Department of Chemical and Geological SciencesUniversity of Modena and Reggio EmiliaModenaItaly

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