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

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

Abstract

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. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Daniela Piacentini & Stefano Devoto & Matteo Mantovani & Alessandro Pasuto & Mariacristina Prampolini & Mauro Soldati, 2015. "Landslide susceptibility modeling assisted by Persistent Scatterers Interferometry (PSI): an example from the northwestern coast of Malta," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 78(1), pages 681-697, August.
  • Handle: RePEc:spr:nathaz:v:78:y:2015:i:1:p:681-697
    DOI: 10.1007/s11069-015-1740-8
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    References listed on IDEAS

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    1. Chang-Jo Chung & Andrea Fabbri, 2003. "Validation of Spatial Prediction Models for Landslide Hazard Mapping," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 30(3), pages 451-472, November.
    2. Vorpahl, Peter & Elsenbeer, Helmut & Märker, Michael & Schröder, Boris, 2012. "How can statistical models help to determine driving factors of landslides?," Ecological Modelling, Elsevier, vol. 239(C), pages 27-39.
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    3. Qing Yang & Zhanqiang Chang & Chou Xie & Chaoyong Shen & Bangsen Tian & Haoran Fang & Yihong Guo & Yu Zhu & Daoqin Zhou & Xin Yao & Guanwen Chen & Tao Xie, 2023. "Combining Soil Moisture and MT-InSAR Data to Evaluate Regional Landslide Susceptibility in Weining, China," Land, MDPI, vol. 12(7), pages 1-34, July.
    4. Lidia Selmi & Thais S. Canesin & Ritienne Gauci & Paulo Pereira & Paola Coratza, 2022. "Degradation Risk Assessment: Understanding the Impacts of Climate Change on Geoheritage," Sustainability, MDPI, vol. 14(7), pages 1-19, April.
    5. Geoff Main & John Schembri & Ritienne Gauci & Kevin Crawford & David Chester & Angus Duncan, 2018. "The hazard exposure of the Maltese Islands," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 92(2), pages 829-855, June.
    6. Stefano Devoto & Linley J. Hastewell & Mariacristina Prampolini & Stefano Furlani, 2021. "Dataset of Gravity-Induced Landforms and Sinkholes of the Northeast Coast of Malta (Central Mediterranean Sea)," Data, MDPI, vol. 6(8), pages 1-16, July.
    7. Mirko Francioni & Riccardo Salvini & Doug Stead & John Coggan, 2018. "Improvements in the integration of remote sensing and rock slope modelling," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 90(2), pages 975-1004, January.
    8. I. P. Kovács & T. Bugya & Sz. Czigány & M. Defilippi & D. Lóczy & P. Riccardi & L. Ronczyk & P. Pasquali, 2019. "How to avoid false interpretations of Sentinel-1A TOPSAR interferometric data in landslide mapping? A case study: recent landslides in Transdanubia, Hungary," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 96(2), pages 693-712, March.

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