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Landslide Susceptibility Mapping of Central and Western Greece, Combining NGI and WoE Methods, with Remote Sensing and Ground Truth Data

Author

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  • Charalampos Kontoes

    (National Observatory of Athens, Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, BEYOND Center, GR-15236 Athens, Greece)

  • Constantinos Loupasakis

    (Laboratory of Engineering Geology and Hydrogeology, Department of Geological Sciences, School of Mining and Metallurgical Engineering, National Technical University of Athens, GR-15780 Athens, Greece)

  • Ioannis Papoutsis

    (National Observatory of Athens, Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, BEYOND Center, GR-15236 Athens, Greece)

  • Stavroula Alatza

    (National Observatory of Athens, Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, BEYOND Center, GR-15236 Athens, Greece)

  • Eleftheria Poyiadji

    (Hellenic Survey of Geology and Mineral Exploration, GR-11527 Athens, Greece)

  • Athanassios Ganas

    (National Observatory of Athens, Institute of Geodynamics, GR-11810 Athens, Greece)

  • Christina Psychogyiou

    (National Observatory of Athens, Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, BEYOND Center, GR-15236 Athens, Greece)

  • Mariza Kaskara

    (National Observatory of Athens, Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, BEYOND Center, GR-15236 Athens, Greece)

  • Sylvia Antoniadi

    (National Observatory of Athens, Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, BEYOND Center, GR-15236 Athens, Greece)

  • Natalia Spanou

    (Hellenic Survey of Geology and Mineral Exploration, GR-11527 Athens, Greece)

Abstract

The exploitation of remote sensing techniques has substantially improved pre- and post- disaster landslide management over the last decade. A variety of landslide susceptibility methods exists, with capabilities and limitations related to scale and spatial accuracy issues, as well as data availability. The Interferometric Synthetic Aperture Radar (InSAR) capabilities have significantly contributed to the detection, monitoring, and mapping of landslide phenomena. The present study aims to point out the contribution of InSAR data in landslide detection and to evaluate two different scale landslide models by comparing a heuristic to a statistical method for the rainfall-induced landslide hazard assessment. Aiming to include areas with both high and low landslide occurrence frequencies, the study area covers a large part of the Aetolia–Acarnania and Evritania prefectures, Central and Western Greece. The landslide susceptibility product provided from the weights of evidence (WoE) method proved more accurate, benefitting from the expert opinion and the landslide inventory. On the other hand, the Norwegian Geological Institute (NGI) methodology has the edge on its immediate implementation, with minimum data requirements. Finally, it was proved that using sequential SAR image acquisitions gives the benefit of an updated landslide inventory, resulting in the generation of, on request, updated landslide susceptibility maps.

Suggested Citation

  • Charalampos Kontoes & Constantinos Loupasakis & Ioannis Papoutsis & Stavroula Alatza & Eleftheria Poyiadji & Athanassios Ganas & Christina Psychogyiou & Mariza Kaskara & Sylvia Antoniadi & Natalia Spa, 2021. "Landslide Susceptibility Mapping of Central and Western Greece, Combining NGI and WoE Methods, with Remote Sensing and Ground Truth Data," Land, MDPI, vol. 10(4), pages 1-25, April.
  • Handle: RePEc:gam:jlands:v:10:y:2021:i:4:p:402-:d:534298
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    References listed on IDEAS

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    1. 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.
    2. N. Sabatakakis & G. Koukis & E. Vassiliades & S. Lainas, 2013. "Landslide susceptibility zonation in Greece," 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. 65(1), pages 523-543, January.
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    4. Maria Kouli & Constantinos Loupasakis & Pantelis Soupios & Filippos Vallianatos, 2010. "Landslide hazard zonation in high risk areas of Rethymno Prefecture, Crete Island, Greece," 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. 52(3), pages 599-621, March.
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    4. Xianmin Wang & Xinlong Zhang & Jia Bi & Xudong Zhang & Shiqiang Deng & Zhiwei Liu & Lizhe Wang & Haixiang Guo, 2022. "Landslide Susceptibility Evaluation Based on Potential Disaster Identification and Ensemble Learning," IJERPH, MDPI, vol. 19(21), pages 1-26, October.

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