Landslide Susceptibility Mapping of Central and Western Greece, Combining NGI and WoE Methods, with Remote Sensing and Ground Truth Data
Charalampos Kontoes,
Constantinos Loupasakis,
Ioannis Papoutsis,
Stavroula Alatza,
Eleftheria Poyiadji,
Athanassios Ganas,
Christina Psychogyiou,
Mariza Kaskara,
Sylvia Antoniadi,
Natalia Spanou
Affiliations
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
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.
