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Landslide Mapping and Susceptibility Assessment Using Geospatial Analysis and Earth Observation Data

Author

Listed:
  • Emmanouil Psomiadis

    (Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos st., 11855 Athens, Greece)

  • Andreas Papazachariou

    (Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos st., 11855 Athens, Greece)

  • Konstantinos X. Soulis

    (Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos st., 11855 Athens, Greece)

  • Despoina-Simoni Alexiou

    (Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos st., 11855 Athens, Greece)

  • Ioannis Charalampopoulos

    (Department of Crop Science, Agricultural University of Athens, 75 Iera Odos st., 11855 Athens, Greece)

Abstract

The western part of Crete Island has undergone serious landslide events in the past. The intense rainfalls that took place in the September 2018 to February 2019 period provoked extensive landslide events at the northern part of Chania prefecture, along the motorway A90. Geospatial analysis methods and earth observation data were utilized to investigate the impact of the various physical and anthropogenic factors on landslides and to evaluate landslide susceptibility. The landslide inventory map was created based on literature, aerial photo analysis, satellite images, and field surveys. A very high-resolution Digital Elevation Model (DEM) and land cover map was produced from a dense point cloud and Earth Observation data (Landsat 8), accordingly. Sentinel-2 data were used for the detection of the recent landslide events and offered suitable information for two of them. Eight triggering factors were selected and manipulated in a GIS-based environment. A semi-quantitative method of Analytical Hierarchy Process (AHP) and Weighted Linear Combination (WLC) was applied to evaluate the landslide susceptibility index (LSI) both for Chania prefecture and the motorway A90 in Chania. The validation of the two LSI maps provided accurate results and, in addition, several susceptible points with high landslide hazards along the motorway A90 were detected.

Suggested Citation

  • Emmanouil Psomiadis & Andreas Papazachariou & Konstantinos X. Soulis & Despoina-Simoni Alexiou & Ioannis Charalampopoulos, 2020. "Landslide Mapping and Susceptibility Assessment Using Geospatial Analysis and Earth Observation Data," Land, MDPI, vol. 9(5), pages 1-26, April.
    • Handle: RePEc:gam:jlands:v:9:y:2020:i:5:p:133-:d:351666
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    References listed on IDEAS

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    3. Athanasios V. Argyriou & Christos Polykretis & Richard M. Teeuw & Nikos Papadopoulos, 2022. "Geoinformatic Analysis of Rainfall-Triggered Landslides in Crete (Greece) Based on Spatial Detection and Hazard Mapping," Sustainability, MDPI, vol. 14(7), pages 1-25, March.
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