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Geoinformatic Analysis of Rainfall-Triggered Landslides in Crete (Greece) Based on Spatial Detection and Hazard Mapping

Author

Listed:
  • Athanasios V. Argyriou

    (Laboratory of Geophysical—Satellite Remote Sensing & Archaeo-Environment (GeoSat ReSeArch), Institute for Mediterranean Studies (IMS), Foundation for Research & Technology Hellas (FORTH), 74100 Rethymno, Greece
    Centre for Applied Geosciences, School of Earth and Environmental Sciences, University of Portsmouth, Portsmouth PO1 3QL, UK)

  • Christos Polykretis

    (Laboratory of Geophysical—Satellite Remote Sensing & Archaeo-Environment (GeoSat ReSeArch), Institute for Mediterranean Studies (IMS), Foundation for Research & Technology Hellas (FORTH), 74100 Rethymno, Greece)

  • Richard M. Teeuw

    (Centre for Applied Geosciences, School of Earth and Environmental Sciences, University of Portsmouth, Portsmouth PO1 3QL, UK)

  • Nikos Papadopoulos

    (Laboratory of Geophysical—Satellite Remote Sensing & Archaeo-Environment (GeoSat ReSeArch), Institute for Mediterranean Studies (IMS), Foundation for Research & Technology Hellas (FORTH), 74100 Rethymno, Greece)

Abstract

Among several natural and anthropogenic conditioning factors that control slope instability, heavy rainfall is a key factor in terms of triggering landslide events. In the Mediterranean region, Crete suffers the frequent occurrence of heavy rainstorms that act as a triggering mechanism for landslides. The Mediterranean island of Crete suffers from frequent occurrences of heavy rainstorms, which often trigger landslides. Therefore, the spatial and temporal study of recent storm/landslide events and the projection of potential future events is crucial for long-term sustainable land use in Crete and Mediterranean landscapes with similar geomorphological settings, especially with climate change likely to produce bigger and more frequent storms in this region. Geoinformatic technologies, mainly represented by remote sensing (RS) and Geographic Information Systems (GIS), can be valuable tools towards the analysis of such events. Considering an administrative unit of Crete (municipality of Rethymnon) for investigation, the present study focused on using RS and GIS-based approaches to: (i) detect landslides triggered by heavy rainstorms during February 2019; (ii) determine the interaction between the triggering factor of rainfall and other conditioning factors; and (iii) estimate the spatial component of a hazard map by spatially indicating the possibility for rainfall-triggered landslides when similar rainstorms take place in the future. Both landslide detection and hazard mapping outputs were validated by field surveys and empirical analysis, respectively. Based on the validation results, geoinformatic technologies can provide an ideal methodological framework for the acquisition of landslide-related knowledge, being particularly beneficial to land-use planning and decision making, as well as the organization of emergency actions by local authorities.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:7:p:3956-:d:780855
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    References listed on IDEAS

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    1. Christos Polykretis & Manolis G. Grillakis & Athanasios V. Argyriou & Nikos Papadopoulos & Dimitrios D. Alexakis, 2021. "Integrating Multivariate (GeoDetector) and Bivariate (IV) Statistics for Hybrid Landslide Susceptibility Modeling: A Case of the Vicinity of Pinios Artificial Lake, Ilia, Greece," Land, MDPI, vol. 10(9), pages 1-23, September.
    2. Prabin Kayastha & Megh Dhital & Florimond Smedt, 2012. "Landslide susceptibility mapping using the weight of evidence method in the Tinau watershed, Nepal," 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. 63(2), pages 479-498, September.
    3. Hariklia D. Skilodimou & George D. Bathrellos & Efterpi Koskeridou & Konstantinos Soukis & Dimitrios Rozos, 2018. "Physical and Anthropogenic Factors Related to Landslide Activity in the Northern Peloponnese, Greece," Land, MDPI, vol. 7(3), pages 1-18, July.
    4. 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.
    5. Jewgenij Torizin & Michael Fuchs & Adnan Alam Awan & Ijaz Ahmad & Sardar Saeed Akhtar & Simon Sadiq & Asif Razzak & Daniel Weggenmann & Faseeh Fawad & Nimra Khalid & Faisan Sabir & Ahsan Jamal Khan, 2017. "Statistical landslide susceptibility assessment of the Mansehra and Torghar districts, Khyber Pakhtunkhwa Province, Pakistan," 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. 89(2), pages 757-784, November.
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    Cited by:

    1. Marco Manzan & Giovanni Bacaro & Andrea Nardini & Giulia Casagrande & Amedeo Pezzi & Francesco Petruzzellis & Enrico Tordoni & Giorgio Fontolan, 2022. "Climate Change Risk and Vulnerabilities Analysis in Trieste SECAP," Sustainability, MDPI, vol. 14(10), pages 1-28, May.
    2. Constantinos Nefros & Dimitrios S. Tsagkas & Gianna Kitsara & Constantinos Loupasakis & Christos Giannakopoulos, 2023. "Landslide Susceptibility Mapping under the Climate Change Impact in the Chania Regional Unit, West Crete, Greece," Land, MDPI, vol. 12(1), pages 1-25, January.

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