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Improvements in the integration of remote sensing and rock slope modelling

Author

Listed:
  • Mirko Francioni

    (University of Exeter)

  • Riccardo Salvini

    (University of Siena)

  • Doug Stead

    (Simon Fraser University)

  • John Coggan

    (University of Exeter)

Abstract

Over the last two decades, the approach to the investigation of landslides has changed dramatically. The advent of new technologies for engineering geological surveys and slope analyses has led to step-change increases in the quality of data available for landslide studies. However, the use of such technologies in the survey and analysis of slopes is often complex and may not always be either desirable or feasible. In this context, this paper aims to improve the understanding of the use of remote sensing techniques for rock mass characterization and provide guidance and on how and when the data obtained from these techniques can be used as input for stability analyses. Advantages and limitations of available digital photogrammetry and laser scanning techniques will also be discussed in relation to their cost and the quality of data that can be obtained. A critique of recent research data obtained from remote sensing techniques is presented together with a discussion on use of the data for slope stability analysis. This highlights how data use may be optimized to reduce both parameter and model uncertainty in future slope analyses.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:nathaz:v:90:y:2018:i:2:d:10.1007_s11069-017-3116-8
    DOI: 10.1007/s11069-017-3116-8
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    References listed on IDEAS

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    1. Michel Jaboyedoff & Thierry Oppikofer & Antonio Abellán & Marc-Henri Derron & Alex Loye & Richard Metzger & Andrea Pedrazzini, 2012. "Use of LIDAR in landslide investigations: a review," 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. 61(1), pages 5-28, March.
    2. 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.
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    Cited by:

    1. Stefano Furlani & Alberto Bolla & Linley Hastewell & Matteo Mantovani & Stefano Devoto, 2022. "Integrated Geomechanical and Digital Photogrammetric Survey in the Study of Slope Instability Processes of a Flysch Sea Cliff (Debeli Rtič Promontory, Slovenia)," Land, MDPI, vol. 11(12), pages 1-27, December.
    2. Joana Duarte & Fernanda Rodrigues & Jacqueline Castelo Branco, 2022. "Sensing Technology Applications in the Mining Industry—A Systematic Review," IJERPH, MDPI, vol. 19(4), pages 1-16, February.
    3. Xuan-hao Wang & Wei Cui & Gui-ke Zhang & Hong Yang, 2023. "Identification of rocky ledge on steep, high slopes based on UAV photogrammetry," 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. 116(3), pages 3201-3224, April.

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