The application of Unmanned Aerial Vehicles (UAVs), commonly known as drones, in geological, geomorphological, and geotechnical studies has gained significant attention due to their versatility and capability to capture high-resolution data from challenging terrains. This research uses drone-based high-resolution photogrammetry to assess the geomechanical properties and rockfall potential of several rock scarps within a wide area of 50 ha. Traditional methods for evaluating geomechanical parameters on rock scarps involve time-consuming field surveys and measurements, which can be hazardous in steep and rugged environments. By contrast, drone photogrammetry offers a safer and more efficient approach, allowing for the creation of detailed 3D models of a cliff area. These models provide valuable insights into the topography, geological structures, and potential failure mechanisms. This research processed the acquired drone imagery using advanced geospatial software to generate accurate orthophotos and digital elevation models. These outputs analysed the key factors contributing to rockfall triggering, including identifying discontinuities, joint orientations, kinematic analysis of failures, and fracturing frequency. More than 8.9 × 107 facets, representing discontinuity planes, were recognised and analysed for the kinematic failure modes, showing that direct toppling is the most abundant rockfall type, followed by planar sliding and flexural toppling. Three different fracturation grades were also identified based on the number of planar facets recognised on rock surfaces. The approach used in this research contributes to the ongoing development of fast, practical, low-cost, and non-invasive techniques for geomechanical assessment on vertical rock scarps. In particular, the results show the effectiveness of drone-based photogrammetry for rapidly collecting comprehensive geomechanical data valid to recognise the prone areas to rockfalls in vast regions.


    Access

    Download


    Export, share and cite



    Title :

    Rockfall Analysis from UAV-Based Photogrammetry and 3D Models of a Cliff Area


    Contributors:


    Publication date :

    2024




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    Coastal cliff monitoring using UAS photogrammetry and TLS

    Kersten, Thomas P. / Lindstaedt, Maren / Mechelke, Klaus | HENRY – Federal Waterways Engineering and Research Institute (BAW) | 2020

    Free access

    Electronic Data Collection for Rockfall Analysis

    Bellamy, Derrick / Bateman, Vanessa / Drumm, Eric C. et al. | Transportation Research Record | 2003


    Cliff railways

    Marks, George Corydon | Engineering Index Backfile | 1894


    Rockfall-preventing loader cab shell

    LIU JUN | European Patent Office | 2021

    Free access

    Development of Effective Rockfall Barriers

    Hearn, George | Online Contents | 1995