Rockfall Analysis from UAV-Based Photogrammetry and 3D Models of a Cliff Area
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 h...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/8/1/31 |
| _version_ | 1797344312767283200 |
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| author | Daniele Cirillo Michelangelo Zappa Anna Chiara Tangari Francesco Brozzetti Fabio Ietto |
| author_facet | Daniele Cirillo Michelangelo Zappa Anna Chiara Tangari Francesco Brozzetti Fabio Ietto |
| author_sort | Daniele Cirillo |
| collection | DOAJ |
| description | 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 × 10<sup>7</sup> 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. |
| first_indexed | 2024-03-08T11:00:35Z |
| format | Article |
| id | doaj.art-d707f0b31d9042d6b43e46f8cec13e33 |
| institution | Directory Open Access Journal |
| issn | 2504-446X |
| language | English |
| last_indexed | 2024-03-08T11:00:35Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj.art-d707f0b31d9042d6b43e46f8cec13e332024-01-26T16:06:16ZengMDPI AGDrones2504-446X2024-01-01813110.3390/drones8010031Rockfall Analysis from UAV-Based Photogrammetry and 3D Models of a Cliff AreaDaniele Cirillo0Michelangelo Zappa1Anna Chiara Tangari2Francesco Brozzetti3Fabio Ietto4Laboratorio di Geologia Strutturale Cartografia e Modellazione Geologica, DiSPuTer, Università G. d’Annunzio, 66100 Chieti, ItalyIndependent Researcher, 87030 Falconara Albanese, ItalyDipartimento DiSPuTer, Università G. d’Annunzio, 66100 Chieti, ItalyLaboratorio di Geologia Strutturale Cartografia e Modellazione Geologica, DiSPuTer, Università G. d’Annunzio, 66100 Chieti, ItalyDepartment of Biology, Ecology and Earth Science, University of Calabria, 87036 Arcavacata di Rende, ItalyThe 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 × 10<sup>7</sup> 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.https://www.mdpi.com/2504-446X/8/1/31UAV photogrammetric surveypost-processing kinematic (PPK) photogrammetryrockfall analysisjointing frequency analysisgeomechanical analysis |
| spellingShingle | Daniele Cirillo Michelangelo Zappa Anna Chiara Tangari Francesco Brozzetti Fabio Ietto Rockfall Analysis from UAV-Based Photogrammetry and 3D Models of a Cliff Area Drones UAV photogrammetric survey post-processing kinematic (PPK) photogrammetry rockfall analysis jointing frequency analysis geomechanical analysis |
| title | Rockfall Analysis from UAV-Based Photogrammetry and 3D Models of a Cliff Area |
| title_full | Rockfall Analysis from UAV-Based Photogrammetry and 3D Models of a Cliff Area |
| title_fullStr | Rockfall Analysis from UAV-Based Photogrammetry and 3D Models of a Cliff Area |
| title_full_unstemmed | Rockfall Analysis from UAV-Based Photogrammetry and 3D Models of a Cliff Area |
| title_short | Rockfall Analysis from UAV-Based Photogrammetry and 3D Models of a Cliff Area |
| title_sort | rockfall analysis from uav based photogrammetry and 3d models of a cliff area |
| topic | UAV photogrammetric survey post-processing kinematic (PPK) photogrammetry rockfall analysis jointing frequency analysis geomechanical analysis |
| url | https://www.mdpi.com/2504-446X/8/1/31 |
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