CINECA IRIS Institutional Research Information System
IRIS è la soluzione IT che facilita la raccolta e la gestione dei dati relativi alle attività e ai prodotti della ricerca. Fornisce a ricercatori, amministratori e valutatori gli strumenti per monitorare i risultati della ricerca, aumentarne la visibilità e allocare in modo efficace le risorse disponibili.
EnglishEngineering rock mass classification is usually the first stage in the analysis and characterization of rock slopes. However, when dealing with sedimentary/heterogeneous rock masses, the use of existing classification methods can be difficult and often misleading, especially when used to define rockfall risk areas and appropriate slope mitigation works. In this research, we describe a novel approach for geomechanical rock slope analysis based on the combined use of remote sensing, geographic information systems (GIS), and the Slope Mass Rating (SMR) classification system. The Montagna dei Fiori area (Italian central Apennines), which is characterized by the sedimentary rocks of the Umbria Marche heterogeneous succession, is used as a case study to demonstrate the application of the proposed approach. Conventional geomechanical scanlines are integrated with photogrammetric techniques to increase the amount of data collected, especially in inaccessible areas. In particular, a new fast and low-cost method of georeferencing 3D photogrammetric models is presented. GIS are used to manage all the data acquired using remote sensing techniques and geomechanical analyses, and a semi-automatic tool developed to allow calculation of the SMR along a major highway, the SP52, which crosses the study area. Finally, a modification of the SMR procedure is proposed to enable definition of the most appropriate mitigation works in folded heterogeneous sedimentary rock masses comprising alternating marls and limestones. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
| Titolo: | A new approach for defining Slope Mass Rating in heterogeneous sedimentary rocks using a combined remote sensing GIS approach | |
| Autori: | ||
| Data di pubblicazione: | 2018 | |
| Rivista: | ||
| Abstract: | Engineering rock mass classification is usually the first stage in the analysis and characterization of rock slopes. However, when dealing with sedimentary/heterogeneous rock masses, the use of existing classification methods can be difficult and often misleading, especially when used to define rockfall risk areas and appropriate slope mitigation works. In this research, we describe a novel approach for geomechanical rock slope analysis based on the combined use of remote sensing, geographic information systems (GIS), and the Slope Mass Rating (SMR) classification system. The Montagna dei Fiori area (Italian central Apennines), which is characterized by the sedimentary rocks of the Umbria Marche heterogeneous succession, is used as a case study to demonstrate the application of the proposed approach. Conventional geomechanical scanlines are integrated with photogrammetric techniques to increase the amount of data collected, especially in inaccessible areas. In particular, a new fast and low-cost method of georeferencing 3D photogrammetric models is presented. GIS are used to manage all the data acquired using remote sensing techniques and geomechanical analyses, and a semi-automatic tool developed to allow calculation of the SMR along a major highway, the SP52, which crosses the study area. Finally, a modification of the SMR procedure is proposed to enable definition of the most appropriate mitigation works in folded heterogeneous sedimentary rock masses comprising alternating marls and limestones. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature. | |
| Handle: | http://hdl.handle.net/11564/702071 | |
| Appare nelle tipologie: | 1.1 Articolo in rivista |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| Francioni2019_Article_ANewApproachForDefiningSlopeMa.pdf | Original Paper | PDF editoriale | Administrator Richiedi una copia | |
| Francioni2019_Article_ANewApproachForDefiningSlopeMa.pdf | PDF editoriale | Administrator Richiedi una copia |
http://hdl.handle.net/11564/702071
Copyright © 2022