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.
A new approach for defining Slope Mass Rating in heterogeneous sedimentary rocks using a combined remote sensing GIS approach
Francioni, Mirko
;Sciarra, Nicola;Calamita, Fernando
2018-01-01
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.File | Dimensione | Formato | |
---|---|---|---|
Francioni2019_Article_ANewApproachForDefiningSlopeMa.pdf
Solo gestori archivio
Descrizione: Original Paper
Tipologia:
PDF editoriale
Dimensione
30 MB
Formato
Adobe PDF
|
30 MB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Francioni2019_Article_ANewApproachForDefiningSlopeMa.pdf
Solo gestori archivio
Tipologia:
PDF editoriale
Dimensione
2.31 MB
Formato
Adobe PDF
|
2.31 MB | Adobe PDF | Visualizza/Apri Richiedi una copia |
sciarra 2 A new approach.pdf
accesso aperto
Descrizione: File pubblicazione post referaggio
Tipologia:
Documento in Post-print
Dimensione
4.16 MB
Formato
Adobe PDF
|
4.16 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.