In this work, we present the results of a rockfall trajectory study performed on the south-western slope of Mt.Catiello (Sorrento Peninsula, southern Italy). Such a study develops within a multi-methodological approachwhich integrates different types of remote sensing data and techniques. Specifically, ground-truth data (e.g., rockmass geo-structural information, rock block inventory) were generated by geologically-supervised interpretationsof high-resolution virtual outcrop models (VOMs). These data were then used for reconstructing thein-situ fractured rock mass attributes of the Mt. Catiello peak, as provided by a Discrete Fracture Network (DFN)model, and to prepare the subsequent numerical simulations of rockfall trajectories. The resulting rockfall scenariosare consistent with the ground-truth data, both in terms of size and spatial distribution. Thus, we believethat the proposed approach can be effectively applied to other areas, characterized by similar geological featuresbut higher levels of exposure and vulnerability.

An integrated approach for the reconstruction of rockfall scenarios from UAV and satellite-based data in the Sorrento Peninsula (southern Italy)

Luca Schilirò
Primo
Conceptualization
;
Luca Smeraglia;
2022

Abstract

In this work, we present the results of a rockfall trajectory study performed on the south-western slope of Mt.Catiello (Sorrento Peninsula, southern Italy). Such a study develops within a multi-methodological approachwhich integrates different types of remote sensing data and techniques. Specifically, ground-truth data (e.g., rockmass geo-structural information, rock block inventory) were generated by geologically-supervised interpretationsof high-resolution virtual outcrop models (VOMs). These data were then used for reconstructing thein-situ fractured rock mass attributes of the Mt. Catiello peak, as provided by a Discrete Fracture Network (DFN)model, and to prepare the subsequent numerical simulations of rockfall trajectories. The resulting rockfall scenariosare consistent with the ground-truth data, both in terms of size and spatial distribution. Thus, we believethat the proposed approach can be effectively applied to other areas, characterized by similar geological featuresbut higher levels of exposure and vulnerability.
2022
Istituto di Geologia Ambientale e Geoingegneria - IGAG
Rockfall
UAV
Photogrammetry
DFN model
rock mass characterization
Rockyfor3D
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/443035
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