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

Highlights

• A multi-methodological approach for rockfall simulations: from slope face to valley

• Integration of UAV-SfM and satellite-based data for rock mass and debris analysis

• Obtaining ground-truth information from different types of virtual outcrop models

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 approach which integrates different types of remote sensing data and techniques. Specifically, ground-truth data (e.g., rock mass geo-structural information, rock block inventory) were generated by geologically-supervised interpretations of high-resolution virtual outcrop models (VOMs). These data were then used for reconstructing the in-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 scenarios are consistent with the ground-truth data, both in terms of size and spatial distribution. Thus, we believe that the proposed approach can be effectively applied to other areas, characterized by similar geological features but higher levels of exposure and vulnerability.

Introduction

Rockfalls represent one of the most insidious landslide phenomena for human-related activities, especially along railways, roads, and lifelines. The hazardousness of such phenomena is mostly related to the difficulty in predicting their occurrence, essentially due to the complexity of triggering mechanisms and the lack of clear precursors before the collapse (Feng et al., 2021). Other threatening features of rockfalls are the high frequency of occurrence (Leroi, 2005) and long run-out of the mobilized blocks (e.g., Giacomini et al., 2009; Hungr et al., 2014) which, in turn, depend on their high kinetic energy and velocity. For these reasons, a comprehensive rockfall analysis should include not only the identification of the possible source areas, but also the delimitation of the areas potentially invaded by the falling rock blocks (Hantz et al., 2021). As regards the latter aspect, in the last years different numerical models wre developed for calculating the trajectories and run-out of detached blocks (e.g., Volkwein et al., 2011; Žabota et al., 2021), usually through the simulation of the physical process. However, the consistency of similar models strongly relies on the calibration procedure of the input parameters. In particular, the estimation of shape and size of the potentially unstable blocks and the definition of reliable values of restitution and friction coefficients represent key steps of the calibration workflow (Wyllie, 2014; Asteriou and Tsiambaos, 2018). The calibration requires detailed information about surficial topography; in this respect, nowadays it is possible to obtain accurate terrain data through numerous remote sensing techniques, e.g., laser scanning (e.g., Tonini and Abellan, 2014; Mazzanti et al., 2018) or structure-from-motion (SfM) photogrammetry based on UAV (unmanned aerial vehicle) acquisitions (e.g., Fazio et al., 2019; Robiati et al., 2019). The acquired data can be then employed for the reconstruction of virtual outcrop models (VOMs), whose potential was shown in different contexts, from slope stability analyses (e.g., Baghbanan et al., 2017; Cheng et al., 2021) to studies of fracture network characterization (e.g., Volatili et al., 2019; Forte et al., 2021), including geotechnical characterization of rock masses and the development of Discrete Fracture Network (DFN) models (e.g., Ren et al., 2017; Ma et al., 2020; Gottron and Henk, 2021). However, in the literature it is quite unusual to find analyses which integrate both remote sensing data and DFN models in the framework of rockfall trajectory studies (Lambert et al., 2012; Crosta et al., 2015).

Thus, in this work we present a rockfall trajectory study concerning the south-western slope of Mt. Catiello (Sorrento Peninsula, southern Italy). This area shows clear evidence of rock slope instability: therefore, we used Rockyfor3D (Dorren, 2016) for reconstructing the potential trajectories of the released rock blocks. Specific focus was dedicated to the collection of detailed terrain data through different remote sensing techniques (i.e., UAV-SfM and satellite imagery). These data were used not only for calibrating and validating the results of rockfall numerical simulations (sensu Dorren et al., 2013), but also for performing a detailed rock mass characterization based on a DFN model. In this respect, considering the geological, structural and geomorphological features of Mt. Catiello (i.e., steep, variously fractured carbonate slopes), we propose an integrated, comprehensive approach that can be effectively applied to other areas of the Sorrento Peninsula, characterized by similar features but higher levels of exposure and vulnerability (e.g., populated coastal areas).