Filippo Giadrossich

Rockfalls represent a widespread natural hazard that threatens infrastructures and settlements in mountainous and coastal areas. In Baunei (Sardinia, Italy), steep carbonate cliffs above the SS125 road frequently generate block detachments that endanger traffic and nearby urban areas. The present work adopts a quantitative risk assessment framework, consistent with the Swiss PLANAT guidelines, to evaluate the protective effectiveness of direct-protection forests in combination with engineered barriers. The framework integrates the key components of hazard, exposure, and vulnerability to quantify direct-impact risk and associated economic loss. Using Rockyfor3D simulations, three scenarios were analysed: bare slope, forest only, and forest plus protective works. The results demonstrate that vegetation markedly reduces both runout distance and kinetic energy of falling blocks, halving the direct-impact risk compared to bare-slope conditions. The addition of barriers further decreases residual exposure, with most trajectories intercepted and remaining impacts limited to low-energy classes. Monetised risk estimates confirm an 84% reduction with forest cover alone and near-complete mitigation when complemented by fences, except in short discontinuous segments. The proposed approach offers a replicable and cost-effective tool for rockfall risk management and sustainable protection forest planning in Mediterranean settings.

Urban trees are subjected to stressful conditions caused by anthropogenic, biotic, and abiotic factors. These stressors can cause structural changes, increasing the risks of branch failure or even complete uprooting. To mitigate the risks to people’s safety, administrators must assess and evaluate the health and structural stability of trees. Risk analysis typically takes into account environmental vulnerability and tree characteristics, assessed at a specific point in time. However, although dynamic tests play a crucial role in risk assessment in urban environments, the high cost of the sensors significantly limits their widespread application across large tree populations. For this reason, the present study aims to evaluate the effectiveness of low-cost sensors in monitoring tree dynamics. A low-cost micro-electro-mechanical systems (MEMS) sensor is tested in the laboratory and the field using a pull-and-release test, and its performance is compared with that of seismic reference accelerometers. The collected data are analyzed and compared in terms of both the frequency and time domains. To obtain reliable measurements, the accelerations must be generated by substantial dynamic excitations, such as high wind events or abrupt changes in loading conditions. The results show that the MEMS sensor has lower accuracy and higher noise compared to the seismic sensor; however, the MEMS can still identify the main peaks in the frequency domain compared to the seismic sensor, provided that the input amplitude is sufficiently high.

The ‘2018 Marganai Forest Soil Erosion Experiment Database’ is a comprehensive collection of measures taken during scientific experiment trials designed to investigate the effects of forest canopy coverage on soil erosion under intense artificial rainfall, four years after coppicing. The investigation involved the establishment of eight paired plots with and without forest canopy coverage, subjected to artificial rainfall simulation aimed to measure the amount of sediment transported by runoff. The work represents a valuable resource for researchers interested in understanding the complex implications of forest management practices on soil erosion. The paper, produced using Quarto in a Gitlab-based RStudio project, is an example of ‘reproducible research’ documenting that the database provides detailed information on the experimental setup as well as on the range of different measurements that have been collected. The database, produced using NFS-DataDocumentationProcedure, is stored in an SQLite file, extensively exploiting the relational properties of the engine, enhancing data accessibility, interoperability and reusability.

The mitigation of the risk from gravitational natural hazards involves a variety of measures in engineering and management. The basis for any measures is the identification of hazard prone areas by considering past events and model simulations. Various models are available for the simulation of gravitational natural hazards but their application is often a trade off between simplicity and accuracy. A physical interpretation of the well established energy line principle allows to formulate the corresponding equations of motion and to introduce a model that is still simple but more accurate. The equations of motion are derived by the application of the Lagrange formalism for a friction block that slides on an inclined plane. Furthermore, a numerical algorithm based on the Euler method is set up to solve the equations of motion on a digital terrain model. This model is applied and compared to the energy line principle based on the equation of energy and to past events in two case studies for rockfall and landslide. The outcomes show that the formulation of the energy line principle with the equations of motion corresponds well to the formulation based on the equation of energy but allows a more differentiated simulation of the runout zone that reproduces better the past events. However, there are artifacts from the numerical solution of the equations of motion that require a deeper theoretical investigation and also uncertainties in the past events that must be worked through in a more elaborated empirical study. Nevertheless, the concept of this approach to enhance the performance of the energy line principle simply by another perspective to the same physical concept is thus proved.

CSV and Excel formats are among the most common storage formats for data sharing, especially in scientific and government contexts. Chaves-Fraga notes that a significant amount of public data is published in tabular formats such as CSV and Excel, which can hinder data accessibility and interoperability due to their lack of standardized metadata (Chaves-Fraga, 2020). This is in line with the findings of Burg et al. (2019). They highlight that although CSV files are widely used due to their simplicity, they often lack the necessary metadata to ensure data quality and provenance, which are crucial for compliance with the FAIR principles. Furthermore, Kaur et al. (2021) highlight that many health information systems allow data to be exported in CSV format, which is accessible but does not provide the semantic interoperability needed for effective data sharing and reuse. Furthermore, the limitations of CSV and Excel formats are compounded when datasets are converted to SQLite databases.The NFS group (NuoroForestrySchool.io) has developed an open source Python-based application (https://gitlab.com/NuoroForestrySchool/nfs-data-documentation-procedure) that facilitates the organization of the data a researcher is willing to share. The application is designed to be used as a command line tool or through a graphical interface. It reads as input a spreadsheet file with one sheet for each table, plus an application-specific sheet defining the database schema, the data dictionary, the DataCite metadata, and other specific metadata (extended title, abstract/summary). The output of the procedure is represented by a SQLite file containing all the data and metadata, as well as an image of the graphical ERD-like schema, and a formal pdf document presenting the contents of the database. The SQLite file is a metadata-rich SQL-based database, taking full advantage of relational features and thus improving data accessibility, interoperability, and reusability by humans and machines.The use of the procedure is demonstrated by processing a simple but significant use case.LITERATURE Chaves-Fraga, David, Edna Ruckhaus, Freddy Priyatna, Maria-Esther Vidal, e Oscar Corcho. 2021. «Enhancing virtual ontology based access over tabular data with Morph-CSV». A cura di Axel-Cyrille Ngonga Ngomo, Muhammad Saleem, Ruben Verborgh, Muhammad Saleem, Ruben Verborgh, Muhammad Intizar Ali, e Olaf Hartig. Semantic Web 12 (6): 869–902. https://doi.org/10.3233/SW-210432. Kaur, Jasleen, Jasmine Kaur, Shruti Kapoor, e Harpreet Singh. 2021. «Design & Development of Customizable Web API for Interoperability of Antimicrobial Resistance Data». Scientific Reports 11 (1): 11226. https://doi.org/10.1038/s41598-021-90601-z. Van Den Burg, G. J. J., A. Nazábal, e C. Sutton. 2019. «Wrangling Messy CSV Files by Detecting Row and Type Patterns». Data Mining and Knowledge Discovery 33 (6): 1799–1820. https://doi.org/10.1007/s10618-019-00646-y.

Accurately identifying hazard-prone areas is critical for mitigating risks from gravitational natural hazards such as landslides and rockfalls. Although many models exist to simulate these rapid mass movements, there are often trade-offs between simplicity, robustness and precision. This study builds upon the well-established energy line principle by reinterpreting the energy line angle as a kinetic friction coefficient, enabling the derivation of equations of motion that describe the forces driving mass movements. Using the Lagrange formalism for a sliding friction block, the equations of motion are developed and solved numerically with an Euler-based algorithm applied to digital terrain models. This force-based perspective retains the energy line principle’s simplicity and robustness while offering improved accuracy. In this study, the method is evaluated using two case studies with 36 documented landslide and 6 rockfall events in northern Italy. The results were compared with those of a traditional energy-based approach as well as with documented past events. The refined model produces smaller, more differentiated runout zones, achieving 41% resp. 11% higher true positive and 65% resp. 16% lower false positive rates compared to the energy-based approach for reproducing the past rockfall and landslide events. These findings demonstrate that the developed approach enhances accuracy without increasing computational complexity. This enhancement has the potential to extend the application of the energy line principle beyond preliminary analyses, enabling more detailed and reliable hazard mapping at larger spatial scales.