Article
Engineering, Geological
Settimio Ferlisi, Antonio Marchese, Dario Peduto
Summary: This study presents the results of a research aimed at quantitatively estimating the risk of slow-moving landslides on a road network, as well as the consequences in damaged conditions. New methodological approaches were successfully tested in a case study in the Campania region of southern Italy.
Article
Engineering, Civil
Raffaele Laguardia, Michele D'Amato, Matteo Coltellacci, Gino Di Trocchio, Rosario Gigliotti
Summary: This study investigates a group of 12,016 reinforced concrete buildings and proposes vulnerability, fragility, and loss curves, as well as an assessment of expected annual loss. The buildings data collected from the Da.D.O. database includes observed damage from the 2009 L'Aquila earthquake. The methodology used allows for the inclusion of undamaged and not-surveyed buildings, which are not part of the database, by considering the typological distribution in two different reference municipalities. The results obtained demonstrate that the completed database enables a more reliable seismic risk assessment, with the expected annual loss being minimally affected by the reference municipality assumed for estimating undamaged buildings.
JOURNAL OF EARTHQUAKE ENGINEERING
(2023)
Article
Engineering, Civil
N. Chieffo, T. M. Ferreira, R. da Silva Vicente, P. B. Lourenco, A. Formisano
Summary: The research aims to evaluate the susceptibility and potential damage of heritage buildings by considering local site effects. A case study in Horta, Faial, Azores, Portugal was conducted to assess the physical vulnerability of the investigated structures. The research developed a damage scenario based on real accelerograms collected after the 1998 Azores seismic event using a reliable seismic intensity prediction equation.
JOURNAL OF EARTHQUAKE ENGINEERING
(2023)
Article
Engineering, Civil
Michele D'Amato, Raffaele Laguardia, Gino Di Trocchio, Matteo Coltellacci, Rosario Gigliotti
Summary: This study presents a seismic risk analysis of masonry buildings based on the damage data of the 2009 L'Aquila earthquake. Typological loss curves and Expected Annualized Losses (EAL) values are derived from the AeDES forms in the Da.D.O. database. A supplemental approach is proposed to improve the statistical significance of the sample and to include undamaged and not surveyed buildings that experienced low shaking values. The proposed loss curves allow for the economic assessment of the effectiveness of local interventions, such as chains/ring beams, in mitigating seismic risk.
JOURNAL OF EARTHQUAKE ENGINEERING
(2022)
Article
Environmental Sciences
Olga Petrucci, Graziella Emanuela Scarcella, Massimo Conforti
Summary: This paper introduces a GIS-based approach to create a multilevel data system for studying landslide occurrences in small territorial units. The main goal is to collect all available geological, geomorphological, climatic, and landslide data in a structured data management system and analyze them to identify typical landslide scenarios for effective risk management. A case study in Catanzaro, Italy, demonstrated the methodology's use in analyzing landslide risk and revealed the spatial and temporal distribution of landslide occurrences as well as their impact on infrastructure. The proposed GIS platform can be updated and expanded to include additional thematic layers, such as flood events, to support comprehensive landslide risk management.
Article
Engineering, Geological
Dario Peduto, Mariantonia Santoro, Luigi Aceto, Luigi Borrelli, Giovanni Gulla
Summary: This study presents an integrated approach to investigate the kinematic features of a slow-moving landslide affecting Lungro town in Southern Italy, utilizing multi-source data and innovative remote sensing technology to analyze damage distribution and potential causes. By cross-comparing different datasets, a comprehensive outline of the landslide features was derived for effective risk management and the development of advanced geotechnical-structural models.
Article
Architecture
A. Formisano, N. Chieffo
Summary: This research investigates the influence of site effects on the seismic vulnerability of the historical centre of Baranello, Italy. The study reveals that local amplification factors significantly increase the expected damage, indicating the proposed simplified approach can be a useful tool to predict seismic risk in urban areas.
INTERNATIONAL JOURNAL OF ARCHITECTURAL HERITAGE
(2023)
Article
Architecture
Xavier Cardenas-Haro, Nicola Tarque, Leonardo Todisco, Javier Leon
Summary: This paper focuses on the seismic vulnerability analysis of adobe buildings in the Historic Centre of Cuenca, Ecuador. It presents a method that evaluates the seismic behavior of adobe facade walls and identifies the main failure mechanisms. The study provides fragility curves and estimates repair costs after seismic scenarios.
INTERNATIONAL JOURNAL OF ARCHITECTURAL HERITAGE
(2023)
Article
Engineering, Civil
Hong Lv, Zening Wu, Xinjian Guan, Yu Meng
Summary: This study proposed a DPS-HBM model to calculate the flood loss ratio function in cities lacking data, combining the improved analogy principle and Hierarchical Bayesian Model. The model showed good performance in transplantation verification and provided a new approach for establishing flood loss functions in cities with data scarcity.
JOURNAL OF HYDROLOGY
(2021)
Article
Engineering, Geological
A. Rosti, C. Smerzini, R. Paolucci, A. Penna, M. Rota
Summary: This paper explores and validates the use of 3D physics-based numerical simulations (PBS) for seismic fragility studies. The study demonstrates the suitability of PBS for region-specific seismic vulnerability and risk applications through a case study of the 2009 L'Aquila seismic event.
BULLETIN OF EARTHQUAKE ENGINEERING
(2023)
Article
Engineering, Civil
Maria Papathoma-Koehle, Matthias Schloegl, Lea Dosser, Florian Roesch, Marco Borga, Marcel Erlicher, Margreth Keiler, Sven Fuchs
Summary: This study compares the results of vulnerability assessment using vulnerability curves and vulnerability indices. It found that vulnerability curves, while valuable, tend to over-estimate damages, while vulnerability indices provide better understanding of local-scale damage patterns but require more detailed data and further research. Both methods complement each other and provide better insights into the physical vulnerability of buildings exposed to torrential hazards.
JOURNAL OF HYDROLOGY
(2022)
Article
Engineering, Aerospace
K. C. Niraj, Sharad Kumar Gupta, Dericks Praise Shukla
Summary: This paper uses DInSAR and MTInSAR techniques to study surface displacement in the Kotrupi Region. DInSAR accurately measures displacements but is limited by various factors, while MTInSAR uses data from multiple periods to reduce atmospheric disturbances and unwrapping errors. The results show significant deformation in the Kotrupi area after a landslide, with MTInSAR providing more accurate results compared to DInSAR.
ADVANCES IN SPACE RESEARCH
(2022)
Article
Remote Sensing
Xin Yao, Yiping Chen, Donglie Liu, Zhenkai Zhou, Veraldo Liesenberg, Jose Marcato Junior, Jonathan Li
Summary: The study utilized the average-DInSAR method to detect displacements on tableland escarpments and confirmed that these movements were induced by underground coal mining. This method proved to be simple and effective for detecting pre-failure displacements in areas with similar geological conditions, aiding in the formulation of early warning strategies for landslides.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Geosciences, Multidisciplinary
Nicoletta Nappo, Dario Peduto, Marco Polcari, Franz Livio, Maria Francesca Ferrario, Valerio Comerci, Salvatore Stramondo, Alessandro Maria Michetti
Summary: Como historic centre in northern Italy is prone to subside due to thick sediments in the subsoil. The combination of natural causes and human activities has amplified subsidence-induced differential settlements, resulting in damage on the superstructures. Through analyzing hydrogeological and stratigraphic features, in situ damage investigations, and SAR data, it can contribute to the management of Como's architectural and cultural heritage.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2021)
Article
Engineering, Geological
Sergio Lagomarsino, Serena Cattari, Daria Ottonelli
Summary: The macroseismic vulnerability model for unreinforced masonry existing buildings, based on empirical and expert elicitation methods, has been calibrated and improved to produce satisfactory results, playing a significant role in the development of Italian Risk Maps.
BULLETIN OF EARTHQUAKE ENGINEERING
(2021)
Article
Geochemistry & Geophysics
Carlo Noviello, Simona Verde, Virginia Zamparelli, Gianfranco Fornaro, Antonio Pauciullo, Diego Reale, Gianfranco Nicodemo, Settimio Ferlisi, Giovanni Gulla, Dario Peduto
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
(2020)
Article
Environmental Sciences
Danilo Godone, Paolo Allasia, Luigi Borrelli, Giovanni Gulla
Article
Engineering, Geological
Settimio Ferlisi, Antonio Marchese, Dario Peduto
Summary: This study presents the results of a research aimed at quantitatively estimating the risk of slow-moving landslides on a road network, as well as the consequences in damaged conditions. New methodological approaches were successfully tested in a case study in the Campania region of southern Italy.
Article
Engineering, Geological
Dario Peduto, Luisa Oricchio, Gianfranco Nicodemo, Michele Crosetto, Jordi Ripoll, Pere Buxo, Marc Janeras
Summary: The paper introduces a multi-source approach for analyzing ground movements affecting the village of Barbera de la Conca in Spain. By combining various monitoring techniques, the study provides insight into the kinematics of urban slopes and highlights the importance of integrated approaches in planning risk mitigation works.
Article
Geosciences, Multidisciplinary
Loredana Antronico, Francesco De Pascale, Roberto Coscarelli, Giovanni Gulla
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2020)
Article
Engineering, Geological
Dario Peduto, Mariantonia Santoro, Luigi Aceto, Luigi Borrelli, Giovanni Gulla
Summary: This study presents an integrated approach to investigate the kinematic features of a slow-moving landslide affecting Lungro town in Southern Italy, utilizing multi-source data and innovative remote sensing technology to analyze damage distribution and potential causes. By cross-comparing different datasets, a comprehensive outline of the landslide features was derived for effective risk management and the development of advanced geotechnical-structural models.
Article
Chemistry, Multidisciplinary
Gaetano Pecoraro, Gianfranco Nicodemo, Rosa Menichini, Davide Luongo, Dario Peduto, Michele Calvello
Summary: This paper presents a procedure to assess the risk level of stretches of roads exposed to slow-moving landslides at the municipal scale. It proposes an analysis method that combines landslide susceptibility maps, a road-damage database developed using Google Street View images, and ground-displacement measurements from satellite SAR images. The results demonstrate the importance of integrating these different approaches and data to understand the behavior of slow-moving landslides affecting road networks.
APPLIED SCIENCES-BASEL
(2023)
Article
Geosciences, Multidisciplinary
Taorui Zeng, Thomas Glade, Yangyi Xie, Kunlong Yin, Dario Peduto
Summary: This study applies deep learning algorithm and landslide evolution model in long-term warning systems, using the Sifangbei landslide in the Three Gorges reservoir area of China as a test site. The results show that the combination of deep learning and evolution methods can predict landslide displacement and evolution stages, which can contribute to the establishment of long-term warning systems.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2023)
Article
Geosciences, Multidisciplinary
Taorui Zeng, Liyang Wu, Dario Peduto, Thomas Glade, Yuichi S. Hayakawa, Kunlong Yin
Summary: This study aims to define a robust ensemble framework that can be used as a benchmark method for future research comparing different ensemble models. By using decision tree, support vector machine, multi-layer perceptron neural network, random forest, and extreme gradient boosting models, it provides accurate and effective spatial probability predictions of landslide occurrence. Results from the study conducted in Dazhou town, China, show that the stacking based random forest and extreme gradient boosting model has the highest capability in predicting landslide-affected areas.
GEOSCIENCE FRONTIERS
(2023)
Article
Geosciences, Multidisciplinary
Filippo Vecchiotti, Anna Sara Amabile, Salvatore Clemente, Marc Ostermann, Gianfranco Nicodemo, Dario Peduto
Summary: This paper focuses on the study of the Vogelsberg landslide in Austria, using the BFAST and VIM methods to characterize the landslide from the kinematic and geometrical point of view. The analysis of Sentinel-1 differential interferograms and MSBAS algorithms allowed the identification of the seasonality and trend of the landslide, which were correlated with triggering factors such as rain and snow melting. The VIM method reconstructed the depth of the landslide slip surface and evaluated the volumes of material mobilized. The results highlight the importance of in-depth analysis of MT-InSAR data for landslide characterization and hazard assessment.
Article
Geosciences, Multidisciplinary
Dario Peduto, Luca Iervolino, Vito Foresta
Summary: This paper investigates the changes in the physical, mechanical, and hydraulic properties of coarse-grained pyroclastic soils under wildfire-burned and laboratory heating conditions. The findings reveal variations in grain size distribution, chromatic changes, specific gravity, shear strength reduction, and changes in soil-water retention capacity. This knowledge is crucial for analyzing landslide susceptibility on fire-affected slopes under unsaturated conditions.
Article
Engineering, Geological
Settimio Ferlisi, Gianfranco Nicodemo, Dario Peduto, Caterina Negulescu, Gilles Grandjean
GEORISK-ASSESSMENT AND MANAGEMENT OF RISK FOR ENGINEERED SYSTEMS AND GEOHAZARDS
(2020)