Early Warning Systems (EWS) are efficient tools for preventing and mitigating the risks associated to landslides occurrence. In this paper, an integrated methodology for landslides’ analysis is presented and described. Such methodology is aimed at the creation of early warning systems and is based on the integration between a modern monitoring technique, such as the Ground-Based Interferometric Synthetic Aperture Radar (GBInSAR), along with advanced numerical modelling. The paper also shows the application of the proposed methodology to the case study of a rockslide in central Italy. The integration between monitoring data, thanks to a GBInSAR survey and advanced numerical simulations with the combined Finite-Discrete Elements Method (FDEM), allowed for the definition of a set of surface velocity thresholds to be adopted for the long-term monitoring of the landslide and for the creation of an effective EWS.
An integrated methodology for landslides’ early warning systems / Barla, Marco; Antolini, Francesco. - In: LANDSLIDES. - ISSN 1612-510X. - STAMPA. - (2016). [10.1007/s10346-015-0563-8]
An integrated methodology for landslides’ early warning systems
BARLA, MARCO;ANTOLINI, FRANCESCO
2016
Abstract
Early Warning Systems (EWS) are efficient tools for preventing and mitigating the risks associated to landslides occurrence. In this paper, an integrated methodology for landslides’ analysis is presented and described. Such methodology is aimed at the creation of early warning systems and is based on the integration between a modern monitoring technique, such as the Ground-Based Interferometric Synthetic Aperture Radar (GBInSAR), along with advanced numerical modelling. The paper also shows the application of the proposed methodology to the case study of a rockslide in central Italy. The integration between monitoring data, thanks to a GBInSAR survey and advanced numerical simulations with the combined Finite-Discrete Elements Method (FDEM), allowed for the definition of a set of surface velocity thresholds to be adopted for the long-term monitoring of the landslide and for the creation of an effective EWS.Pubblicazioni consigliate
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https://hdl.handle.net/11583/2601567
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