Zobrazeno 1 - 10
of 132
pro vyhledávání: '"Samuele Segoni"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-24 (2024)
Abstract In this study, a landslide susceptibility assessment is performed by combining two machine learning regression algorithms (MLRA), such as support vector regression (SVR) and categorical boosting (CatBoost), with two population-based optimiza
Externí odkaz:
https://doaj.org/article/b090d347f4884c15945fda07c3dfb164
Publikováno v:
All Earth, Vol 34, Iss 1, Pp 243-258 (2022)
The increase in population and urbanisation of hilly regions have increased the risk due to landslides. This manuscript presents a data-driven approach with a random forest algorithm to estimate the projected area, length, travel distance, and width
Externí odkaz:
https://doaj.org/article/82357e09cf104387b9b8eafacf337115
Publikováno v:
Environmental Research Letters, Vol 19, Iss 8, p 084023 (2024)
The frequency of occurrence of hydrogeological disasters (HGDs), as well as the persistence of their impacts, are not evenly distributed. Hazardous areas, by definition, are more prone to extreme events, while in densely urbanized regions, the impact
Externí odkaz:
https://doaj.org/article/4d03b82a3d044e9db9fce67c613b2fdf
Publikováno v:
Frontiers in Earth Science, Vol 11 (2023)
Landslide susceptibility assessment using machine learning models is a popular and consolidated approach worldwide. The main constraint of susceptibility maps is that they are not adequate for temporal assessments: they are generated from static pred
Externí odkaz:
https://doaj.org/article/8a8ea86031e140c2b8954aa8f30954bc
Autor:
Samuele Segoni
Publikováno v:
Geosciences, Vol 13, Iss 11, p 322 (2023)
Despite the importance of Earth sciences in addressing the global challenges that humanity is presently facing, attention toward related disciplines has been witnessed to be globally declining at various levels, including education and university tea
Externí odkaz:
https://doaj.org/article/6699bd1a46c8420899da659ae5215cba
Publikováno v:
Data, Vol 8, Iss 10, p 151 (2023)
This dataset collects tabular and geographical information about all hydrogeological disasters (landslides and floods) that occurred in Italy from 2013 to 2022 that caused such severe impacts as to require the declaration of national-level emergencie
Externí odkaz:
https://doaj.org/article/7a0752c8bca44ba39ab78bcea3c0fab6
Autor:
Francesco Caleca, Veronica Tofani, Samuele Segoni, Federico Raspini, Rachele Franceschini, Ascanio Rosi
Publikováno v:
Frontiers in Earth Science, Vol 10 (2022)
Landslides are a worldwide natural hazard that cause more damage and casualties than other hazards. Therefore, social and economic losses can be reduced through a landslide quantitative risk assessment (QRA). In the last two decades, many attempts of
Externí odkaz:
https://doaj.org/article/004e21c44f39488589c8bb7bd8ab7a95
Autor:
Agnese Innocenti, Ascanio Rosi, Veronica Tofani, Veronica Pazzi, Elisa Gargini, Elena Benedetta Masi, Samuele Segoni, Davide Bertolo, Marco Paganone, Nicola Casagli
Publikováno v:
Remote Sensing, Vol 15, Iss 8, p 2159 (2023)
Performing a reliable stability analysis of a landslide slope requires a good understanding of the internal geometries and an accurate characterisation of the geotechnical parameters of the identified strata. Geotechnical models are commonly based on
Externí odkaz:
https://doaj.org/article/0fc8c362abda4eed909c7df3e8ec066b
Autor:
Minu Treesa Abraham, Neelima Satyam, Nakshatram Shreyas, Biswajeet Pradhan, Samuele Segoni, Khairul Nizam Abdul Maulud, Abdullah M. Alamri
Publikováno v:
Geomatics, Natural Hazards & Risk, Vol 12, Iss 1, Pp 540-559 (2021)
This study proposes a regional landslide early warning system for Idukki (India), using a decisional algorithm. The algorithm forecasts the possibility of occurrence of landslide by comparing the rainfall thresholds with the cumulated rainfall values
Externí odkaz:
https://doaj.org/article/c4ee3e87bc88473e99a9799ed9f542e9
Publikováno v:
Water, Vol 14, Iss 21, p 3485 (2022)
Landslide hazard management usually requires time-consuming campaigns of data acquisition, elaboration, and modeling. However, in the post-emergency phase management, time is a factor, and simpler but faster methods of analysis are needed to support
Externí odkaz:
https://doaj.org/article/fbb76c1238c2486abcded05a1afde267