[HTML][HTML] Deep learning for geological hazards analysis: Data, models, applications, and opportunities

Z Ma, G Mei - Earth-Science Reviews, 2021 - Elsevier
As natural disasters are induced by geodynamic activities or abnormal changes in the
environment, geological hazards tend to wreak havoc on the environment and human …

[HTML][HTML] Geographical landslide early warning systems

F Guzzetti, SL Gariano, S Peruccacci, MT Brunetti… - Earth-Science …, 2020 - Elsevier
The design, implementation, management, and verification of landslide early warning
systems (LEWSs) are gaining increasing attention in the literature and among government …

Deep learning forecast of rainfall-induced shallow landslides

AC Mondini, F Guzzetti, M Melillo - Nature communications, 2023 - nature.com
Rainfall triggered landslides occur in all mountain ranges posing threats to people and the
environment. Given the projected climate changes, the risk posed by landslides is expected …

A review of the recent literature on rainfall thresholds for landslide occurrence

S Segoni, L Piciullo, SL Gariano - Landslides, 2018 - Springer
The topic of rainfall thresholds for landslide occurrence was thoroughly investigated,
producing abundance of case studies at different scales of analysis and several technical …

Regional early warning model for rainfall induced landslide based on slope unit in Chongqing, China

S Liu, J Du, K Yin, C Zhou, C Huang, J Jiang, J Yu - Engineering Geology, 2024 - Elsevier
Recent advances in the diversity and systematization of design methods and real-time data
have led to a general elevation in spatio-temporal accuracy for regional landslide early …

Hydrogeomorphic response to extreme rainfall in headwater systems: Flash floods and debris flows

M Borga, M Stoffel, L Marchi, F Marra, M Jakob - Journal of Hydrology, 2014 - Elsevier
Flash floods and debris flows develop at space and time scales that conventional
observation systems for rainfall, streamflow and sediment discharge are not able to monitor …

Debris-flow monitoring and warning: Review and examples

M Hürlimann, V Coviello, C Bel, X Guo, M Berti… - Earth-Science …, 2019 - Elsevier
Debris flows represent one of the most dangerous types of mass movements, because of
their high velocities, large impact forces and long runout distances. This review describes …

Soil moisture information can improve shallow landslide forecasting using the hydrometeorological threshold approach

P Marino, DJ Peres, A Cancelliere, R Greco… - Landslides, 2020 - Springer
Empirical thresholds indicating the meteorological conditions leading to shallow landslide
triggering are one of the most important components of landslide early warning systems …

[HTML][HTML] Urban pluvial flooding prediction by machine learning approaches–a case study of Shenzhen city, China

Q Ke, X Tian, J Bricker, Z Tian, G Guan, H Cai… - Advances in Water …, 2020 - Elsevier
Urban pluvial flooding is a threatening natural hazard in urban areas all over the world,
especially in recent years given its increasing frequency of occurrence. In order to prevent …

[HTML][HTML] A tool for the automatic calculation of rainfall thresholds for landslide occurrence

M Melillo, MT Brunetti, S Peruccacci, SL Gariano… - … Modelling & Software, 2018 - Elsevier
Empirical rainfall thresholds are commonly used to forecast landslide occurrence in wide
areas. Thresholds are affected by several uncertainties related to the rainfall and the …