Deep learning techniques in extreme weather events: A review
Extreme weather events pose significant challenges, thereby demanding techniques for
accurate analysis and precise forecasting to mitigate its impact. In recent years, deep …
accurate analysis and precise forecasting to mitigate its impact. In recent years, deep …
[HTML][HTML] Speech-recognition in landslide predictive modelling: A case for a next generation early warning system
Traditional landslide early warnings are based on the notion that intensity-duration relations
can be approximated to single precipitation values cumulated over fixed time windows …
can be approximated to single precipitation values cumulated over fixed time windows …
[HTML][HTML] From spatio-temporal landslide susceptibility to landslide risk forecast
The literature on landslide susceptibility is rich with examples that span a wide range of
topics. However, the component that pertains to the extension of the susceptibility framework …
topics. However, the component that pertains to the extension of the susceptibility framework …
Evaluation and prediction of compound geohazards in highly urbanized regions across China's Greater Bay Area
Natural hazards could have devastating consequences globally, making hazard assessment
and spatial prediction crucial for enhancing the resilience of urbanized regions. However …
and spatial prediction crucial for enhancing the resilience of urbanized regions. However …
[HTML][HTML] Rainfall-induced landslide prediction models, part ii: deterministic physical and phenomenologically models
Landslides are frequent hillslope events that may present significant risks to humans and
infrastructure. Researchers have made ongoing efforts to assess the potential danger …
infrastructure. Researchers have made ongoing efforts to assess the potential danger …
Revisiting spatiotemporal evolution process and mechanism of a giant reservoir landslide during weather extremes
An updated comprehension of landslide kinematics is a prerequisite for developing effective
risk assessment and emergency management in the context of climate variability and …
risk assessment and emergency management in the context of climate variability and …
Deep Learning Prediction of Rainfall-driven Debris Flows Considering the Similar Critical Thresholds within Comparable Background Conditions
H Jiang, Q Zou, Y Zhu, Y Li, B Zhou, W Zhou… - … Modelling & Software, 2024 - Elsevier
Abstract Machine learning has been widely applied to predict the spatial or temporal
likelihood of debris flows by leveraging its powerful capability to fit nonlinear features and …
likelihood of debris flows by leveraging its powerful capability to fit nonlinear features and …
[HTML][HTML] Regional-scale spatiotemporal landslide probability assessment through machine learning and potential applications for operational warning systems: a case …
The use of machine learning models for landslide susceptibility mapping is widespread but
limited to spatial prediction. The potential of employing these techniques in spatiotemporal …
limited to spatial prediction. The potential of employing these techniques in spatiotemporal …
Development of Advanced Landslide Investigation Protocol Using Geophysical Methods for Mississippi
Slope failures frequently occur in highway embankments in Mississippi due to the existence
of highly expansive Yazoo Clay. In addition, the Mississippi climate, especially the high …
of highly expansive Yazoo Clay. In addition, the Mississippi climate, especially the high …
Precipitation-induced landslide risk escalation in China's urbanization with high-resolution soil moisture and multi-source precipitation product
K He, X Chen, D Zhao, X Yu, Y Jin, Y Liang - Journal of Hydrology, 2024 - Elsevier
Landslides pose a formidable natural hazard. Accurate risk assessment of landslides
triggered by precipitation heavily relies on hydrometeorological factors, specifically …
triggered by precipitation heavily relies on hydrometeorological factors, specifically …