A comprehensive review of machine learning‐based methods in landslide susceptibility mapping

S Liu, L Wang, W Zhang, Y He, S Pijush - Geological Journal, 2023 - Wiley Online Library
Landslide susceptibility mapping (LSM) has been widely used as an important reference for
development and construction planning to mitigate the potential social‐eco impact caused …

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 …

[HTML][HTML] Spatial landslide susceptibility assessment using machine learning techniques assisted by additional data created with generative adversarial networks

HAH Al-Najjar, B Pradhan - Geoscience Frontiers, 2021 - Elsevier
In recent years, landslide susceptibility mapping has substantially improved with advances
in machine learning. However, there are still challenges remain in landslide mapping due to …

Rainfall induced landslide susceptibility mapping based on Bayesian optimized random forest and gradient boosting decision tree models—A case study of …

G Rong, S Alu, K Li, Y Su, J Zhang, Y Zhang, T Li - Water, 2020 - mdpi.com
Among the most frequent and dangerous natural hazards, landslides often result in huge
casualties and economic losses. Landslide susceptibility mapping (LSM) is an excellent …

Landslide susceptibility zonation of Idukki district using GIS in the aftermath of 2018 Kerala floods and landslides: a comparison of AHP and frequency ratio methods

AV Thomas, S Saha, JH Danumah… - … of Geovisualization and …, 2021 - Springer
This study aims to demarcate landslide susceptible zones using methods of analytical
hierarchy process (AHP) and frequency ratio (FR) to find the most influencing factors and to …

Landslide vulnerability and risk assessment for multi-hazard scenarios using airborne laser scanning data (LiDAR)

WM Abdulwahid, B Pradhan - Landslides, 2017 - Springer
Landslide hazard, vulnerability, and risk-zoning maps are considered in the decision-
making process that involves land use/land cover (LULC) planning in disaster-prone areas …

AI-based rainfall prediction model for debris flows

Y Zhao, X Meng, T Qi, Y Li, G Chen, D Yue, F Qing - Engineering Geology, 2022 - Elsevier
Debris flow prediction based on rainfall monitoring is important for early warning and
disaster risk reduction. Taking a typical debris flow catchment (with debris flows occurring on …

Definition of 3D rainfall thresholds to increase operative landslide early warning system performances

A Rosi, S Segoni, V Canavesi, A Monni, A Gallucci… - Landslides, 2021 - Springer
Intensity–duration rainfall thresholds are commonly used in regional-scale landslide
warning systems. In this manuscript, 3D thresholds are defined also considering the mean …

Artificial intelligence-based fiber optic sensing for soil moisture measurement with different cover conditions

XF Liu, HH Zhu, B Wu, J Li, TX Liu, B Shi - Measurement, 2023 - Elsevier
Actively heated fiber Bragg grating (AH-FBG) can perform quasi-distributed monitoring of
soil water content. However, the analysis method needs to be improved to minimize …

Application of convolutional neural networks based on Bayesian optimization to landslide susceptibility mapping of transmission tower foundation

M Lin, S Teng, G Chen, B Hu - Bulletin of Engineering Geology and the …, 2023 - Springer
The stability of tower foundation slopes is an important factor to maintain the operation of a
power system. However, it is time-consuming and expensive to evaluate tower foundation …