[HTML][HTML] Riverside landslide susceptibility overview: leveraging artificial neural networks and machine learning in accordance with the United Nations (UN) sustainable …

YA Nanehkaran, B Chen, A Cemiloglu, J Chen… - Water, 2023 - mdpi.com
Riverside landslides present a significant geohazard globally, posing threats to
infrastructure and human lives. In line with the United Nations' Sustainable Development …

Modelling landslide susceptibility prediction: a review and construction of semi-supervised imbalanced theory

F Huang, H ** in Iran: a comparison between frequency ratio and weights-of-evidence bivariate statistical models with …
K Khosravi, E Nohani, E Maroufinia, HR Pourghasemi - Natural hazards, 2016 - Springer
Flood is one of the most prevalent natural disasters that frequently occur in the northern part
of Iran reported in hot spots of flood occurrences. The main aim of the current study was to …

Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling

JN Goetz, A Brenning, H Petschko, P Leopold - Computers & geosciences, 2015 - Elsevier
Statistical and now machine learning prediction methods have been gaining popularity in
the field of landslide susceptibility modeling. Particularly, these data driven approaches …

Machine learning ensemble modelling as a tool to improve landslide susceptibility map** reliability

M Di Napoli, F Carotenuto, A Cevasco, P Confuorto… - Landslides, 2020 - Springer
Statistical landslide susceptibility map** is a topic in complete and constant evolution,
especially since the introduction of machine learning (ML) methods. A new methodological …

Flood susceptibility map** using frequency ratio and weights-of-evidence models in the Golastan Province, Iran

O Rahmati, HR Pourghasemi, H Zeinivand - Geocarto International, 2016 - Taylor & Francis
Flood is one of the most devastating natural disasters with socio-economic and
environmental consequences. Thus, comprehensive flood management is essential to …

Enhanced dynamic landslide hazard map** using MT-InSAR method in the Three Gorges Reservoir Area

C Zhou, Y Cao, X Hu, K Yin, Y Wang, F Catani - Landslides, 2022 - Springer
Landslide hazard map** is essential for disaster reduction and mitigation. The hazard
map produced by the spatiotemporal probability analysis is usually static with false-negative …

[HTML][HTML] Optimizing landslide susceptibility map** using machine learning and geospatial techniques

G Agboola, LH Beni, T Elbayoumi, G Thompson - Ecological Informatics, 2024 - Elsevier
Landslides present a substantial risk to human lives, the environment, and infrastructure.
Consequently, it is crucial to highlight the regions prone to future landslides by examining …

Machine learning for landslides prevention: a survey

Z Ma, G Mei, F Piccialli - Neural Computing and Applications, 2021 - Springer
Landslides are one of the most critical categories of natural disasters worldwide and induce
severely destructive outcomes to human life and the overall economic system. To reduce its …