[HTML][HTML] Landslide susceptibility map** using machine learning: A literature survey

M Ado, K Amitab, AK Maji, E Jasińska, R Gono… - Remote Sensing, 2022 - mdpi.com
Landslide is a devastating natural disaster, causing loss of life and property. It is likely to
occur more frequently due to increasing urbanization, deforestation, and climate change …

[HTML][HTML] Ensemble learning framework for landslide susceptibility map**: Different basic classifier and ensemble strategy

T Zeng, L Wu, D Peduto, T Glade, YS Hayakawa… - Geoscience …, 2023 - Elsevier
The application of ensemble learning models has been continuously improved in recent
landslide susceptibility research, but most studies have no unified ensemble framework …

Shared blocks-based ensemble deep learning for shallow landslide susceptibility map**

T Kavzoglu, A Teke, EO Yilmaz - Remote Sensing, 2021 - mdpi.com
Natural disaster impact assessment is of the utmost significance for post-disaster recovery,
environmental protection, and hazard mitigation plans. With their recent usage in landslide …

Advanced integration of ensemble learning and MT-InSAR for enhanced slow-moving landslide susceptibility zoning

T Zeng, L Wu, YS Hayakawa, K Yin, L Gui, B **… - Engineering …, 2024 - Elsevier
Abstract The Three Gorges Dam's operation has been recognized as a contributing factor to
slope instability and the reactivation of pre-existing deep-seated landslides in the region …

GIS-based comparative study of the Bayesian network, decision table, radial basis function network and stochastic gradient descent for the spatial prediction of …

J Huang, S Ling, X Wu, R Deng - Land, 2022 - mdpi.com
Landslides frequently occur along the eastern margin of the Tibetan Plateau, which poses a
risk to the construction, maintenance, and transportation of the proposed Dujiangyan city to …

A comparative study of heterogeneous and homogeneous ensemble approaches for landslide susceptibility assessment in the Djebahia region, Algeria

Z Matougui, L Djerbal, R Bahar - Environmental Science and Pollution …, 2024 - Springer
This study aims to compare the performance of ensembles according to their inherent
diversity in the context of landslide susceptibility assessment. Heterogeneous and …

An integrated approach based landslide susceptibility map**: case of Muzaffarabad region, Pakistan

M Basharat, JA Khan, HG Abdo… - … , Natural Hazards and …, 2023 - Taylor & Francis
Landslides result in the devastation of property and loss of lives. This study assesses
landslide susceptibility by employing geographic information systems (GIS) and machine …

Integration of rotation forest and multiboost ensemble methods with forest by penalizing attributes for spatial prediction of landslide susceptible areas

TX Bien, M Iqbal, A Jamal, DD Nguyen… - … Research and Risk …, 2023 - Springer
Landslides are among the most destructive natural hazards causing loss of life, destruction
of infrastrucures and damage to properties, especially in hilly and mountaneous areas all …

Multi‐hazard assessment using machine learning and remote sensing in the North Central region of Vietnam

HD Nguyen, DK Dang, QT Bui, AI Petrisor - Transactions in GIS, 2023 - Wiley Online Library
Natural hazards constitute a diverse category and are unevenly distributed in time and
space. This hinders predictive efforts, leading to significant impacts on human life and …

A new approach based on Balancing Composite Motion Optimization and Deep Neural Networks for spatial prediction of landslides at tropical cyclone areas

TA Tuan, PD Pha, TT Tam, DT Bui - IEEE Access, 2023 - ieeexplore.ieee.org
Landslides are a significant geological hazard that annually cause extensive damage and
loss of life worldwide. Therefore, it is crucial to have reliable prediction models for landslide …