Spatial implementation of frequency ratio, statistical index and index of entropy models for landslide susceptibility mapping in Al-Balouta river basin, Tartous …

HG Abdo, H Almohamad, AA Al Dughairi, SA Ali… - Geoscience Letters, 2022 - Springer
Landslide vulnerability prediction maps are among the most important tools for managing
natural hazards associated with slope stability in river basins that affect ecosystems …

Machine learning and remote sensing application for extreme climate evaluation: example of flood susceptibility in the Hue Province, Central Vietnam Region

MC Ha, PL Vu, HD Nguyen, TP Hoang, DD Dang… - Water, 2022 - mdpi.com
Floods are the most frequent natural hazard globally and incidences have been increasing
in recent years as a result of human activity and global warming, making significant impacts …

Landslide susceptibility assessment using statistical and machine learning techniques: A case study in the upper reaches of the Minjiang River, southwestern China

S Ling, S Zhao, J Huang, X Zhang - Frontiers in Earth Science, 2022 - frontiersin.org
Landslides have frequently occurred in deeply incised valleys in the upper reaches of the
Minjiang River. Long-term interactions between rock uplift and river undercutting developed …

Integrating deep learning neural network and M5P with conventional statistical models for landslide susceptibility modelling

S Saha, A Saha, M Santosh, B Kundu, R Sarkar… - Bulletin of Engineering …, 2024 - Springer
Landslides are among the devastating geological hazards that cause immense damage in
hilly regions. The Indian Himalayan region is plagued by numerous major landslides. Here …

An assessment of negative samples and model structures in landslide susceptibility characterization based on Bayesian network models

S Khabiri, MM Crawford, HJ Koch, WC Haneberg… - Remote Sensing, 2023 - mdpi.com
Landslide susceptibility mapping (LSM) characterizes landslide potential, which is essential
for assessing landslide risk and developing mitigation strategies. Despite the significant …

Landslide susceptibility assessment in multiple urban slope settings with a landslide inventory augmented by InSAR techniques

L Chen, P Ma, C Yu, Y Zheng, Q Zhu, Y Ding - Engineering Geology, 2023 - Elsevier
Landslide susceptibility assessment (LSA) evaluates the likelihood of landslide occurrences
and can help mitigate and prevent landslide risks. Recently, there have been vast …

Assessing landslide susceptibility based on hybrid multilayer perceptron with ensemble learning

H Hong - Bulletin of Engineering Geology and the Environment, 2023 - Springer
Landslides have brought about serious human and economic losses worldwide. Modeling
landslide susceptibility is an important technology to avoid the loss caused by landslide …

Modelling and mapping of landslide susceptibility regulating potential ecosystem service loss: an experimental research in Saudi Arabia

J Mallick, S Alqadhi, S Talukdar, SK Sarkar… - Geocarto …, 2022 - Taylor & Francis
The study aims to create a novel artificial intelligence model-based landslide susceptibility
model (LSM) at Aqabat, Saudi Arabia. For LSM, a combination of bagging, dagging, random …

Prediction of river suspended sediment load using machine learning models and geo-morphometric parameters

M Asadi, A Fathzadeh, R Kerry… - Arabian journal of …, 2021 - Springer
Estimating sediment load of rivers is one of the major problems in river engineering that has
been using various data mining algorithms and variables. It is desirable to obtain accurate …

Integrating Machine Learning Ensembles for Landslide Susceptibility Mapping in Northern Pakistan

N Ali, J Chen, X Fu, R Ali, MA Hussain, H Daud… - Remote Sensing, 2024 - mdpi.com
Natural disasters, notably landslides, pose significant threats to communities and
infrastructure. Landslide susceptibility mapping (LSM) has been globally deemed as an …