[HTML][HTML] Landslide susceptibility mapping 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 …

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 …

Spatio-temporal assessment of land use land cover based on trajectories and cellular automata Markov modelling and its impact on land surface temperature of …

A Tariq, F Mumtaz, M Majeed, X Zeng - Environmental Monitoring and …, 2023 - Springer
This research aims to assess the urban growth and impact on land surface temperature
(LST) of Lahore, the second biggest city in Pakistan. In this research, various geographical …

A novel swarm intelligence: cuckoo optimization algorithm (COA) and SailFish optimizer (SFO) in landslide susceptibility assessment

RMA Ikram, AA Dehrashid, B Zhang, Z Chen… - … Research and Risk …, 2023 - Springer
Inherent hazards such as landslides pose a threat to human life and may inflict significant
harm on the surrounding ecosystem. For planning, controlling, and avoiding landslide …

An integrated approach of machine learning, remote sensing, and GIS data for the landslide susceptibility mapping

I Ullah, B Aslam, SHIA Shah, A Tariq, S Qin, M Majeed… - Land, 2022 - mdpi.com
Landslides triggered in mountainous areas can have catastrophic consequences, threaten
human life, and cause billions of dollars in economic losses. Hence, it is imperative to map …

Evaluation efficiency of hybrid deep learning algorithms with neural network decision tree and boosting methods for predicting groundwater potential

Y Chen, W Chen, S Chandra Pal, A Saha… - Geocarto …, 2022 - Taylor & Francis
Delineation of the groundwater's potential zones is a growing phenomenon worldwide due
to the high demand for fresh groundwater. Therefore, the identification of potential …

Uncertainty study of landslide susceptibility prediction considering the different attribute interval numbers of environmental factors and different data-based models

F Huang, Z Ye, SH Jiang, J Huang, Z Chang, J Chen - Catena, 2021 - Elsevier
This paper aims to explore the influences of different attribute interval numbers (AINs) in the
frequency ratio (FR) analysis of continuous environmental factors and the influences of …

Landslide hazard assessment based on Bayesian optimization–support vector machine in Nanping City, China

W Xie, W Nie, P Saffari, LF Robledo, PY Descote… - Natural Hazards, 2021 - Springer
Landslide hazard assessment is critical for preventing and mitigating landslide disasters.
The tuning of hyperparameters is of great importance to achieve better accuracy in a …

GIS-based comparative study of Bayes network, Hoeffding tree and logistic model tree for landslide susceptibility modeling

W Chen, S Zhang - Catena, 2021 - Elsevier
Landslides, one of the most common hazards around the world, have brought about severe
damage to life and property of human. To prevent and mitigate landslides, various models …

Prediction of gully erosion susceptibility mapping using novel ensemble machine learning algorithms

A Arabameri, S Chandra Pal, R Costache… - … , Natural Hazards and …, 2021 - Taylor & Francis
Spatial modelling of gully erosion at regional level is very relevant for local authorities to
establish successful counter-measures and to change land-use planning. This work is …