[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 …

Machine learning based landslide susceptibility mapping models and GB-SAR based landslide deformation monitoring systems: Growth and evolution

B Ganesh, S Vincent, S Pathan, SRG Benitez - … Applications: Society and …, 2023 - Elsevier
Ongoing landslides have wreaked havoc in various regions across the globe. This article
presents a study of two forms of landslide monitoring viz; creation of Landslide Susceptibility …

Assessing the imperative of conditioning factor grading in machine learning-based landslide susceptibility modeling: a critical inquiry

T Zeng, B Jin, T Glade, Y Xie, Y Li, Y Zhu, K Yin - Catena, 2024 - Elsevier
Current machine learning approaches to landslide susceptibility modeling often involve
grading conditioning factors, a method characterized by substantial subjectivity and …

Determining the suitable settlement areas in Alanya with GIS-based site selection analyses

S Dogan, C Kilicoglu, H Akinci, H Sevik… - … science and pollution …, 2023 - Springer
Urbanization, which is defined as an irreversible global-scale problem nowadays,
necessitates the foundation of new settlement areas. In general, no sufficient scientific …

Landslide susceptibility mapping in Three Gorges Reservoir area based on GIS and boosting decision tree model

F Miao, F Zhao, Y Wu, L Li, Á Török - Stochastic Environmental Research …, 2023 - Springer
As one of the most destructive geological disasters, a myriad of landslides has revived and
developed in the Three Gorges Reservoir area under the combined action of various …

Machine learning based forest fire susceptibility assessment of Manavgat district (Antalya), Turkey

HA Akıncı, H Akıncı - Earth Science Informatics, 2023 - Springer
This study primarily aims to produce forest fire susceptibility maps for the Manavgat district of
Antalya province in Turkey using different machine learning (ML) techniques. Forest fire …

GIS-based landslide susceptibility mapping using logistic regression, random forest and decision and regression tree models in Chattogram District, Bangladesh

MS Chowdhury, MN Rahman, MS Sheikh, MA Sayeid… - Heliyon, 2024 - cell.com
The frequency of landslides and related economic and environmental damage has
increased in recent decades across the hilly areas of the world, no exception is Bangladesh …

Exploring the uncertainty of landslide susceptibility assessment caused by the number of non–landslides

Q Liu, A Tang, D Huang - Catena, 2023 - Elsevier
Identifying the uncertainty caused by the number of non-landslides is necessary to obtain a
precise landslide susceptibility map. Hence, the objective of this study is to investigate the …

Comparative analysis of tree-based ensemble learning algorithms for landslide susceptibility mapping: A case study in Rize, Turkey

A Yavuz Ozalp, H Akinci, M Zeybek - Water, 2023 - mdpi.com
The Eastern Black Sea Region is regarded as the most prone to landslides in Turkey due to
its geological, geographical, and climatic characteristics. Landslides in this region inflict both …

Essential insights into decision mechanism of landslide susceptibility mapping based on different machine learning models

D Sun, Y Ding, J Zhang, H Wen, Y Wang, J Xu… - Geocarto …, 2022 - Taylor & Francis
This work aims to discuss and compare the inherent essence of different machine learning
algorithms for landslide susceptibility models (LSMs), which is of great significance for …