Random forest-based landslide susceptibility mapping in coastal regions of Artvin, Turkey

H Akinci, C Kilicoglu, S Dogan - ISPRS International Journal of Geo …, 2020 - mdpi.com
Natural disasters such as landslides often occur in the Eastern Black Sea region of Turkey
owing to its geological, topographical, and climatic characteristics. Landslide events occur …

Landslide susceptibility mapping using state-of-the-art machine learning ensembles

BT Pham, VD Vu, R Costache, TV Phong… - Geocarto …, 2022 - Taylor & Francis
This study propose a new approach through which the landslide susceptibility in Quang
Nam (Vietnam) will be estimated using the best model among the following algorithms …

Conditioning factor determination for mapping and prediction of landslide susceptibility using machine learning algorithms

HAH Al-Najjar, B Kalantar, B Pradhan… - Earth resources and …, 2019 - spiedigitallibrary.org
Landslides are type of natural geohazard interfering with many economical and social
activities and causing serious damages on human life. It is ranked as a great disaster …

Landslide susceptibility modeling in a landslide prone area in Mazandarn Province, north of Iran: a comparison between GLM, GAM, MARS, and M-AHP methods

HR Pourghasemi, M Rossi - Theoretical and Applied Climatology, 2017 - Springer
Landslides are identified as one of the most important natural hazards in many areas
throughout the world. The essential purpose of this study is to compare general linear model …

Evaluation of re-sampling methods on performance of machine learning models to predict landslide susceptibility

MB Hassangavyar, HE Damaneh, QB Pham… - Geocarto …, 2022 - Taylor & Francis
This study tests the applicability of three resampling methods (ie bootstrapping, random-
subsampling and cross-validation) for enhancing the performance of eight machine-learning …

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 …

A comparative study of regional landslide susceptibility mapping with multiple machine learning models

Y Wang, L Wang, S Liu, P Liu, Z Zhu… - Geological …, 2023 - Wiley Online Library
The purpose of this study is to utilize three machine learning models—random forest, logistic
regression and extreme gradient boosting—to assess the landslide susceptibility of Wushan …

Prediction of the future landslide susceptibility scenario based on LULC and climate projections

A Tyagi, RK Tiwari, N James - Landslides, 2023 - Springer
Worldwide, landslides are the most frequently occurring disaster that is very destructive and
unpredictable in nature. A total of 850 landslide events were detected during 2005–2020 in …

[HTML][HTML] How do machine learning techniques help in increasing accuracy of landslide susceptibility maps?

Y Achour, HR Pourghasemi - Geoscience Frontiers, 2020 - Elsevier
Landslides are abundant in mountainous regions. They are responsible for substantial
damages and losses in those areas. The A1 Highway, which is an important road in Algeria …

GIS-based evaluation of landslide susceptibility using hybrid computational intelligence models

W Chen, Y Li - Catena, 2020 - Elsevier
Landslides have caused huge economic and human losses in China. Mapping of landslide
susceptibility is an important tool to prevent and control landslide disasters. The purpose of …