Comparison of a logistic regression and Naïve Bayes classifier in landslide susceptibility assessments: The influence of models complexity and training dataset size

P Tsangaratos, I Ilia - Catena, 2016 - Elsevier
The main objective of the present study was to compare the performance of a classifier that
implements the Logistic Regression and a classifier that employs a Naïve Bayes algorithm in …

A novel ensemble approach for landslide susceptibility mapping (LSM) in Darjeeling and Kalimpong districts, West Bengal, India

J Roy, S Saha, A Arabameri, T Blaschke, DT Bui - Remote Sensing, 2019 - mdpi.com
Landslides are among the most harmful natural hazards for human beings. This study aims
to delineate landslide hazard zones in the Darjeeling and Kalimpong districts of West …

Application of the analytical hierarchy process (AHP) for landslide susceptibility mapping: A case study from the Tinau watershed, west Nepal

P Kayastha, MR Dhital, F De Smedt - Computers & Geosciences, 2013 - Elsevier
Landslide problems are abundant in the mountainous areas of Nepal due to a unique
combination of adverse geological conditions, abundant rainfall and anthropogenic factors …

Landslide susceptibility mapping by binary logistic regression, analytical hierarchy process, and statistical index models and assessment of their performances

HR Pourghasemi, HR Moradi, SM Fatemi Aghda - Natural hazards, 2013 - Springer
The current research presents a detailed landslide susceptibility mapping study by binary
logistic regression, analytical hierarchy process, and statistical index models and an …

Exploring effectiveness of frequency ratio and support vector machine models in storm surge flood susceptibility assessment: A study of Sundarban Biosphere …

M Sahana, S Rehman, H Sajjad, H Hong - Catena, 2020 - Elsevier
Abstract The Sundarban Biosphere Reserve (SBR), which is one of the important coastal
regions of India, is vulnerable to storm surge hazards. It experiences storm surge flood of …

Evaluating GIS-based multiple statistical models and data mining for earthquake and rainfall-induced landslide susceptibility using the LiDAR DEM

J Dou, AP Yunus, D Tien Bui, M Sahana, CW Chen… - Remote Sensing, 2019 - mdpi.com
Landslides are typically triggered by earthquakes or rainfall occasionally a rainfall event
followed by an earthquake or vice versa. Yet, most of the works presented in the past …

Landslide detection and susceptibility mapping by airsar data using support vector machine and index of entropy models in cameron highlands, malaysia

D Tien Bui, H Shahabi, A Shirzadi, K Chapi… - Remote Sensing, 2018 - mdpi.com
Since landslide detection using the combination of AIRSAR data and GIS-based
susceptibility mapping has been rarely conducted in tropical environments, the aim of this …

Spatial prediction of landslide susceptibility by combining evidential belief function, logistic regression and logistic model tree

W Chen, X Zhao, H Shahabi, A Shirzadi… - Geocarto …, 2019 - Taylor & Francis
In this study, we introduced novel hybrid of evidence believe function (EBF) with logistic
regression (EBF-LR) and logistic model tree (EBF-LMT) for landslide susceptibility …

Landslide susceptibility assessment at the Wuning area, China: A comparison between multi-criteria decision making, bivariate statistical and machine learning …

H Hong, H Shahabi, A Shirzadi, W Chen, K Chapi… - Natural Hazards, 2019 - Springer
The aim of this research is to investigate multi-criteria decision making [spatial multi-criteria
evaluation (SMCE)], bivariate statistical methods [frequency ratio (FR), index of entropy …

Assessing LNRF, FR, and AHP models in landslide susceptibility mapping index: a comparative study of Nojian watershed in Lorestan province, Iran

M Abedini, S Tulabi - Environmental earth sciences, 2018 - Springer
Landslides and slope instabilities are major risks for human activities which often lead to
economic losses and human fatalities all over the world. The main purpose of this study is to …