Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN)

Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN)

Landslide is a natural hazard that results in many economic damages and human losses every year. Numerous researchers have studied landslide susceptibility mapping (LSM), each attempting to improve the accuracy of the final outputs. However, few studies have been published on the training data selec...

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Bibliographic Details
Main Authors: Bahareh Kalantar, Biswajeet Pradhan, Seyed Amir Naghibi, Alireza Motevalli, Shattri Mansor
Format: Article
Language:English
Published: Taylor & Francis Group 2018-01-01
Series:Geomatics, Natural Hazards & Risk
Subjects:
Landslide
SVM
ANN
LR
remote sensing
training data
GIS
Online Access:http://dx.doi.org/10.1080/19475705.2017.1407368

Internet

http://dx.doi.org/10.1080/19475705.2017.1407368

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