A review of Statistical approaches used for landslide susceptibility analysis with the help of Remote sensing and GIS technology
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Geo-Informatics, Civil Engineering Department, Graphic Era (Deemed to be University) (Accredited with Grade 'A' by NAAC) Dehradun - 248002, Uttrakhand, India
Centre for Remote Sensing and Geo-Informatics, Sathyabama University
Submission date: 2023-08-19
Final revision date: 2023-10-16
Acceptance date: 2023-10-16
Publication date: 2023-12-08
Corresponding author
Kishan Singh Rawat   

Centre for Remote Sensing and Geo-Informatics, Sathyabama University
Acta Sci. Pol. Formatio Circumiectus 2023;22(3):83-96
  • Landslide Susceptibility Using Statistical Models
One of the most significant environmental risks is landslides. It might happen due to human action or natural occurrence and have significant social, economic, and environmental repercussions. The danger of landslides occurring in a certain area based on regional topographical features is known as landslide susceptibility. Numerous articles evaluating landslide susceptibility have been written since the middle of the seventies utilizing a variety of techniques and methodologies in diverse geographical and environmental situations.To critically review this literature, major factors that are considered for landslide susceptibility, and the models that are used for landslide susceptibility analysis. Then these data are represented in a graphical visualization form.Landslide susceptibility zoning, The goal of the current study, which was undertaken as a review, was to provide a critical analysis of statistical methods used for landslide susceptibility modelling and associated terrain zonation from 2010 to 2023.There has been an increase in the number of publications from 2019 onwards on the topic of landslide susceptibility. In 20.8% of the studies, the FR model and LR model has been chosen as the most popular approach for determining landslide vulnerability. Other then Logistic regression and Frequency ratio model, other models like Fuzzy, WoE, ANN, SVM and RF are also popular for landslide susceptibility. As the technology in the field of GIS&RS is updating day to day and recent policy developments, are significant factors in boosting interest in landslide susceptibility research.
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