Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance

An extensive analysis and comparison between different ML techniques using a case study from Algeria is undertaken, noting that tree-based ensemble algorithms achieve excellent results compared to other machine learning algorithms and that the Random Forest algorithm offers robust performance for accurate landslide susceptibility mapping with only a small number of adjustments required before training the model.