Landslide Susceptibility Assessment using Skyline Operator and Majority Voting

Özet

Landslide susceptibility assessment is the problem of determining the likelihood of a landslide to occur in a particular area based on the geological and morphological properties of the area. In this study, we propose a method wherein skyline operator is used to model landslides and majority voting is used to assess landslide susceptibility. Experiments conducted on a real life data set showed that the proposed method achieves 83.07% classification accuracy and is superior over most commonly used techniques for landslide susceptibility assessment such as logistic regression, support vector machines and artificial neural network.