Application of a novel hybrid machine learning algorithm in shallow landslide susceptibility mapping in a mountainous area

• Main Authors: Ghasemian, Bahareh, Shahabi, Himan, Shirzadi, Ataollah, Al-Ansari, Nadhir, Jaafari, Abolfazl, Geertsema, Marten, M. Melesse, Assefa, K. Singh, Sushant, Ahmad, Anuar
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2022
• Subjects: G70.39-70.6 Remote sensing
• Online Access: http://eprints.utm.my/104043/1/AnuarAhmad2022_ApplicationofaNovelHybridMachineLearning.pdf; http://eprints.utm.my/104043/; http://dx.doi.org/10.3389/fenvs.2022.897254

Landslides can be a major challenge in mountainous areas that are influenced by climate and landscape changes. In this study, we propose a hybrid machine learning model based on a rotation forest (RoF) meta classifier and a random forest (RF) decision tree classifier called RoFRF for landslide predi...