Ensemble Disagreement Active Learning for Spatial Prediction of Shallow Landslide

  • Biswajeet PradhanEmail author
  • Maher Ibrahim Sameen
  • Bahareh Kalantar


In Malaysia, landslides are considered as the most frequent and devastating natural disaster that cause human life and property losses. The spatial prediction of landslides is the basic step required for hazard and risk assessments. Spatial prediction methods of landslides are established and documented in the literature. However, several research directions on this topic need to be developed and explored in depth. The current improvement in computer technology and laser scanning systems provide improved data processing capabilities and topographic datasets, as well as new trends in landslide modeling and methods that can deal with such advanced technologies and datasets.


Support Vector Machine Active Learning Landslide Susceptibility Support Vector Machine Model Landslide Occurrence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Biswajeet Pradhan
    • 1
    Email author
  • Maher Ibrahim Sameen
    • 1
  • Bahareh Kalantar
    • 1
  1. 1.Department of Civil EngineeringUniversity Putra MalaysiaSerdangMalaysia

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