Landslide susceptibility mapping using machine learning algorithms and remote sensing data in a tropical environment

• Main Authors: Nhu, Viet Ha, Mohammadi, Ayub, Shahabi, Himan, Ahmad, Baharin, Al-Ansari, Nadhir, Shirzadi, Ataollah, Clague, John J., Jaafari, Abolfazl, Chen, Wei, Nguyen, Hoang
• Format: Article
• Language: English
• Published: MDPI 2020
• Subjects: NA Architecture
• Online Access: http://eprints.utm.my/id/eprint/93344/1/BaharinAhmad2020_LandslideSusceptibilityMappingUsingMachine.pdf; http://eprints.utm.my/id/eprint/93344/; http://dx.doi.org/10.3390/ijerph17144933

We used AdaBoost (AB), alternating decision tree (ADTree), and their combination as an ensemble model (AB-ADTree) to spatially predict landslides in the Cameron Highlands, Malaysia. The models were trained with a database of 152 landslides compiled using Synthetic Aperture Radar Interferometry, Goog...