Landslide susceptibility mapping using machine learning algorithms and remote sensing data in a tropical environment
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...
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: | |
Online Access: | http://eprints.utm.my/93344/1/BaharinAhmad2020_LandslideSusceptibilityMappingUsingMachine.pdf |
Similar Items
-
Monitoring and assessment of water level fluctuations of the Lake Urmia and its environmental consequences using multitemporal landsat 7 ETM+ images
by: Nhu, Viet Ha, et al.
Published: (2020) -
New ensemble models for shallow landslide susceptibility modeling in a semi-arid watershed
by: Bui, Dieu Tien, et al.
Published: (2019) -
Landslide detection and susceptibility mapping by airsar data using support vector machine and index of entropy models in Cameron Highlands, Malaysia
by: Dieu, Tien Bui, et al.
Published: (2018) -
A novel ensemble approach of bivariate statistical-based logistic model tree classifier for landslide susceptibility assessment
by: Chen, Wei, et al.
Published: (2018) -
Landslide susceptibility assessment at the Wuning area, China: a comparison between multi-criteria decision making, bivariate statistical and machine learning methods
by: Hong, Haoyuan, et al.
Published: (2019)