A Hybrid Model Consisting of Supervised and Unsupervised Learning for Landslide Susceptibility Mapping

A Hybrid Model Consisting of Supervised and Unsupervised Learning for Landslide Susceptibility Mapping

Landslides cause huge damage to social economy and human beings every year. Landslide susceptibility mapping (LSM) occupies an important position in land use and risk management. This study is to investigate a hybrid model which makes full use of the advantage of supervised learning model (SLM) and...

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Bibliographic Details
Main Authors: Zhu Liang, Changming Wang, Zhijie Duan, Hailiang Liu, Xiaoyang Liu, Kaleem Ullah Jan Khan
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Remote Sensing
Subjects:
landslide susceptibility
unsupervised machine learning
supervised machine learning
hybrid model
geographic information system
Online Access:https://www.mdpi.com/2072-4292/13/8/1464

Internet

https://www.mdpi.com/2072-4292/13/8/1464

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