Comparison of Machine Learning Methods for Potential Active Landslide Hazards Identification with Multi-Source Data

Comparison of Machine Learning Methods for Potential Active Landslide Hazards Identification with Multi-Source Data

The early identification of potential landslide hazards is of great practical significance for disaster early warning and prevention. The study used different machine learning methods to identify potential active landslides along a 15 km buffer zone on both sides of Jinsha River (Panzhihua-Huize sec...

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Bibliographic Details
Main Authors: Xiangxiang Zheng, Guojin He, Shanshan Wang, Yi Wang, Guizhou Wang, Zhaoying Yang, Junchuan Yu, Ning Wang
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:ISPRS International Journal of Geo-Information
Subjects:
multi-source data
landslide
potential geological hazards
machine learning
Online Access:https://www.mdpi.com/2220-9964/10/4/253

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