Landslide Hazard Assessment in Highway Areas of Guangxi Using Remote Sensing Data and a Pre-Trained XGBoost Model

Landslide Hazard Assessment in Highway Areas of Guangxi Using Remote Sensing Data and a Pre-Trained XGBoost Model

This study presents a novel method for assessing landslide hazards along highways using remote sensing and machine learning. We extract geospatial features such as slope, aspect, and rainfall over Guangxi, China, and apply an extreme gradient boosting model pre-trained on contiguous United States da...

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Bibliographic Details
Main Authors: Yuze Zhang, Lei Deng, Ying Han, Yunhua Sun, Yu Zang, Minlu Zhou
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Remote Sensing
Subjects:
landslide hazard assessment
remote sensing data
XGBoost algorithm
highway
pre-trained model
Online Access:https://www.mdpi.com/2072-4292/15/13/3350

Internet

https://www.mdpi.com/2072-4292/15/13/3350

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