Comparative Performance of Machine Learning Models for Landslide Susceptibility Assessment: Impact of Sampling Strategies in Highway Buffer Zone

Comparative Performance of Machine Learning Models for Landslide Susceptibility Assessment: Impact of Sampling Strategies in Highway Buffer Zone

Landslide susceptibility assessment is critical for hazard mitigation and land-use planning. This study evaluates the impact of two different non-landslide sampling methods—random sampling and sampling constrained by the Global Landslide Hazard Map (GLHM)—on the performance of various machine learni...

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Bibliographic Details
Main Authors: Zhenyu Tang, Shumao Qiu, Haoying Xia, Daming Lin, Mingzhou Bai
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Applied Sciences
Subjects:
landslide susceptibility assessment
SHAP method
machine learning
deep learning
Online Access:https://www.mdpi.com/2076-3417/15/15/8416
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