A LightGBM-based landslide susceptibility model considering the uncertainty of non-landslide samples

AbstractThe quality of samples is crucial in constructing a data-driven landslide susceptibility model. This article aims to construct a data-driven landslide susceptibility model that takes into account the selection of non-landslide samples. First, 21 conditioning factors are selected, including f...

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Bibliographic Details

Published in:	Geomatics, Natural Hazards & Risk
Main Authors:	Deliang Sun, Xiaoqing Wu, Haijia Wen, Qingyu Gu
Format:	Article
Language:	English
Published:	Taylor & Francis Group 2023-12-01
Subjects:	Information quantity method Light Gradient Boosting Machine (LightGBM) Bayesian optimization box plot diagram SHapley Additive exPlanation (SHAP)
Online Access:	https://www.tandfonline.com/doi/10.1080/19475705.2023.2213807