华南地质2026，Vol.42Issue(4)：561-572,12.DOI:10.3969/j.issn.2097-0013.2026.04.001
基于机器学习模型的我国滑坡易发性评价方法综述
Review on Landslide Susceptibility Assessment Methods in China Based on Machine Learning Models
摘要
Abstract
[Objective]Landslide susceptibility evaluation is a prerequisite for landslide risk management and control,and it is of great significance for safeguarding the life and property safety of residents in mountainous areas.With powerful capabilities of nonlinear fitting,high-dimensional data mining,and adaptive learning,machine learning models have gradually replaced traditional evaluation methods and become the dominant research method for landslide susceptibility assessment.[Methods]Through literature review,this paper systematically summarizes the research progress of machine learning methods in landslide susceptibility evaluation in China,sorts out the technical workflow of landslide susceptibility evaluation,and focuses on analyzing the core procedures including data preparation and preprocessing,classification and combinatorial optimization of machine learning models,accuracy verification,and susceptibility mapping.[Results]The research results show that machine learning models have been widely applied in domestic landslide susceptibility evaluation,and ensemble models have become one of the mainstream methods with favorable application performance.However,there are still deficiencies in the systematization of data and indicator systems,model interpretability and generalizability,as well as the interdisciplinary application of susceptibility zoning maps when machine learning models are adopted for landslide susceptibility evaluation,which need to be further explored in future studies.This paper can provide a comprehensive theoretical framework and reference basis for the in-depth research and practical application of machine learning models in the field of landslide susceptibility evaluation.关键词
机器学习/滑坡/易发性评价/综述Key words
machine learning/landslide/susceptibility evaluation/review分类
天文与地球科学引用本文复制引用
闵承华,张和军,邬学农..基于机器学习模型的我国滑坡易发性评价方法综述[J].华南地质,2026,42(4):561-572,12.基金项目
兴山县卫生健康局兴山县疾病预防控制中心及实验室能力建设等基坑支护设计项目(A4200002714001058) （A4200002714001058）
