LandslideSusceptibilityMappingData

This project aims to predict geological hazard susceptibility using the LightGBM machine learning model with DEM-related data and other indicators. The GIS database, source code, and CSV data correspond to the paper titled "Low-Time-Cost but Accurate Landslide Susceptibility Mapping: Identifying Triggering Factors with Solely DEM-Derived Indicators, LightGBM Algorithm, and Explainable Machine Learning Techniques." The study area is located in Zhushan County, Shiyan City, Hubei Province, China.本项目旨在结合数字高程模型（Digital Elevation Model，DEM）相关数据与其他指标，采用LightGBM机器学习模型开展地质灾害易发性预测研究。本项目配套的地理信息系统（Geographic Information System，GIS）数据库、源代码及CSV数据，均对应发表于题为《低时间成本但高精度滑坡易发性制图：仅依托DEM衍生指标、LightGBM算法与可解释机器学习技术识别触发因子》的学术论文。本研究的研究区域位于中国湖北省十堰市竹山县。