北京师范大学学报（自然科学版）2025，Vol.61Issue(4)：551-562,12.DOI:10.12202/j.0476-0301.2024267
融合时序InSAR形变和LightGBM的滑坡易发性评价
Integrating time-series InSAR deformation and LightGBM for landslide susceptibility assessment
摘要
Abstract
Existing landslide susceptibility models typically rely on static predisposing factors,to effectively capture the relationship between landslides and geographic variables but neglecting dynamic features like surface deformation.Time-series interferometric synthetic aperture radar(TS-InSAR)is applied in this study to obtain line-of-sight deformation rates in Yunyang county,breaking into vertical and slope-direction components as InSAR factors.These are combined with static predisposing factors to develop a LightGBM model for landslide susceptibility.Shapley additive explanations(SHAP)algorithm is used to identify key influencing factors.It is found that 28.15％of Yunyang is moderately susceptible,with high and very high susceptibility areas concentrated along the Yangtze River,in line with historical landslide distributions.SHAP analysis highlights elevation,land use,and proximity to rivers as primary factors.Incorporation of InSAR data improves model AUC from 0.819 5 to 0.830 2,with enhanced landslide susceptibility prediction.This study confirms the significant role of time-series InSAR deformation data to improve susceptibility assessments.关键词
时序InSAR/地表动态形变/LightGBM算法/SHAP/滑坡易发性评价Key words
time-series InSAR/surface dynamic deformation/LightGBM algorithm/SHAP/landslide susceptibility assessment分类
天文与地球科学引用本文复制引用
朱颖,李长明,张强,文海家,冀琴,朱星,张廷斌,孙德亮,唐云辉,赵建军..融合时序InSAR形变和LightGBM的滑坡易发性评价[J].北京师范大学学报（自然科学版）,2025,61(4):551-562,12.基金项目
国家重点研发计划资助项目(2021YFB3901400) （2021YFB3901400）
重庆市自然科学基金资助项目(CSTB2023NSC0-MSX0618,CSTB2023NSCQ-MSX0990) （CSTB2023NSC0-MSX0618,CSTB2023NSCQ-MSX0990）
重庆师范大学科学基金资助项目(23XWB032) （23XWB032）
