河南理工大学学报（自然科学版）2025，Vol.44Issue(1)：57-67,11.DOI:10.16186/j.cnki.1673-9787.2023070010
基于优化MaxEnt模型的怒江州滑坡易发性评价
Evaluation of landslide susceptibility in Nujiang Prefecture based on optimized MaxEnt model
摘要
Abstract
Objectives Nujiang Prefecture is a typical alpine canyon area,frequent landscape geological di-sasters seriously restricts local development.Methods To solve this problem,taking into account the actual situation in Nujiang Prefecture,14 influencing factors such as slope direction and elevation were selected from five aspects of meteorology and hydrology,topography and geo-morphology,stratigraphic lithology,vegetation ecology and human activities to judge the correlation between landslides and each influencing factor,and build an evaluation index system.The MaxEnt model feature combination(FC)and regulariza-tion multi-plier(RM)parameters were optimized,and the sample of the akaike information criterion(AICc),Omission Rate(OR)and AUC(Area Under Curve)value before optimization were compared with that after opitimazation,and the occurrence of landslide hazards based on the optimized MaxEnt model was predictedto realize the landslide susceptibility evaluation in Nujiang Prefecture.Results The optimized MaxEnt model has excellent applicability in predicting landslide susceptibility in the study area(AUC=0.913)).Jackknife method was used to calculate the influence degree of each influencing factor on suscepti-bility.Elevation(S3,23.2%),slope(S9,22.4%),settlement density(S5,14.2%),distance from river(S13,13.7%),distance from road(S4,9.6%)and lithology(S7,8.7%)tare the top six factors,with a cu-mulative contribution of 91.8%.The spatial proportions of extremely high,high,medium and low landslide susceptibility levels were 4.88%,8.96%,18.40%and 67.76%,respectively.The highest proportion of ex-tremely high and high susceptibility areas was found in Lushui City.On the whole,extremely high and high susceptibility areas were mainly distributed in valleys along rivers and roads,while low susceptibility areas were mainly distributed in areas with little human activities and undeveloped river valleys.Conclusions The optimized MaxEnt model is more suitable for landslide sensitivity prediction in Nujiang Prefecture,and the research results can provide reference for disaster prevention,and land use planning in Nujiang Prefecture.关键词
怒江州/最大熵模型/滑坡/易发性Key words
Nujiang Prefecture/maximum entropy model/landslide/susceptibility分类
地质学引用本文复制引用
李益敏,向倩英,邓选伦,冯显杰..基于优化MaxEnt模型的怒江州滑坡易发性评价[J].河南理工大学学报（自然科学版）,2025,44(1):57-67,11.基金项目
国家自然科学基金资助项目(41161070) （41161070）
云南省科技厅-云南大学联合基金重点资助项目(2019FY003017) （2019FY003017）
云南大学大湄公河次区域气候变化研究省创新团队项目(2019HC027) （2019HC027）
中国地质调查局项目(DD20221824) （DD20221824）
