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基于斜坡单元的怒江州滑坡易发性研究

Study on Landslide Susceptibility in Nujiang Prefecture Based on Slope Unit
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摘要 开展滑坡易发性分析是制定合理的地质灾害防治规划的基础,对防灾减灾工作具有重要意义。以怒江州为研究区,斜坡单元为评价单元,选取高程、坡度、坡向、NDVI、距河流距离、降雨量、岩性、距断层距离和距道路距离9个因素为评价因子,采用信息量(I)模型、确定性系数(CF)模型以及I-LR、CF-LR耦合模型进行滑坡易发性评价,并对4种模型进行精度验证。结果表明:(1)CF-LR模型中滑坡点落入高、极高易发区占比最大,为88.77%,且滑坡点密度(0.3092)最大,高于I模型(0.2854)与C F模型(0.2776)单一模型;(2)极高、高易发区主要发育于怒江、独龙江、澜沧江和通甸河4条河流一带;中易发区主要分布于研究区东部;低和极低易发区主要分布在研究区的北部、中部以及西部边缘地区;(3)根据基于Sridevi Jadi经验概率法和ROC曲线的结果均表明,CF-LR模型预测精度高于其他3个模型。 Conducting landslide susceptibility analysis is the foundation for formulating reasonable geological disaster prevention and control plan,which is of great significance for disaster prevention and reduction.Taking Nujiang Prefecture as the research area and slope unit as the evaluation unit,nine factors including elevation,slope,slope aspect,NDVI,rainfall,lithology,distance from fault and distance from road were selected as evaluation factors.Information content(I)model,deterministic coefficient(CF)model and I-LR and CF-LR coupling models were used to evaluate landslide susceptibility.The accuracy of the four models was verified.The results showed that:(1)In the CF-LR model,the proportion of landslide points falling into high and extremely high prone areas was the largest,accounting for 88.77%,the density of landslide points(0.3092)was the largest,which was higher than that of I model(0.2854)and CF model(0.2776).(2)The extremely high and highly prone areas mainly developed in the Nujiang River,Dulong River,Lancang River and Tongdian River.The middle prone area was mainly distributed in the eastern part of the study area.The low and very low susceptibility prone area was mainly distributed in the northern,central and western edge of the study area.(3)According to the results based on Sridevi Jadi empirical probability method and ROC curve,the prediction accuracy of CF-LR model was higher than that of the other three models.
作者 蒋文学 李益敏 杨雪 邓选伦 杨一铭 JIANG Wenxue;LI Yimin;YANG Xue;DENG Xuanlun;YANG Yiming(School of Earth Sciences,Yunnan University,Kunming 650500;Yunnan Colleges and Universities Domestic High Score Satellite Remote Sensing Geological Engineering Research Center,Kunming 650500)
出处 《水土保持学报》 CSCD 北大核心 2023年第5期160-167,共8页 Journal of Soil and Water Conservation
基金 云南省科技厅—云南大学联合基金重点项目(2019FY003017) 云南大学湄公河次区域气候变化研究省创新团队项目(2019HC027)。
关键词 斜坡单元 信息量 确定性系数 逻辑回归 易发性 怒江州 slope unit information quantity deterministic coefficient logistic regression susceptibility Nujiang Prefecture
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