长江科学院院报 ›› 2020, Vol. 37 ›› Issue (9): 50-56.DOI: 10.11988/ckyyb.20190726

• 工程安全与灾害防治 • 上一篇    下一篇

基于加权信息量模型的临潼区滑坡易发性评价

杨盼盼, 王念秦, 郭有金, 马啸   

  1. 西安科技大学 地质与环境学院,西安 710054
  • 收稿日期:2019-06-23 修回日期:2019-08-12 出版日期:2020-09-01 发布日期:2020-09-25
  • 作者简介:杨盼盼(1990-),女,甘肃定西人,博士研究生,主要从事地质环境演变与地质灾害防治等方面的研究。E-mail:xustypp@163.com
  • 基金资助:
    国家自然科学基金项目(41572287);陕西省科技统筹创新工程计划项目(2016KTCL03-19);陕西省煤田地质局科技计划项目(JB2014-4)

Assessment of Landslide Susceptibility in Lintong District Using Weighted Information Value Model

YANG Pan-pan, WANG Nian-qin, GUO You-jin, MA Xiao   

  1. College of Geology and Environment, Xi'an University of Science and Technology, Xi'an 710054, China
  • Received:2019-06-23 Revised:2019-08-12 Online:2020-09-01 Published:2020-09-25

摘要: 为提高滑坡易发性评价的准确性和精度,结合随机森林(FR)模型和信息量(IV)模型2种方法,提出一种新的加权信息量(WIV)模型。以西安市临潼区为研究区,基于野外调查和因素相关性分析,选取坡度、坡向、高程、曲率、地形起伏、岩土体类型、降雨量、断层、水系和道路10个影响因子,以全区72个滑坡灾害点为样本数据,分别采用FR模型、IV模型和WIV模型对研究区开展滑坡易发性评价。结果表明:WIV模型训练样本的成功率和预测率比FR模型分别高4.9%和1.9%,比IV模型分别高17.80%和4.70%;滑坡灾害点高易发区和极高易发区多分布在断层、河流及道路集中区域,且其滑坡灾害点比例WIV模型比IV模型、FR模型分别提高6.37%和4.45%;WIV模型易发性评价分区结果与研究区实际情况相近。研究成果可为防灾减灾工程提供科学依据。

关键词: 滑坡易发性, 评价因子, 随机森林模型, 信息量模型, 加权信息量模型, 西安市临潼区

Abstract: A weighted information value (WIV) model integrating random forest (FR) model and information value (IV) model is proposed in an attempt to improve the precision and accuracy of landslide susceptibility assessment. Lintong District of Xi'an City is taken as the research area. According to field survey and factor correlation analysis, ten factors including slope gradient, slope aspect, elevation, curvature, topographic relief, rock and soil type, rainfall, fault, water system, and road are selected as influence factors for the assessment. With 72 landslide hazard points as sample data, the landslide susceptibility is assessed using RF model, IV model and WIV model, respectively. Results demonstrate that the success rate and prediction rate of WIV model training samples are higher than those of FR model by 4.90% and 1.90%, respectively, and higher than those of IV model by 7.80% and 4.70%, respectively. Highly and extremely highly susceptible areas are mainly distributed in faults, rivers and roads. The rate of landslide hazard points in highly and extremely highly susceptible areas by WIV model is 6.37% and 4.44% higher than that by IV model and FR model, respectively. In conclusion, the results of WIV model are consistent with the actual situation of the research area.

Key words: landslide susceptibility, assessment factor, random forest model, information value model, weighted information value model, Lintong District of Xi'an City

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