基于确定性系数模型与逻辑回归模型耦合的地质灾害易发性评价——以贵州省开阳县为例
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P642.2

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贵州省科技平台及人才团队计划项目(黔科合平台人才[2017]5402号);贵州省科学技术项目(黔科合J字2244);贵州省专业学位研究生课程案例库[黔教合YJSCXJH﹝2018﹞089]


Geohazard Susceptibility Assessment Based on The Integrated model of Certainty Factor Model and Logistic Regression Model:A Case Study in Kaiyang County,Guizhou Province
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    摘要:

    开阳县地质条件复杂,区内地质灾害频发,本文以贵州省开阳县为研究区,选取高程、坡度、地形起伏度、坡向、工程岩组、斜坡结构、断层、水系、归一化植被指数(Normalized Difference Vegetation Index, NDVI) 9个影响因子,基于GIS的栅格数据模型,分别采用CF模型、Logistic回归模型以及两种模型耦合的方法进行地质灾害易发性评价,利用灾害点在各等级下的分布和成功率曲线(Receiver Operating Characteristic, ROC)对三种模型的评价精度进行检验。结果表明,CF模型与Logistic回归模型评价结果总体上一致,但是耦合模型的评价分区结果更加合理,精度更高;因此,本文基于耦合模型的评价结果,将开阳县地质灾害易发性等级分为高易发区、中易发区、低易发区和极低易发区。研究成果可为县级区域地质灾害易发性评价以及提供理论指导和技术参考。

    Abstract:

    Kaiyang county, the geological conditions are complex and the geological hazard happen frequently, is selected as a case study. In this paper, nine factors, including altitude, the slope gradient, relief amplitude, slope direction, the engineering rock group, fault, drainage, the Normalized Difference Vegetation Index (NDVI) and slope structure are considered to assess geohazard susceptibility by using the deterministic coefficient model, logistic regression model and the coupling model, and testing the evaluation accuracy of the models by the distribution of disaster points and the Receiver Operating Characteristic(ROC)curve. The results show that the coupled model are more reasonable and more accurate than the others which are consistent on the whole. Based on the results of the coupling model, therefore, dividing the geological disaster prone areas of Kaiyang into high-prone areas, medium-prone areas, low-prone areas and extremely low-prone areas. The research results can provide theoretical guidance and technical reference for the evaluation of regional geological hazards at the county level.

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覃乙根,杨根兰,江兴元,等. 基于确定性系数模型与逻辑回归模型耦合的地质灾害易发性评价——以贵州省开阳县为例[J]. 科学技术与工程, 2020, 20(1): 96-103.
Qin Yigen, Yang Genlan, Jiang Xingyuan, et al. Geohazard Susceptibility Assessment Based on The Integrated model of Certainty Factor Model and Logistic Regression Model:A Case Study in Kaiyang County, Guizhou Province[J]. Science Technology and Engineering,2020,20(1):96-103.

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历史
  • 收稿日期:2019-05-13
  • 最后修改日期:2019-09-22
  • 录用日期:2019-08-07
  • 在线发布日期: 2020-01-21
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