基于遥感技术的河谷边坡工程地质环境评价

4区 医学 Tobacco Regulatory Science Pub Date : 2021-11-03 DOI:10.18001/trs.7.6.103
Liangzhuang Ma, Guangming He, Xunshi Wang, Xiangling Zhao, Bing Fan, Shangtao Li
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引用次数: 0

摘要

河谷边坡工程地质环境评价方法在确定地质环境评价指标权重时精度较小,导致地质环境评价结果与河谷边坡工程实际值误差较大。因此,提出了基于遥感技术的河谷边坡工程地质环境评价逆向研究。利用遥感技术构建河谷边坡项目地质环境评价框架,在此基础上,采用德尔菲法初步确定地质环境评价指标,采用聚类分析对评价指标进行筛选,构建项目地质环境评价体系,采用层次分析法计算评价指标权重;并根据工程地质环境评价体系得到相应的遥感影像编号。根据这些数据,使用相应的软件进行预处理,得到工程地质环境遥感数据。在层次分析法的基础上,构建了灰色评价方法,实现了河谷边坡工程地质环境的评价。实验结果表明,与现有方法相比,所提方法的评价误差较小,充分证明了所提方法具有更好的应用性能。
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Geological environment evaluation of river valley slope projects based on remote sensing technology
The method to evaluate the geological environment of river valley slope projects has a small precision in determining the weight of geological environment evaluation index, which leads to a large error between the results of geological environment evaluation and the actual value of river valley slope projects. Therefore, the reverse research of the geological environment evaluation of river valley slope projects based on remote sensing technology is proposed. Remote sensing technology is used to build the projects’ geological environment evaluation framework of river valley slope, on this basis, the Delphi method is used to preliminarily determine the geological environment evaluation index, the cluster analysis is used to screen the evaluation index, the evaluation system of projects’ geological environment is constructed, the AHP method is used to calculate the evaluation index weight, and the corresponding remote sensing image number is obtained according to the projects’ geological environment evaluation system. According to the data, the corresponding software is used to preprocess it, and the remote sensing data of projects’ geological environment is obtained. The grey evaluation method is constructed based on AHP to realize the evaluation of geological environment of river valley slope projects. The experimental results show that compared with the existing methods, the evaluation error of the proposed method is smaller, which fully proves that the application performance of the proposed method is better.
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