2022•Earth Science-Journal of China University of GeosciencesOpen access

基于SBAS-InSAR技术的成汶高速汶川段滑坡易发区选线研究

Peiyuan Liu, Ming Chang, Binbin Wu, Chaopeng Luo, Chao Zhou

Abstract

摘要: 西南山区地质构造复杂导致大量的滑坡分布.为了科学有效的指导西南山区道路选线,提前规避地质灾害高风险,滑坡灾害早期识别必不可少.合成孔径雷达干涉测量(interferometric synthetic aperture radar,InSAR)技术因其全天候、多时相等特点被广泛应用于滑坡灾害的早期识别中.收集了87景Sentinel-1A降轨数据,利用差分干涉测量短基线集时序分析(small baseline subset interferometric synthetic aperture radar,SBAS-InSAR)技术对成汶高速路汶川段进行形变区的识别与分析,结果显示共识别出10处,经野外复核均为处于持续变形中的滑坡,有较好的一致性.根据早期识别结果,对3个比选方案进行综合对比分析,确定方案B为最优选择.SBAS-InSAR技术能有效识别山区公路潜在滑坡隐患区,为山区公路的准确选线提供科学依据. 关键词: 高速公路选线 / 滑坡隐患 / 差分干涉测量短基线集时序分析 / 时序形变分析 / 工程地质

About this research paper

What this paper is about

Why it matters

OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Key concepts: Interferometric synthetic aperture radar, GNSS augmentation, Remote sensing, Synthetic aperture radar, Interferometry, Inverse synthetic aperture radar, Geodesy, Geology