| 基于InSAR技术的川西高山峡谷区地质灾害早期识别研究——以小金川河流域为例 |
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| 作者姓名： | 唐尧 王立娟 廖军 邓琮 |
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| 作者单位： | 1.四川安信科创科技有限公司,四川 成都 610045;2.四川省安全科学技术研究院,四川 成都 610045;3.四川省地震与地质灾害应急技术保障中心,四川 成都 610045;4.四川交通职业技术学院,四川 成都 611130 |
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| 基金项目： | 四川省科技厅基本科研业务“区域自然灾害综合风险研判与预警方法研究(编号: 2021JDKY0009-1)”和四川省科技厅“川西高山峡谷地区地震与地质灾害态势感知与应急救援(编号: 2020YFS0387)”项目联合资助 |
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| 摘 要： | 采用短基线集时序干涉测量(small baseline subset InSAR,SBAS-InSAR)技术,利用多时相合成孔径雷达数据,对川西高山峡谷区开展地表多时相、长时序形变监测与地质灾害隐患早期识别研究。介绍了时序InSAR方法原理,梳理了数据处理流程,分析了小金川河流域雷达可视性,利用2018-11—2019-12共26期的Sentinel-1A历史存档数据开展了流域内地表形变监测,结果表明: 流域内雷达视线方向的年平均形变速率为-51.12~75.28 mm/a; 依据形变异常分布规律,共判译出4处形变异常区与11处潜在地质灾害隐患点,其中6处隐患点为已知地质灾害点,其余5处隐患点尚不为人知。以隐患点P1(阿娘寨滑坡)为典型案例,开展了长时序监测分析与验证,评估利用InSAR技术开展地质灾害隐患早期识别的可靠性,证明了SBAS-InSAR技术在地质灾害早期识别中的优势及有效性,其技术成果在川西高山峡谷区具有大范围推广应用的潜力。
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| 关 键 词： | SBAS-InSAR 高山峡谷区 地质灾害 小金川河 早期识别 |
| 收稿时间： | 2021-02-26 |
Research on early identification of geological hazards in high mountain and valley areas of western Sichuan Province based on InSAR technology: A case study of Xiaojinchuan River Basin |
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| Authors: | TANG Yao WANG Lijuan LIAO Jun DENG Cong |
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| Institution: | 1. Sichuan Anxin Kechuang Technology Co., Ltd, Sichuan Chengdu 610045, China;2. Sichuan Academy of Safety Science and Technology, Sichuan Chengdu 610045, China;3. Sichuan Earthquake and Geological Disaster Emergency Technical Support Center, Sichuan Chengdu 610045, China;4. Sichuan Vocational and Technical College of Communications, Sichuan Chengdu 611130, China |
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| Abstract: | Short Baseline Set Time-Series Interferometry (Small Baseline Subset InSAR,SBAS-InSAR) technology is used to carry out research on surface multi-temporal and long time-series deformation monitoring and early identification of potential geological hazards in the high mountain and valley areas of western Sichuan, combining with the multi-temporal synthetic aperture radar data. The principle of the time-series InSAR method is introduced and the data processing process is sorted out. Besides, the radar visibility of Xiaojinchuan River Basin is analyzed, and the surface deformation monitoring in the basin is carried out using 26 periods of Sentinel-1A historical archived data from November 2018 to December 2019. The results show that the accumulated deformation in the radar line of sight direction in the basin reaches -51.12—75.28 mm/a. 4 deformation anomalies and 11 potential geological hazards were identified based on the distribution pattern of deformation anomalies, including 6 known geological hazards and 5 unknown geological hazards. Taking P1 (Aniangzhai landslide) as an example, the authors in this paper have carried out the long time series monitoring analysis and verification. The reliability of using InSAR technology for early identification of geological hazards were identified to prove the advantages and effectiveness of SBAS-InSAR technology in early identification of geological hazards, which has the potential for wide-scale application in the high mountain and valley areas of western Sichuan. |
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| Keywords: | SBAS-InSAR high mountain and valley area geological hazard Xiaojinchuan River early identification |
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