ISSN 1009-6248CN 61-1149/P 双月刊

主管单位:中国地质调查局

主办单位:中国地质调查局西安地质调查中心
中国地质学会

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    基于多源时序InSAR技术的滑坡隐患早期识别

    Early Identification of Potential Dangers of Loess Landslide Based on Multi-Source and Time Series InSAR

    • 摘要: 中国山区滑坡灾害频发且分布广泛,尤其是地处高位的隐蔽型灾害及隐患,传统的技术对其识别监测效果较差。InSAR技术作为一种基于广域面范围的对地观测技术,可以快速获取地表大范围的微小缓慢形变,相对于点监测技术来说,具有先天的优势,在滑坡隐患识别工作中起到了重要的作用。笔者以新疆叶城为研究区,收集10景ALOS-2数据和98景Sentinel-1数据,基于SBAS-InSAR技术对滑坡地质灾害及隐患进行识别与监测。基于形变结果,结合光学遥感影像,建立遥感解译标准,共解译出22处有形变特征的滑坡隐患,进行了野外验证,确定滑坡隐患点20处,识别准确率达91%。基于形变特征和野外验证结果对两处典型隐患点的时间序列形变情况及形变原因进行了详细的分析。结果显示,两处滑坡整体呈现缓慢蠕变的状态,但遇降雨或融雪可能会发生加速变形。研究表明,多源InSAR技术可以有效的识别叶城地区的滑坡隐患,为后续的滑坡灾害防治提供了可靠的数据支撑。

       

      Abstract: Landslide disasters are frequent and widespread in mountainous areas of China, especially those potential disasters and dangers at high altitudes, where traditional technologies are less effective in identification and monitoring. Interferometric Synthetic Aperture Radar (InSAR) technology, as a ground observation technique based on a wide-area surface, can rapidly acquire minor and slow ground deformations over large areas, offering innate advantages over point monitoring techniques and playing a significant role in the identification of landslide risks. This study focuses on the Yecheng area of Xinjiang, utilizing 10 scenes of ALOS-2 data and 98 scenes of Sentinel-1 data. Based on the SBAS-InSAR method, identification and monitoring of geological hazards and potential landslide risks were conducted. By interpreting the deformation results in conjunction with optical remote sensing images, a remote sensing interpretation standard was established, revealing 22 potential landslide sites with deformation characteristics. Field verification confirmed 20 of these sites, achieving an identification accuracy rate of 91%. Detailed analysis of the time series deformation and causes at two typical risk sites based on deformation characteristics and field verification results showed a general trend of slow creep, with the potential for accelerated deformation in the event of rainfall or snowmelt. The results indicate that multi-source InSAR technology effectively identifies potential landslide risks in the Yecheng area, providing reliable data support for subsequent landslide disaster prevention and control measures.

       

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