黎浩良, 杨莹辉, 许强, 等. 2023. 高寒山区地质灾害季节分区InSAR早期识别研究——以东构造结地区为例[J]. 工程地质学报, 31(3): 780-795. doi: 10.13544/j.cnki.jeg.2022-0556.
    引用本文: 黎浩良, 杨莹辉, 许强, 等. 2023. 高寒山区地质灾害季节分区InSAR早期识别研究——以东构造结地区为例[J]. 工程地质学报, 31(3): 780-795. doi: 10.13544/j.cnki.jeg.2022-0556.
    Li Haoliang, Yang Yinghui, Xu Qiang, et al. 2023. Early geohazard detection in cold mountain region based on InSAR technology with season partition- example of eastern Himalayan syntaxis region[J]. Journal of Engineering Geology, 31(3): 780-795. doi: 10.13544/j.cnki.jeg.2022-0556.
    Citation: Li Haoliang, Yang Yinghui, Xu Qiang, et al. 2023. Early geohazard detection in cold mountain region based on InSAR technology with season partition- example of eastern Himalayan syntaxis region[J]. Journal of Engineering Geology, 31(3): 780-795. doi: 10.13544/j.cnki.jeg.2022-0556.

    高寒山区地质灾害季节分区InSAR早期识别研究——以东构造结地区为例

    EARLY GEOHAZARD DETECTION IN COLD MOUNTAIN REGION BASED ON INSAR TECHNOLOGY WITH SEASON PARTITION-EXAMPLE OF EASTERN HIMALAYAN SYNTAXIS REGION

    • 摘要: 高寒山区显著存在的季节性地貌变化,使得常规InSAR难以维持长时间相干性,不利于上述区域地质灾害的精准早期识别。针对该问题,本文提出并发展了一种利用InSAR季节相干性的高寒山区地质灾害早期识别方法。其基本思路为:首先获取研究区域InSAR时序干涉图与相干系数图,依据InSAR相干性变化趋势,将每年划分为夏季时段、过渡时段和冬季时段,并依据过渡时段InSAR相干性将其进一步纳入到夏季时段或冬季时段;分别对夏季时段和冬季时段InSAR干涉对开展Stacking-InSAR处理,并引入部分干涉质量较好的长时间基线InSAR干涉对;最终综合利用获取的夏季和冬季时段Stacking-InSAR成果,开展区域地质灾害的精准早期识别工作。本文以高寒高植被覆盖的东构造结地区为实验对象,利用本文发展的新方法开展了区域地质灾害的早期识别工作。结果显示,利用季节分区Stacking-InSAR进行区域地质灾害识别,冬夏时段识别灾害的重复率低于16%,表明上述区域不同时节地质灾害类型存在明显差异;进一步与常规全干涉Stacking-InSAR灾害识别成果对比发现,新方法识别灾害数量增加了28%。研究表明,发展新方法可更精准识别高寒山区地质灾害,并有效提高灾害识别率,为此类地区的地质灾害早期识别和预警预防提供了一种新思路和新方法,也为高寒山区地质灾害的防灾减灾提供了重要的技术支撑。

       

      Abstract: The significant seasonal changing of surface coverage makes it is difficult to maintain the InSAR interferometric coherence with a long temporal baseline in the cold mountain region. It causes a negative effect in the identification of geohazard in such region. Here, we propose a geohazard identification method based on InSAR seasonal coherence variation in the cold mountain region. First, the InSAR time series interferograms and coherence are obtained. Then, according to the InSAR coherence variation, each year is divided into summer season, transition season and winter season. Second, according to the characteristic of the coherence of the transition season interferometric pairs, they can be added into summer season or winter season groups. Then, the time series InSAR deformation in summer season and winter season are extracted based on Stacking-InSAR technique, respectively. It is noted that some long temporal baseline InSAR interferometric pairs with a high coherence also are introduced into InSAR time series analysis. Finally, the Stacking-InSAR deformation in summer season and winter season are jointly used to detect the geohazard in the cold mountain region. In this study, the Eastern Himalayan Syntaxis is set as study area, and the proposed method is adopted to detect the geohazard in this area. And it is found that only 16% geohazards can be identified by both the summer and winter InSAR results, which indicates that different geohazards in summer and winter. In addition, the proposed method detects more 28% geohazards than the result of traditional Stacking-InSAR technology using all interferograms. Therefore, the proposed method can accurately and effectively detect geohazard in the cold mountain region. It can provide a help to the reduction and prevention of geohazard in such region.

       

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