Identification of large-scale landslide hazards based on differences of geological structure prone to sliding and multiple-source data in karst mountainous areas
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摘要: 岩溶山区地质环境复杂且脆弱,重特大崩滑地质灾害时有发生。如果对岩溶山区的地质环境认知不准,将直接导致对灾害识别能力不足。文章围绕岩溶山区裸露型岩溶陡崖、复合岩组型斜坡以及非裸露型岩溶斜坡3类基本易滑地质结构差异,探讨多源数据条件下更具适用性的识别探测方法。对于空间影响面积小的厚层岩溶陡崖结构,星-地组合识别方法更加适用,基于GNSS的识别探测方式可在获得动态变形趋势基础上,对可能发生的失稳模式进行初步预判,同时可对InSAR解译的地表位移进行矢量化校正,有利于提高对具有相同或相近SAR数据条件地区的灾害识别程度。对于具有较大空间影响面积的斜坡区域,可优先选用基于InSAR的遥感技术来获取地表变形结果,对于有致灾风险的大变形区还可结合易滑地质结构及外部影响因素对其可能失稳模式进行预判或反演分析。任何灾害识别方式都有其局限性,在实践中可根据不同地质结构特征与灾害类型特点,通过多源、多维度监测来构建综合识别体系,探索更具适用性的识别探测与数据分析新思路。Abstract: The geological environment in karst mountainous areas of southwest China is complex and fragile, where large landslide hazards are common. The inaccurate geological cognition of karst mountainous area will directly lead to the lack of disaster identification ability. Based on the three kinds of main geological structures, exposed karst cliffs, complex rock formations and non-exposed karst slopes, which are prone to sliding in the karst mountainous areas of China, more applicable identification and detection methods of multiple-source data are discussed in this paper. For the karst cliff composed by thick layers of carbonate with small spatial impact area, the satellite-ground combination identification method is more applicable. The trend of dynamic deformation can be measured with the GNSS detection method, then the possible failure modes can be prejudged preliminarily. At the same time, it can help to make vector correction to the displacement from InSAR interpretation, to improve the degree of identification of the areas with the same or similar SAR observation conditions. For geological hazards with large spatial impact areas, the remote sensing technology based on InSAR is preferred to obtain surface deformation. For large deformation areas with high risk, the possible initiation mechanism can be studied or inversion analyzed in combination with the structure models liable to slide and external influence factors. The displacement identification method focuses on the increment of surface deformation is not applicable to the sudden landslides without enough early deformation. In view of such potential geological hazards, a comprehensive identification system can be constructed through multiple-source and multiple-dimensional monitoring, so as to explore a new way of landslide hazards identification and data analysis.
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