Identification of large-scale landslide hazards based on differences of geological structure prone to sliding and multiple-source data in karst mountainous areas

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.