No abstract

Multibeam echo-sounding and seismic data were obtained during three geophysical surveys by Guangzhou Marine Geological Survey (GMGS) on the north-eastern slope of the South China Sea (SCS). Nineteen seafloor domes and numerous elongated pockmarks were distinguished in the study area. The seafloor domes vary on number of summits, shape, and spatial interrelation, based on which they were classified into four types which are single-summit, double-summits, elongated, and connected. Bottom simulating reflectors and blanking zone underneath were observed in the seismic profiles, indicating the potential existence of gas hydrate and free gas. Multiple faults and diapirs exist beneath the seafloor domes and pockmarks, which were inferred to provide efficient pathways for fluid migrating from deep subsurface. The seafloor domes exhibits high backscatter feature, which is potentially associated with the seep-related gas hydrate and authigenic carbonate in the shallow sediment. It is speculated that fault and diapir activity, fault sliding caused by region extension and the interaction between neighbour domes control and affect the activity and formation of the domes. However, further investigations, including geological sampling and seafloor observation, are still needed to confirm whether they are mud volcanoes.

No abstract

The southwest mountainous area of China is one of the areas with the most landslides in the world. In this paper, we used Ya’an City and Garzê Tibetan Autonomous Prefecture in Sichuan Province as the research areas to explore the identification application effects of large-area potential landslides using synthetic aperture radar (SAR) data with different wavelength types (Sentinel-1, ALOS-2), different processing methods (SBAS-InSAR, Stacking-InSAR), and different geological environmental conditions. The results show the following: (1) The effect of identifying landslides with different slope directions is largely affected by the satellite orbit direction; when we identify landslide hazards across a large area, the joint monitoring mode of ascending and descending orbit data is required. (2) The period of monitoring affects the identification effect of potential landslides when landslide identification is carried out in southwestern China; the InSAR monitoring period is recommended to be more than 2 years. (3) In different geological environmental regions, SBAS technology and Stacking technology have their own advantages; Stacking technology identifies more potential landslides, and SBAS technology identifies potential landslides with higher accuracy; (4) the degree of vegetation coverage has a great impact on the landslide identification effect of different SAR data sources. In low-density vegetation coverage areas, the landslide identification result using Sentinel-1 data seems to be better than the result using ALOS-2 data. In high-density vegetation coverage areas, the landslide identification result using ALOS-2 data is better than that using Sentinel-1 data.