This study proposes a semi-supervised learning algorithm using pseudo-labels for 3D geological modelling. We establish a 3D geological model using borehole data from a complex real urban local survey area in Shenyang and make an uncertainty analysis of this model. The method effectively expands the sample space, which is suitable for geomodelling and uncertainty analysis from boreholes. The modelling results perform well in terms of spatial morphology and geological semantics.

This study proposes a 3D and temporally dynamic (4D) geological modeling method. Several simulation and actual cases show that the 4D spatial and temporal evolution of regional geological formations can be modeled easily using this method with smooth boundaries. The 4D modeling system can dynamically present the regional geological evolution process under the timeline, which will be helpful to the research and teaching on the formation of typical and complex geological features.

The lack of collocated meteorological data at GNSS stations makes it difficult to take full advantage of GNSS observations for weather studies. This research demonstrates the potentials of retrieving accurate PWV from GNSS using adjacent synoptic data and generating high-quality PWV maps from the GNSS network for weather prediction in near-real time. Results also demonstrate that it's possible to reveal the moisture advection, transportation and convergence during heavy rainfalls using PWV maps.