Slope visualisation and stability study using geographic information science

Abstract

High-precision visualised three-dimensional (3D) slope modelling and stability analysis have benefited from the quick development of big data technology. This research aims to utilise unmanned aerial vehicle survey data to obtain influencing information on slope topography. A high-precision 3D surface model is established, which is then overlaid with 3D geological models and 3D mineral models constructed using geographic information system technology. This approach enables more efficient and accurate 3D visualisation modelling of slopes. Based on the 3D model, the search for the most dangerous sliding surface under rainfall conditions is completed. The average absolute error of sample points in the surface modelling effect verification experiment is less than 0.5 m, and the average relative error is less than 2%. These results indicate that the overall modelling effect of the 3D slope model can meet the requirements of subsequent stability analysis. According to the results of random simulation, the minimum safety factor on the most neutral surfaces is less than 1, which indicates that the slopes at some locations in this site do have the possibility of landslide. The neutral surface where the lowest safety factor appears can be used to pinpoint the position of the most hazardous sliding surface.