Cliff face rock slope stability analysis based on unmanned arial vehicle (UAV) photogrammetry

Abstract

Rock cliff faces are mostly avoided in rock engineering research, especially where the scale of the slope exceeds the scale of fracturing present in the rock mass. The research to understand the rock cliff face joints plays an important role in slope engineering. This paper presents a rock block identification method based on unnamed aerial vehicle photogrammetry and its computer implementation of Cliff face rock, Fort Munro Pakistan. An advance bundle adjustment method was used to build the real three-dimensional (3D) surface model of the rock mass. Later, random sample consensus algorithm was used to search the structural planes in cloud point model. A computer program, geotechnical structure and model analysis (GeoSMA-3D) was developed to solve the engineering problems and to verify the example. The program confirmed the efficiency of the theory in dealing with complex surface modelling and cliff face rocky slope stability analysis. The approach presented can be applied as a general guiding design principle for cliff face rock slope.