Integrated drone photogrammetry for interbedded rock slope classification and geotechnical stability assessment

Abstract

Interbedded rock slopes comprising alternating sandstone–shale layers exhibit strong anisotropy and spatial heterogeneity, reducing the reliability of conventional, point-based rock mass classification and stability assessment. This study develops an integrated workflow based on drone photogrammetry or unmanned aerial vehicle structure-from-motion (UAV-SfM) to quantify the structural and geomechanical condition of such slopes. High-density point clouds acquired from UAV-SfM were converted into georeferenced, textured 3D surface meshes using ground control points, providing an accurate geomorphological model of the exposed slope. This virtual outcrop enabled continuous, high-resolution mapping of bedding and discontinuities without requiring full physical access to the slope face. Structural attributes including dip and dip direction, spacing, persistence, roughness, weathering condition, and blockiness were extracted using plane fitting and virtual scanlines in ShapeMatriX®, and subsequently used for kinematic analysis and rock mass classification. The results show that wedge sliding is the dominant instability mechanism, with planar sliding locally controlled by persistent shale partings, particularly in structurally complex lower slope domains. Rock mass quality derived from rock mass rating (RMR) ranges from 33 to 50, classifying the slope as Poor to Fair, while geological strength index (GSI) values between 5 and 50 indicate severe degradation in shale-rich bands and comparatively higher integrity in sandstone-dominated zones. Overall, the study demonstrates that UAV-SfM point-cloud modelling provides an effective and defensible basis for virtual rock mass characterization and for linking discontinuity condition, empirical geomechanical indices i.e. RMR and GSI, and kinematic failure potential in anisotropic interbedded rock slope formations.