Probabilistic assessment of slope stability using photogrammetric 3D reconstruction: a novel approach

Most of the existing probabilistic stability assessment approaches consider 2D slope geometry generated from CAD-based approximations. This oversimplification of pit geometry often leads to slope stability estimations which are unrealistic. This research aims at combining 3D reconstructed geometry of a full mining pit with probabilistically modelled material properties to attain a better estimate of slope stability. (a) Here, a photogrammetry-enabled 3D reconstruction approach is used for modelling the geometry of an entire mining pit. (b) The uncertainty and spatial variability associated with the input parameters (material properties, seismic coefficients etc.) are modelled based on log-normally distributed random fields. Finally, the photogrammetry-obtained 3D slope and Monte Carlo sampling-obtained input parameter realizations are used to estimate the probability of slope failure in an opencast coal-mining district. To the best of our knowledge, the proposed framework is the first attempt at probabilistic slope stability assessment of opencast mining environments using 3D reconstructed surface geometry. The mine authority was informed about the potential failure regions, where the probability of failure of the pit was found to be 85% under saturated conditions.