Failure Surface Identification and Structural Domain Segregation Using Drone-Based Structure from Motion Photogrammetry

Abstract

ABSTRACT An emerging topic in the geotechnical site characterization is the use of drones for rock mass characterization through Structure from Motion (SfM) photogrammetry. This study highlights a series of surveys utilizing a DJI Mavic II drone performed between July and August 2022 at an abandoned quarry in Clear Creek Canyon Park, located 0.25 miles west of Golden, Colorado. The purpose of these surveys was for failure surface identification of a historic wedge failure and structural domain segregation of the remaining rock slope. The study site is composed of a heavily jointed interlayered gneiss rock mass with distinct planar discontinuities. However, structural discontinuity orientations may only be homogenous across some sections of the rock mass. This research highlights an improved contour density-based methodology drawing upon existing methods of structural domain identification to locally divide the rock mass into domains of similar structural orientation. Stereographic comparisons between domains are considered utilizing an exponential Kamb density method. The results of this study reveal that both blasting effects and tectonic features likely induced the historic wedge failure. This study also reveals that the remaining rock mass may have profound spatial differences in structural orientations, requiring appropriate domaining for rock mass characterization. INTRODUCTION Most all rock masses have discontinuities in the form of joints, bedding planes, faults, lamination planes, foliation planes, and lithological contact surfaces whose quantity and orientations govern the rock mass strength (de Vallejo et al., 2011). Drone technology, in tandem with Structure from Motion (SfM) photogrammetry, is increasingly being used to characterize the discontinuities of slopes, particularly for steep and hard-to-access locations (Bar et al., 2021; Krajnovich et al., 2020; Papathanassiou et al., 2020; Salvini et al., 2017). Furthermore, data acquired from SfM photogrammetry can also be used in conjunction with previously established semi-automatic discontinuity identification methods (Buyer et al., 2020; Buyer & Schubert, 2016; Buyer & Schubert, 2017; García-Luna et al., 2019; Krajnovich et al., 2020). In addition, drone-based remote sensing can be safer than traditional methods (Battulwar et al., 2021; Deliry & Avdan, 2021).