Rock characterization, UAV photogrammetry and use of algorithms of machine learning as tools in mapping discontinuities and characterizing rock masses in Acoculco Caldera Complex

Abstract

AbstractThe use of UAV represents a very useful tool for rock mass characterization, particularly in large, unsafe, and not accessible areas characterized by a complex geometry. This investigation was mainly focused on mapping discontinuities and characterizing rock masses using UAV photogrammetry, machine learning, including different algorithms, and intact rock laboratory analyses, respectively. To this aim different outcrops from those described as a part of the basement of the Acoculco Caldera Complex, composed by a series of folded limestones were selected. The results indicate that geomechanical and physical properties, together with outcrop information are very important to assign suitable properties to large rock units. In turn, the great number of plots of discontinuity orientation extracted from the 3D point cloud data by the used of our code written in python language allowed to easily identify the presence of a total of seven discontinuity sets, some of them related to the bedding sequence and some others related to shear and tensile stress due to folding.