A Laboratory for the Integration of Geomatic and Geomechanical Data: The Rock Pinnacle “Campanile di Val Montanaia”

Abstract

This work describes a procedure for building a high-quality 3D model of a rocky pinnacle in the Dolomites, Italy, using Structure from Motion (SfM) techniques. The pinnacle, known as “Campanile di Val Montanaia”, is challenging to survey due to its high elevation and sub-vertical cliffs. The construction of the 3D model is the first step in a multi-disciplinary approach to characterize the rock mass and understand its behavior and evolution. This paper discusses the surveying operations, which involved climbing the pinnacle to collect Ground Control Points (GCPs) and using a UAV to capture aerial imagery. The photographs were processed using SfM software to generate point clouds, mesh, and texture, which were then used for rock mass discontinuity mapping. The study compares models of different qualities and point densities to determine the optimal trade-off between processing time and accuracy in terms of discontinuity mapping. The results show that higher quality models allow for more detailed mapping of discontinuities, with some drawbacks due to noise in the case of the densest solution (e.g., increase in frequency of outliers across the point cloud). These pros and cons are also discussed in relation to the computational cost necessary to build the models. The study also examines the limitations and challenges of performing discontinuity mapping in the different models, including subjectivity in interpretation. A further element of interest is the publication of a high-quality 3D georeferenced model of the “Campanile di Val Montanaia” to be used for several potential further applications, such as stability analyses and numerical modeling.

UAV Photogrammetry for Estimating Stand Parameters of an Old Japanese Larch Plantation Using Different Filtering Methods at Two Flight Altitudes

“…However, our RMSE was 0.000553 m and 0.331 pix for UAV 80 m, and 0.000481 m and 0.367 pix for UAV 120 m, during image alignment when two GCPs were added in Agisoft Metashape, confirming the accuracy of the measurements. Tavasci et al [ 79 ] obtained an RMSE of 0.06 m with seven GCPs and a GSD of 0.03 m using RTK GNSS, and they confirmed the good quality of the measurement. Izere [ 107 ] stated that UAV Phantom 4 RTK M300 with RTK GNSS enabled high accuracy on plant height estimation without GCPs.…”

“…The depth filtering mode during the photogrammetric process is considered to remove noticeable outliers while preserving as much as possible the detailed elements of the three-dimensional model [ 79 ]. Tavasci et al [ 79 ], Moe et al [ 77 ], and Jayathunga et al [ 15 ] used mild depth filtering for the automated removal of outliers. We also used mild depth filtering, which was set to remove outliers.…”

“…Image processing was performed separately for UAV 80 m and UAV 120 m. The GCPs were added to each corresponding image for optimization of the camera locations and orientations, as well as other internal camera parameters. The depth filtering mode during the photogrammetric process is considered to remove noticeable outliers while preserving as much as possible the detailed elements of the three-dimensional model [79]. Tavasci et al [79], Moe et al [77], and Jayathunga et al [15] used mild depth filtering for the automated removal of outliers.…”