Enhancement of Point Cloud Data for Rock Slope Stability Analysis
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Unmanned aerial vehicle (UAV) photogrammetry offers a safe and efficient alternative to manual rock mass characterization in hazardous terrain. This study evaluates quality control measures, compares the discontinuity of accuracy data with and without Ground Control Points (GCPs), and performs kinematic a stability analysis of a sedimentary rock slope. Using a GPS-integrated drone and GNSS coordinates, a high-resolution 3D model was generated in Agisoft Metashape, and discontinuity orientations were extracted using CloudCompare. Results indicate that optimal UAV camera angles and an image overlap of 60%–80% are critical for achieving high model fidelity. Incorporating GCPs significantly improved accuracy; the mean percentage differences in dip direction decreased from 5.21%–22.01% (without GCPs) to 1.66%–10.06% (with GCPs). Comparative analysis with manual scanline surveys demonstrated strong agreement, successfully identifying stable conditions, as well as wedge and planar failures modes. These findings underscore the necessity of GCPs in UAV-based mapping for reliable kinematic rock slope assessment.
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