CHARACTERIZING DISCONTINUITIES IN CUT SLOPES AS A WAY TO PREDICT POTENTIAL ROCKFALL HAZARDS USING LIDAR-SLAM TECHNOLOGY

Rockfall hazards are common along roads built in mountainous regions. Several geologic and environmental factors can affect the presence of rockfall hazards and accidents, such as unfavorable orientation of rock discontinuities, slope orientation, degree of undercutting, road visibility, catchment ditch effectiveness, and degree of interbedding. The practice of manually observing road outcrops for discontinuities and potential slope failures can be beneficial; however, it can also be a resource-consuming practice that can yield results on an inefficient time scale. Therefore, the use of a vehicle-mounted-LiDAR (Light Distance and Ranging) scanner with SLAM (Simultaneous Localization and Mapping) can improve the accuracy while reducing the time commitment. The objective of this ongoing study is to find best practices to collect information with LiDAR-SLAM (to better visualize discontinuities) by collecting data using different parameters to observe changes in point-cloud density, and the relationship between time and accuracy with different trajectories (loops vs single-stretches) and average velocities (5,10,25 mph). Preliminary results suggest that a point cloud constructed with an average velocity of 5 mph with a looping trajectory will maximize the number of points in the point cloud. Using a single stretch route at an average velocity of 10 mph does reduce point density, but does not significantly compromise the quality of the point cloud. Future research would include adding a camera with the scanner to colorize meshes to discern the rock outcrop faces better and distinguish between vegetation and the cut slope. Future developments should also include the ability to create geo-referenced maps of roads that will be similar to those of Google Maps.