Phase II: High Resolution Digital Elevation Models (DEMs) and Street-Level Imagery for Rock Cut Slope Inventory and Rockfall Hazard Rating

About the report:

Proactive management of geotechnical assets such as rock cut slopes along highways includes performing inventory and evaluating rockfall hazard ratings. Both activities are aimed at helping transportation agencies to proactively monitor and maintain rockfall prone rock cut slopes. Rock cut slope inventory involves locating rock cut slopes and collecting preliminary geometric/geologic attributes that may contribute to slope failure leading to rockfalls. Rockfall hazard rating provides a detailed analysis of the presence of rockfall hazard risk factors. The risk factors include geometric and geologic factors that are traditionally collected in the field requiring intensive time and monetary investment. An alternative method is the use of remotely acquired data such as the use of LiDAR and photogrammetry to measure geologic parameters on the desktop. This research project is a pilot test to investigate the use of high-resolution LiDAR-derived digital elevation models (DEMs) and street-level imagery from (www.Mapillary.com) to collect geometric and geologic data on the desktop. The proposed automated/semi-automated method will save time and money required for both rock slope inventory and rockfall hazard rating. The accuracy of automated soil/rock cut slope detection using digital elevation models (DEMs) and street-level imagery was found to be 86% when compared to traditional field collection methods and 95% in identifying rock cut slopes. Measurements of rockfall hazard parameters were also in close agreement to those measured in the field. The proposed method will streamline a desktop method, limit field visits and measurements, and enable infrastructure agencies to become more efficient in managing their rock slope assets.

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