CASE STUDY: Can Photogrammetry from UAS's Help Predict Disasters Before They Occur?

3D mesh model of the  Ridracoli dam

SUMMARY: UAV data combined with photogrammetry allows major infrastructure companies to survey their assets with an accuracy that compares favorable to terrestrial LiDAR, but more rapidly, with greater coverage, and at a fraction of the cost. These firms can now perform proactive asset management, and apply tools and methodologies that detect trends and problems before they become real-world safety risks.

PROBLEM: Major infrastructure assets like large bridges and dams require scheduled inspections for maintenance assessments. These complex assets are often in hard to reach, out-of-the-way locations. Traditional inspections methods like terrestrial LiDAR can be slow, expensive, and difficult to use for less experienced operators. These factors result in high inspections costs in an already immense maintenance budget.

In the Emilia-Romagna region of Italy, the Romagna Aqua company is responsible for the drinking water infrastructure. The company was seeking a better way to inspect and maintain the Ridracoli Dam, the backbone of their region's aqueduct. The Ridracoli Dam is comprised of 600,000 square feet of concrete and has a basin covering 32 million cubic meters. The structure is 355 feet tall at the base, and 1,444 feet tall at the crest. It's mammoth as far as infrastructure assets go. Since the dam is crucial to providing drinking water to 48 municipalities, it is maintained with exceptionally high safety standards. Romagna Aqua has embraced predictive modeling to forecast how the dam will respond to changes in various environmental conditions -- especially earthquakes and thermal variations. To feed this model, the company requires accurate data with short turnaround times.

SOLUTION: Romagna Aqua believed that unmanned aircraft systems (UAS's) could provide a better solution for their needs. Working with Italdron, the University of Perugia, and the Department of Civil and Environmental Engineering, the company performed a topographical survey which would serve as the baseline for the UAV portion.

For the UAV portion, the team send out the aircraft for 23 flights -- each lasting about 25 minutes -- over the course of a single day (to minimize effects of atmospheric conditions like lighting and weather). The UAV captured over 6,000 photographs -- many from areas that were previously in accessible for survey, like the downstream portion of the dam's arch. Using specialized software to process the photos, the team generated both reality mesh files (3D models with colorized and textured polygons) and dense point clouds, When the team compared the UAV data products with the data product from the topographical survey, they were thrilled. The data products from the UAV showed deviations within a range of 2 centimeters, and sometimes even less.

Photogrammetry model of the Ridracoli Dam, Italy.

A 3D mesh of the dam produced in ContextCapture (the right side is colored and textured, the left side is raw)

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