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CAIT creating new pipeline threat assessment tool for RITA’s remote sensing program
Remote sensing technologies that collect surface condition data can help infrastructure managers and owners identify high-risk areas after natural disasters. But, molding data into meaningful risk assessment tools requires a combination of know-how and technologies that aren’t always readily available.
USDOT-RITA’s Commercial Remote Sensing and Spatial Information (CRS&SI) program funds research projects that effectively streamline data collection and analysis so they can be put into action. Until now, this research has focused solely on surface infrastructure. Now, CAIT is taking it underground.
Dr. Jie Gong and pipeline experts from the Gas Technology Institute (GTI) are developing a threat assessment platform to analyze risks to pipeline segments following natural disasters. The tool will help utility operators identify and respond to areas where plumes, leaks, or even explosions can likely occur based on changes in a pipeline’s surrounding environment.
The team is building an integrated remote sensing technology that will map pipeline locations, collect three-dimensional images of surface conditions, and couple those with detailed temperature data.
“We’re using LiDAR sensors, whether it is airborne or vehicular, to scan test locations to generate high resolution three-dimensional models of what it ‘sees,’” Gong said. “The infrared cameras detect temperature anomalies or gas leaks that could pose threats to the integrity of gas pipelines below.”
Once the remote sensing tool is deployed, the data it collects will be fed into multilayered GIS-based threat assessment software created by the team.
The first layer in the software will be a GIS map extracted from existing sources that shows pipeline locations.
The second layer hosts an imagery analysis function that compares surface condition images or models to detect slight changes in the environment around pipelines.
The third layer reviews these changes and categorizes them as one of several risk factors like erosion, flooding, or building collapse.
Finally, the tool will calculate the probability of pipeline failure, damage, or disaster based on the risk factors it finds.
The platform will be tested in shore communities affected by Superstorm Sandy. In October 2012, Gong led a study using mobile LiDAR to create high-resolution models of storm damage for officials to plan recovery efforts.
“We already have the surface models from our post-Sandy study in 2012. We’ll revisit those areas, collect some updated models, and upload both into our new software to test its functionality,” Gong said. “That system will compare the two models point by point to detect even the slightest changes in environment.”
The tool will identify high-risk pipe segments to optimize repair schedules and enhance pipeline performance. “It’s one thing to go out and collect data and say, ‘Here’s a colorful 3D model of what things look like,’ without deciphering what the data could mean,” Gong said. “What we’re doing with this project is not only testing the compatibility of these integrated technologies, but taking the data and preparing a threat assessment to help decision makers direct actions where they’re most needed.”
Image: A gas pipeline exposed by storm surge flooding on Staten Island after Superstorm Sandy. ©Jie Gong/CAIT