Tracking the Evolution of Barrier Island Foredunes Using Computer Vision
Keywords
coastal geomorphology, barrier islands, climate change, OpenCV, Scale-Invariant Feature Transform
Type of Proposal
Visual Presentation (Poster, Installation, Demonstration)
Faculty
Faculty of Science
Faculty Sponsor
Dr. Chris Houser
Proposal
Barrier islands serve as the first line of defence for important landward ecosystems and coastal communities, but factors such as climate change and human activity threaten their ability to respond to major storms and heighten the risk of high-impact storm regimes. In response to climate change and sea level rise, it is important to develop a robust model of coastal system evolution, yet studies have shown that extracting simple metrics and models to track evolution is difficult. The spatiotemporal patterns of barrier islands can be tracked using computer vision techniques such as Scale-Invariant Feature Transform (SIFT) to better understand system evolution. A python script was compiled to implement OpenCV’s SIFT model on Digital Elevation Models (DEMs) of Brackley Beach, PEI, allowing for detected key features to be matched across multiple years. Results indicate the movement of the barrier system in response to sea level rise and may aid in developing strategies to combat coastal system erosion in the coming decades.
Tracking the Evolution of Barrier Island Foredunes Using Computer Vision
Barrier islands serve as the first line of defence for important landward ecosystems and coastal communities, but factors such as climate change and human activity threaten their ability to respond to major storms and heighten the risk of high-impact storm regimes. In response to climate change and sea level rise, it is important to develop a robust model of coastal system evolution, yet studies have shown that extracting simple metrics and models to track evolution is difficult. The spatiotemporal patterns of barrier islands can be tracked using computer vision techniques such as Scale-Invariant Feature Transform (SIFT) to better understand system evolution. A python script was compiled to implement OpenCV’s SIFT model on Digital Elevation Models (DEMs) of Brackley Beach, PEI, allowing for detected key features to be matched across multiple years. Results indicate the movement of the barrier system in response to sea level rise and may aid in developing strategies to combat coastal system erosion in the coming decades.