Climate-driven coastal hazards, including shoreline erosion, flooding, and water-level fluctuations, are increasingly threatening infrastructure, ecosystems, and communities along Lake Ontario. Wayne County, with over 50 miles of shoreline, is particularly vulnerable yet lacks high-resolution tools to identify erosion hotspots and forecast future coastal risks. This project builds upon previous NYS-WRI-supported research that developed a proof-of-concept AI-based shoreline monitoring framework using satellite imagery and deep learning. The proposed study will enhance this framework by integrating high-resolution satellite imagery, UAV observations, and community-contributed shoreline data to improve shoreline change detection and forecasting. The project will also examine the influence of key hydroclimatic drivers, including lake water levels, wave dynamics, and precipitation, on shoreline evolution and coastal hazard vulnerability. These analyses will be used to develop high-resolution coastal hazard risk maps for the Wayne County shoreline.
A key component of the project is community engagement through citizen-based shoreline monitoring and collaboration with local stakeholders, including waterfront property owners, NYS Sea Grant, and community organizations. Project outcomes will be translated into accessible maps and visualization tools to support shoreline management, climate adaptation, and hazard mitigation planning. By combining artificial intelligence, high-resolution remote sensing, and stakeholder engagement, this project will deliver a scalable framework for coastal hazard forecasting and resilience planning across Lake Ontario and the Great Lakes region.