A groundbreaking AI-supported mapping project has more than doubled the number of documented streams in the Chesapeake Bay Watershed, revealing over 200,000 miles of waterways—up from the previously recorded 100,000.
The Hyper-Resolution Hydrography Data is the product of a six-year collaboration between the University of Maryland, Baltimore County (UMBC), the Environmental Protection Agency’s Chesapeake Bay Program, and the Chesapeake Conservancy. By combining LiDAR elevation data with artificial intelligence and high-performance computing, researchers created the most detailed stream map of the watershed to date.
Led by UMBC geography professor Matthew Baker, the project marks the first large-scale use of AI and LiDAR for automated stream mapping. The resulting maps are ten times more detailed than previous versions and offer stream-by-stream estimates of width and depth.
“These maps allow us to understand how water moves through both natural and altered landscapes with unprecedented clarity,” Baker said. “It’s a leap forward for conservation science.”
The new data will help prioritize restoration efforts, such as streamside tree planting to reduce erosion and filter pollutants. Urban planners and farmers can also use the maps to mitigate runoff and protect habitat. David Saavedra ’14, now a senior geospatial lead at the Chesapeake Conservancy, led the accuracy assessment and praised the map’s transformative potential.
With a 94% match rate for known streams and up to 82% accuracy for previously unmapped ones, the dataset opens doors to novel research. Labeeb Ahmed ’15 of the EPA said the data will directly support the Chesapeake Bay Watershed Agreement goals, including mapping wetlands and species habitats.
“This is a game-changer for restoration, planning, and scientific discovery,” Ahmed said. “It connects the landscape to our waterways like never before.”
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