A team of American computer engineers and biologists introduced the EEAGER system, a satellite-driven approach designed to identify beaver dams in expansive wild areas. This capability could support smarter water-resource management in regions affected by drought and even assist in reducing wildfire risk, as reported by Wired.
The concept behind EEAGER was conceived by Eddie Corwin, a former Google employee who pursued sustainable real estate development. While studying water regulation, he became intrigued by beavers and the dams they build, structures capable of storing significant volumes of water and helping to regulate floods.
Corwin collaborated with his colleague Dan Akerstein to develop a method that would automatically map beaver-built infrastructure across landscapes. The goal was to translate ecological engineering into a scalable, data-driven tool for monitoring ecosystem services provided by beaver activity.
Throughout the project, beaver expert Emily Fairfax from the University of Minnesota contributed insights. Fairfax has explored how beaver dams create animal corridors during wildfires and can contribute to cooling and moisture retention that may dampen the spread of flames in certain conditions.
A multidisciplinary team of scientists and programmers trained the EEAGER model on a large dataset comprising 13,000 satellite images featuring beaver dams and 56,000 landscape images without such ponds. The neural network demonstrated a high level of accuracy in recognizing beaver-related structures, achieving performance around 98.5 percent in testing scenarios.
Plans were announced for field testing of EEAGER in California during 2024, with the aim of locating beaver dams and ponds more comprehensively. Officials hoped to obtain precise information about where beavers reside, their population density, and potential areas for reintroduction to bolster wildlife resilience in drought-prone and fire-prone regions.
In addition to the United States, conversations emerged about broader applications in Canada, where a number of cities face digital connectivity gaps. The EEAGER effort signals a broader trend toward using satellite imagery and machine learning to map natural infrastructure that supports water security and ecological health, while also addressing emergency risk reduction across diverse landscapes. These developments underscore the value of aligning technological innovation with conservation goals to support communities facing climate-related challenges.