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– Every spring and fall, billions of birds migrate across the United States, largely unseen under the cover of darkness. Now a team of researchers led by computer scientist Daniel Sheldon at the University of Massachusetts Amherst plan to develop new analytic methods with data collected over the past 20 years – more than 200 million archived radar scans from the national weather radar network – to provide powerful new tools for tracking migration. Sheldon says, “The Dark Ecology Project will develop new resources allowing us to estimate the densities of migrating birds over the U.S. each year for the last 25 years.” His collaboration with computer vision expert Subhransu Maji at UMass Amherst and Steven Kelling, director of information science at the Cornell Laboratory of Ornithology, Ithaca, N.Y., is supported by a three-year, $903,300 National Science Foundation grant to UMass Amherst and $309,000 to Cornell. Sheldon has collaborated with scientists at the Cornell Lab of Ornithology since 2009, when he was a Ph.D. student at Cornell. Kelling’s information science team developed eBird, a citizen science project that collects observations from birdwatchers across the globe. The researchers use big data methods to piece together eBird observations to reveal complex patterns of bird occurrence and to guide international bird conservation efforts such as the 2016 State of North America’s Birds report. Maji’s group has developed computer vision techniques for fine-grained categorization, which are alreadyhelping citizens connect with nature by automatically recognizing species of birds, animals, http://alphoe5iex756429.nanobits.org/some-emerging-guidance-on-fast-methods-in-topickeyword and other organisms in photographs. A long-term vision for the new grant, Sheldon explains, is to combine these new data resources to provide a detailed continent-wide view of bird migration.
For the original version including any supplementary images or video, visit https://www.umass.edu/newsoffice/article/%E2%80%98dark-ecology-project%E2%80%99-will-use-past
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