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Can artificial intelligence improve maps for land conservation?
SEATTLE (Thomson Reuters Foundation) - In December 2016, environmental group Chesapeake Conservancy unveiled one of the largest, high-resolution land-cover maps made in the United States. The bay, North America's biggest estuary, has struggled to recover from overfishing and pollution, and the conservancy hopes the map will guide environmental restoration decisions like where to plant stormwater-absorbing trees. Creating a 100,000-square-mile (259,000 square kilometres) digital map that defined land use - water, vegetation or concrete - at such a fine scale was "gruelling", said project director Jeff Allenby. "(It was) day after day of having staff process and correct the tiles," he said. First a computer analysed almost 80,000 tiles - each of which corresponds to about 13 square miles and digitally records the landscape.
- North America > United States > Maryland (0.15)
- North America > United States > Washington > King County > Redmond (0.05)
- North America > United States > Virginia (0.05)
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- Information Technology (0.97)
- Law > Real Estate Law (0.36)
- Law > Environmental Law (0.35)
How Artificial Intelligence Could Prevent Natural Disasters
On May 27, a deluge dumped more than 6 inches of rain in less than three hours on Ellicott City, Maryland, killing one person and transforming Main Street into what looked like Class V river rapids, with cars tossed about like rubber ducks. The National Weather Service put the probability of such a storm at once in 1,000 years. Yet, "it's the second time it's happened in the last three years," says Jeff Allenby, director of conservation technology for Chesapeake Conservancy, an environmental group. Floods are nothing new in Ellicott City, located where two tributaries join the Patapsco River. But Allenby says the floods are getting worse, as development covers what used to be the "natural sponge of a forest" with paved surfaces, rooftops, and lawns.
- North America > United States > Maryland > Howard County > Ellicott City (0.25)
- North America > United States > Virginia (0.15)
- Oceania > Australia > Queensland (0.05)
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How Microsoft's AI Could Help Prevent Natural Disasters
On May 27, a deluge dumped more than 6 inches of rain in less than three hours on Ellicott City, Maryland, killing one person and transforming Main Street into what looked like Class V river rapids, with cars tossed about like rubber ducks. The National Weather Service put the probability of such a storm at once in 1,000 years. Yet, "it's the second time it's happened in the last three years," says Jeff Allenby, director of conservation technology for Chesapeake Conservancy, an environmental group. Floods are nothing new in Ellicott City, located where two tributaries join the Patapsco River. But Allenby says the floods are getting worse, as development covers what used to be the "natural sponge of a forest" with paved surfaces, rooftops, and lawns.
- North America > United States > Maryland > Howard County > Ellicott City (0.25)
- North America > United States > Virginia (0.15)
- Oceania > Australia > Queensland (0.05)
- (8 more...)
Artificial Intelligence: Navy Works on Teaching Robots How to Behave
The rise of artificial intelligence has long stoked fears of killer robots like the "Terminator," and early versions of military automatons are already in the battlefield. Now the Navy is looking into how it can teach machines to do the right thing. "We've been looking at different ways that we can have people interact with autonomous systems," Marc Steinberg, an Office of Naval Research manager, said in a phone interview this month. The Navy is funding a slew of projects at universities and institutes that look at how to train such systems, including stopping robots from harming people. In 1979, a Ford autoworker in Michigan became the first person killed by a robot when he was struck in the head by the arm of a 1-ton production-line machine, according to Guinness World Records. More recently, police in Dallas used a robot to deliver a bomb that killed the shooter who opened fire on officers at a Black Lives Matter protest.
- North America > United States > Michigan (0.25)
- North America > United States > District of Columbia > Washington (0.05)
- North America > United States > Arizona (0.05)
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