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New Algorithm Boosts Crowd-sourced Maps for Natural Disasters

  • Reuters

A Central Electric Power Association lineman pulls a new line across the debris littered lawn of a Scott County, Mississippi resident, Nov. 30, 2016, that was damaged by an apparent tornado Tuesday afternoon. With crowd-sourced mapping rescue workers will have the information they need, such as which roads, buildings and bridges have been destroyed.

A Central Electric Power Association lineman pulls a new line across the debris littered lawn of a Scott County, Mississippi resident, Nov. 30, 2016, that was damaged by an apparent tornado Tuesday afternoon. With crowd-sourced mapping rescue workers will have the information they need, such as which roads, buildings and bridges have been destroyed.

Humanitarian workers delivering aid to regions hit by natural disasters might find it a little easier to reach people most in need of help following new advances in crowd-sourced mapping technology, researchers said on Wednesday.

Traditional maps often do not give rescue workers the information they need when disasters strike, such as which buildings and bridges have been destroyed.

Crowd-mapping, where volunteers on the ground send real-time information about which roads are open and where people could be trapped following earthquakes or hurricanes, has become increasingly popular with aid groups, U.S. researchers said.

Universities create helpful algorithm

To make the mapping process more efficient, researchers at the University of California and the University of Tennessee created a new algorithm that indicates which areas need detailed mapping first after a disaster.

"Online volunteers provide up-to-date geographic information that can help disaster response teams on the ground make more informed decisions," said University of Tennessee geography professor Yingjie Hu.

"We wanted to make that process more efficient," Hu told the Thomson Reuters Foundation.

Earthquake sparks interest

Originally from Sichuan, China, Hu began researching crowd-funded maps after a massive earthquake rocked his home province in 2008 killing more than 80,000 people.

FILE - Survivor carries baby on his back as he and some 1,000 other survivors make a 9-hour walk from the village of Qingping to Hanwang, after earthquake, Sichuan Province, China, May 16, 2008.

FILE - Survivor carries baby on his back as he and some 1,000 other survivors make a 9-hour walk from the village of Qingping to Hanwang, after earthquake, Sichuan Province, China, May 16, 2008.

Rescuers scrambled to save survivors but their efforts were hampered in some cases by a lack of up-to-date information about which roads were open to emergency vehicles, Hu said.

"If we could have applied this algorithm back then more lives could potentially have been saved," he said.

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