University of Tennessee, Knoxville (UT) researchers have developed an algorithm that indicates, following a disaster, which areas need detailed mapping first, which should help response teams respond more efficiently to the most urgent needs.
Volunteers using existing Web-based mapping projects review the most current remote-sensing images, fill in the geographic data gaps, and update the maps following a disaster. However, the hundreds of volunteers working together often map the grid cells in a random order, which slows down the process.
The new algorithm prioritizes the mapping tasks, taking into account the area's population, disaster severity, and road network, and simulates potential rescue routes. It then ranks the priorities of the grid cells based on how the information within each cell can potentially assist the route-planning decisions of response teams. In addition, the algorithm can help inform online volunteers about the priorities of the grid cells via color codes.
"If online volunteers can first map the grid cells that are more urgent, response teams may be able to use the information at an earlier stage," says UT professor Yingjie Hu.
The researchers next want to partner with humanitarian organizations to test the algorithm in a real disaster.
From Tennessee Today
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