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Project Explores How Drones Can Predict Spread of Wildfire

A University of Missouri researcher is teaming up with scholars in Kansas and Georgia to develop drone technology to monitor and potentially predict the spread of wildfires.

The $1.2 million research project that began last month aims to use unmanned aerial vehicles, or drones, to collect real-time data and send the information to firefighters to help contain wildfires, the Columbia Missourian reported.

"Currently, the (nation's) firefighting, or fire management system, is not very effective and efficient," said University of Missouri professor Ming Xin. "One of the main issues is we cannot predict where fires spread."

Xin is working with University of Kansas professor Haiyang Chao and Georgia State University professor Xiaolin Hu in the wake of nearly 56,000 wildfires burning across the country last year, including California's devastating Camp Fire in November that killed nearly 90 people.

The U.S. Department of Agriculture and National Science Foundation are sponsoring the project.

Xin said the project's drones follow a simulation that can precisely predict where a fire will spread for the next 10 to 30 minutes. The simulation is based on thermal imagery of an area and data on wind, terrain and vegetation. The drones collect the real-time data with thermal imaging cameras and sensors that help estimate the wind field.

The most significant factors affecting the spread of a wildfire are an area's terrain, vegetation and weather, Xin said. While information on an area's terrain and vegetation can be collected from a geological survey, the area's weather patterns are more difficult to determine, Xin said.

Xin hopes the technology will help firefighters with their decision-making because they'll be able to see the scene of a fire on a larger scale.

The researchers plan to launch test flights at the University of Kansas Field Station this summer.

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