A researcher from the University of Missouri is working with scholars in Kansas and Georgia to develop drone technology to track and possibly predict the spread of forest fires.

The $ 1.2 million research project that began last month is intended to use unmanned aircraft or drones to collect real-time data and send information to firefighters to prevent forest fires, Columbia Missourian reported.

"Currently, the (national) fire fighting or fire management system is not very effective and efficient," says Professor Ming Xin of the University of Missouri. "One of the main problems is that we can not predict where fires spread."

Xin collaborates with University of Kansas professor Haiyang Chao and Georgia State University professor Xiaolin Hu in the aftermath of nearly 56,000 forest fires that set fire to the entire country last year, including California's devastating campfire in November involving nearly 90 people life came.

The US Department of Agriculture and the National Science Foundation sponsored the project.

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

The main factors that influence the spread of a forest fire are the terrain, the vegetation and the weather of an area, Xin said. Although information about the terrain and the vegetation of an area can be collected through geological research, the weather patterns in the area are more difficult to determine, Xin said.

Xin hopes technology will help firefighters make decisions because they can see the scene of a fire on a larger scale.

The researchers are planning to start test flights this summer at the University of Kansas Field Station.

Copyright 2019 Associated Press. All rights reserved. This material may not be published, broadcast, rewritten or redistributed.

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