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AI, lasers used to evaluate forest damage after hurricanes

1 June 2024

University of Florida Institute of Food and Agricultural Sciences researchers are preparing for hurricane season with state-of-the-art monitoring equipment that will help them determine how extensively forests are damaged during individual hurricanes.

When hurricanes cross Florida, they not only damage homes and businesses, they also destroy forests and timber farms. Getting an accurate assessment for how much timber is damaged by hurricanes is essential for environmental management decisions, salvaging logging operations, tree farms’ insurance estimates and climate change studies, but so far, it’s been a vexing puzzle.

Carlos Silva, assistant professor of quantitative forest science in the UF/IFAS School of Forest, Fisheries and Geomatics Sciences and director of the forest biometrics, remote sensing and AI lab, said the key is to use a combination of remote sensing and artificial intelligence technologies, to create pre- and post-hurricane 3D maps of forests to evaluate forest loss. He uses satellites and lidar – a technology that uses lasers to collect data and which stands for Light Detection and Ranging – ground equipment to achieve this.

“Hurricanes pose a fundamental challenge for us in Florida,” Silva said. “The traditional way to assess the impact of hurricanes is basically going to the field, establishing plots and measuring trees. But if we’re thinking about large areas, it’s really time-consuming, therefore the traditional way of assessing the impact of hurricanes on forest ecosystems is not efficient.”

“We are in a new era for monitoring forests, thanks to these innovative remote-sensing and AI methods,” he said.

Data helps emergency managers and environmental managers make fast, smart decisions in the aftermath of a hurricane, he said. These data help them know which areas were most affected and need help immediately, and which would benefit from specialised action at a later time – such as where to do salvage logging operations.

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Source: University of Florida

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