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Post: Machine learning leads to a first in forestry management tools

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Machine learning leads to a first in forestry management tools
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First regional scale forest mapping using 1-meter measurements

University of Arkansas System Division of Agriculture Hamdi Zurqani FAYETTEVILLE, Ark. — A new dataset is providing a bird’s-eye view of Arkansas’ forests 1 meter at a time.

An Arkansas researcher has developed the first high-resolution forest canopy cover dataset for an entire state, providing valuable insights for forest management and conservation to a major economic sector in Arkansas.

“I had this vision of creating something that we can rely on,” said Hamdi Zurqani, assistant professor for the College of Forestry, Agriculture and Natural Resources at the University of Arkansas at Monticello and researcher with the Arkansas Agricultural Experiment Station. “No data of this kind existed before for an entire state. Usually, people only create similar data for site-specific projects.”

The 1-meter measurements are unique. Until now, the most common forest measurements and datasets have come from satellite imagery at 30-meter spatial resolution, said Zurqani, who conducts research as part of the Arkansas Forest Resources Center, a partnership between the University of Arkansas System Division of Agriculture and UAM. The experiment station is the research arm of the Division of Agriculture.

Forest canopy cover measures the coverage of tree crowns from an aerial view. It shows how much a forest’s uppermost layer of branches, leaves and vegetation forms a continuous cover over the ground. This detailed information is crucial for tracking forest health, as canopy cover is essential for carbon sequestration, wildlife habitat and water regulation.

Zurqani says accurate mapping of tree coverage helps scientists monitor and manage forest resources effectively, ensuring the sustainability of these ecosystems. This information can also assist with wildfire risk assessments, tracking forest health threats from pests and climate, and urban planning.

Zurqani’s research was published late last year in the academic journal Remote Sensing Applications: Society and Environment . The article was titled “ High-resolution forest canopy cover estimation in eco-diverse landscape using machine learning and Google Earth Engine: Validity and reliability assessment. ”

According to the latest Arkansas Agricultural Profile , forests cover 57 percent of the state, and timber was one of the state’s top commodities in 2021 with about $409 […]

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