Purdue launches new AI-based global forest mapping project
Purdue researchers led by Jingjing Liang will develop the first global artificial intelligence-based forest growth model, with funding from the World Resources Institute. (Photo courtesy of Radomir Balazy)
WEST LAFAYETTE, Ind. — Purdue University’s Jingjing Liang has received a two-year, $870,000 grant from the World Resources Institute to map global forest carbon accumulation rates.
“To accurately capture the carbon accumulation rates of forested ecosystems across the world has always been a challenging task, mostly because doing so requires lots of ground-sourced data, and currently such data are very limited to the scientific community,” said Liang, an associate professor of quantitative forest ecology and co-director of the Forest Advanced Computing and Artificial Intelligence Lab.
“This task is considerably more challenging than mapping carbon emissions from forest loss,” said Nancy Harris, research director of the Land & Carbon Lab at the World Resources Institute, a nonprofit research organization based in Washington, D.C. “With emissions, there’s a clear signal in satellite imagery when trees are cut, leading to a big drop in forest carbon stocks and a relatively abrupt pulse of emissions to the atmosphere. With sequestration, forests accumulate carbon gradually and nonlinearly.
