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NASA has awarded a University of Maryland-led team a $1.4 million grant to develop artificial intelligence-based technology to support the conservation of carbon and biodiversity corridors in Central Africa.
The initiative aims to create high-resolution "digital twins"—virtual replicas of physical systems that utilize artificial intelligence and machine learning to analyze real-time data. Applied to Central Africa's carbon and biodiversity corridors, the models will enable scientists to test and forecast different scenarios with unprecedented detail and flexibility.
The project, which will also use remote sensing data and high-fidelity ecosystem modeling, is spearheaded by Department of Geographical Sciences Assistant Professor Yiqun Xie, who is also an affiliate faculty at the Artificial Intelligence Interdisciplinary Institute at Maryland (AIM), along with Professor and Associate Chair George Hurtt, Assistant Research Professor Lei Ma and Assistant Professor Catherine Nakalembe. The team will work with co-investigators from the University of Pittsburgh and Northern Arizona University, as well as collaborators from Yale University, Imazon (Brazil) and WildlifeDirect (Kenya).
Central Africa's forests house the world’s second-largest contiguous rainforest, serving as a major global carbon reservoir and home to thousands of endemic species of plants and wildlife. However, decades of land use, climate change and resource exploitation have led to significant and continued degradation.
“Preserving Central Africa's unique ecosystems is essential for both biodiversity and climate mitigation,” said Xie. “This project will provide the tools needed to make data-driven decisions for conservation efforts and sustainable development.”
The project was one of 24 initiatives selected for funding under NASA’s Advanced Information Systems Technology (AIST) Program, part of NASA’s Earth Science Division. It funds research that advances information systems technology to meet the needs of Earth science missions over the next decade.
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