New Study Demonstrates How NASA Hyperspectral Imaging and Machine Learning Can Transform Biodiversity Management in California
SIPA’s Sara Tjossem – along with MPA-ESP 2024 alumni Anna Veldman, Saiarchana Darira, Christina Van Dyke, and Radhika Ajayan – are among the coauthors of a new paper, “Applying machine learning to biodiversity management: Lessons from two California biodiversity hotspots,” published in Ecosphere.
The project created hands-on training opportunities for MPA-ESP students, who cowrote the paper as an independent study with Tjossem. The research reveals how advanced hyperspectral remote sensing and machine learning can equip land managers with powerful, data-driven tools to prioritize restoration and monitor ecosystem health over time.
“Our Environmental Science and Policy graduates are helping conservation managers with data-driven tools to prioritize restoration efforts and monitor their effectiveness over time,” said Tjossem.
The research is a collaborative effort led by the NASA Jet Propulsion Laboratory (JPL) in collaboration with the Nature Conservancy, University of California Santa Barbara, and Columbia University.