Researchers from the University of Illinois Urbana-Champaign, Washington University in St. Louis, and Sandia National Laboratories have developed a novel dataset to improve the mapping of Alaska’s peatlands. By using radar sensing to detect surface moisture and vegetation structure, combined with machine learning to analyze patterns and classify peatland regions, the dataset provides a more accurate spatial representation of these carbon-rich permafrost areas than traditional ground-based mapping. This dataset addresses limitations in traditional ground surveys and enhances research on carbon storage, nutrient cycles, and peat-fire behavior—key factors for land conservation and fire management.
Image Credits: Journeys with Sean
