Machine learning predicts forest soil fungal diversity from drone images

University of Alberta researchers have found that drone imagery combined with machine learning can effectively map and monitor soil fungal diversity—a key indicator of healthy forests. The findings, published in Forest Ecology and Management, could significantly reduce the need for traditional boots-on-the-ground soil sampling across large forest areas, says Dr. Cameron Carlyle, a co-author of the study.

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