Machine learning predicts forest soil fungal diversity from drone images‎

Combining drone data and machine learning can help cover more ground in monitoring forest soil health, University of Alberta research shows. The findings are published in the journal Forest Ecology and Management. Using both tools to map and monitor soil fungal diversity—a key indicator of a healthy forest ecosystem—proved highly effective and could help reduce the need for boots-on-the-ground soil sampling over huge areas of forest, says Dr. Cameron Carlyle, a professor in the Faculty of Agricultural, Life & Environmental Sciences and a co-author of the study.