AI model achieves detailed tree crown segmentation from drone imagery

Researchers have developed a deep-learning model for segmenting individual tree crowns in broadleaf forests using UAV imagery. The model, based on Mask2Former, was trained on over 18,500 manually delineated crown polygons from seven Japanese forests. It demonstrated strong performance and generalizability across diverse forest types, including tropical rainforests in Borneo, highlighting the importance of large, high-quality annotated datasets. This technology has been integrated into the DF Scanner Pro software to aid practical forest monitoring. AI

IMPACT Enables more detailed and automated forest monitoring and analysis at a tree level.

RANK_REASON Academic paper detailing a new deep-learning model for image segmentation. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

• DF Scanner Pro
• Masanori Onishi
• Mask2Former

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