Integration of Unmanned Aerial Vehicle Imagery and Machine Learning Technology to Map the Distribution of Conifer and Broadleaf Canopy Cover in Uneven-Aged Mixed Forests

Integration of Unmanned Aerial Vehicle Imagery and Machine Learning Technology to Map the Distribution of Conifer and Broadleaf Canopy Cover in Uneven-Aged Mixed Forests

Uneven-aged mixed forests have been recognized as important contributors to biodiversity conservation, ecological stability, carbon sequestration, the provisioning of ecosystem services, and sustainable timber production. Recently, numerous studies have demonstrated the applicability of integrating...

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Bibliographic Details
Main Authors: Nyo Me Htun, Toshiaki Owari, Satoshi Tsuyuki, Takuya Hiroshima
Format: Article
Language:English
Published: MDPI AG 2023-12-01
Series:Drones
Subjects:
species group classification
uneven-aged mixed forest
UAV imagery
U-Net algorithm
random forest
Online Access:https://www.mdpi.com/2504-446X/7/12/705

Internet

https://www.mdpi.com/2504-446X/7/12/705

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