Evaluation of the quality of automatic tree detection using photogrammetric canopy height models and orthomosaic

Evaluation of the quality of automatic tree detection using photogrammetric canopy height models and orthomosaic

The work was performed in the old-growth linden-spruce forest of the Kologrivsky Forest Nature Reserve (Kostroma Oblast, Russia) based on aerial photography with a quadcopter. Automatic detection algorithms made it possible to detect most of the trees in the forest canopy. Tree detection by orthomos...

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Bibliographic Details
Main Authors: Natalya V. Ivanova, Aleksandr V. Lebedev, Maхim P. Shashkov
Format: Article
Language:English
Published: Cherepovets State University 2023-06-01
Series:Трансформация экосистем
Subjects:
kologrivsky forest nature reserve
quadcopter
neural network
agisoft metashape
lidr
rlidar
deepforest
Online Access:http://en.ecosysttrans.com/publikatsii/ecosystem-transformation-volume-6-no-2-2023/evaluation-of-the-quality-of-automatic-tree-detection-using-photogrammetric-canopy-height-models-and/

Internet

http://en.ecosysttrans.com/publikatsii/ecosystem-transformation-volume-6-no-2-2023/evaluation-of-the-quality-of-automatic-tree-detection-using-photogrammetric-canopy-height-models-and/

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