Mapping tree genera using discrete LiDAR and geometric tree metrics

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dc.creatorConnie Ko
dc.creatorTarmo K Remmel
dc.creatorGunho Sohn
dc.date2012
dc.date.accessioned2026-07-07T02:36:58Z
dc.descriptionMaps of tree genera are useful in applications including forest inventory, urban planning, and the maintenance of utility transmission line infrastructure. We present a case study of using high density airborne LiDAR data for tree genera mapping along the right of way (ROW) of a utility transmission line corridor. Our goal was to identify single trees that showed or posed potential threats to transmission line infrastructure. Using the three dimensional mapping capability of LiDAR, we derived tree metrics that are related to the geometry of the trees (tree forms). For example, the dominant growth direction of trees is useful in identifying trees that are leaning towards transmission lines. We also derived other geometric indices that are useful in determining tree genera; these metrics included their height, crown shape, size, and branching structures. Our pilot study was situated north of Thessalon, Ontario, Canada along a major utility corridor ROW and surrounding woodlots. The geometric features used for general classification could be categorized into five broad categories related to: 1) lines, 2) clusters, 3) volumes, 4) 3D buffers of points, and 5) overall tree shape that provide parameters as an input for the Random Forest classifier.
dc.formatapplication/pdf
dc.identifier0304-8799
dc.identifierhttps://www.redalyc.org/articulo.oa?id=173124975015
dc.identifier.urihttp://hdl.handle.net/123456789/420482
dc.languageen
dc.publisherUniversidad Austral de Chile
dc.relationhttp://www.redalyc.org/revista.oa?id=1731
dc.rightsBosque
dc.sourceBosque (Chile) Num.3 Vol.33
dc.subjectAgrociencias
dc.titleMapping tree genera using discrete LiDAR and geometric tree metrics
dc.typeartículo científico

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