The successful applicant will be in charge of developing, testing and implementing algorithms to extract individual tree information from ALS and TLS point clouds.
In particular, she/he will build on a recent comparative study conducted at our lab (yet unpublished) which has identified the most promising algorithms currently published to segment individual tree crowns in ALS point clouds. One important avenue of improvement lies in the combination of spectral information (hyperspectral imagery acquired along with lidar data) with the geometric features extracted from the point cloud.
She/he will also develop and improve algorithms to extract individual tree characteristics from lidar data including Plant Area Index, tree standing volume.
Algorithms will be implemented in the Computree software as well as R language (LidR package) for efficient dissemination.

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