Considerations for assessing functional forest diversity in high-dimensional trait space derived from drone-based lidar

HIGHLIGHTS

  • who: Leonard Hambrecht et al. from the School of Geography, Planning, and Spatial Sciences, University of Tasmania, Hobart, TAS, Australia have published the research work: Considerations for Assessing Functional Forest Diversity in High-Dimensional Trait Space Derived from Drone-Based Lidar, in the Journal: (JOURNAL) of 19/09/2019
  • what: This study investigates whether kernel density estimator (KDE) or one-class support vector machine (SVM) may be computationally more efficient in calculating Four traits were selected for input into the TPD: canopy height effective number of layers plant to ground ratio and box dimensions. The . . .

     

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