scholarly journals Individual Tree Crown Delineation from Airborne Laser Scanning for Diseased Larch Forest Stands

2017 ◽  
Vol 9 (3) ◽  
pp. 231 ◽  
Author(s):  
Chloe Barnes ◽  
Heiko Balzter ◽  
Kirsten Barrett ◽  
James Eddy ◽  
Sam Milner ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Larch Forest ◽  
Forest Stands ◽  
Tree Crown ◽  
Individual Tree ◽  
Airborne Laser ◽  
Crown Delineation ◽  
Tree Crown Delineation

A mixed pixel- and region-based approach for using airborne laser scanning data for individual tree crown delineation in Pinus radiata D. Don plantations

2013 ◽  
Vol 34 (21) ◽  
pp. 7671-7690 ◽  
Author(s):  
Eduardo González-Ferreiro ◽  
Ulises Diéguez-Aranda ◽  
Laura Barreiro-Fernández ◽  
Sandra Buján ◽  
Miguel Barbosa ◽  
...  
Keyword(s):  
Pinus Radiata ◽  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Tree Crown ◽  
Individual Tree ◽  
Mixed Pixel ◽  
Airborne Laser ◽  
Crown Delineation ◽  
Tree Crown Delineation

scholarly journals Airborne laser scanning and tree crown fragmentation metrics for the assessment of Phytophthora ramorum infected larch forest stands

2017 ◽  
Vol 404 ◽  
pp. 294-305 ◽  
Author(s):  
Chloe Barnes ◽  
Heiko Balzter ◽  
Kirsten Barrett ◽  
James Eddy ◽  
Sam Milner ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Phytophthora Ramorum ◽  
Airborne Laser Scanning ◽  
Larch Forest ◽  
Forest Stands ◽  
Tree Crown ◽  
Airborne Laser

scholarly journals Spatial Models With Inter-Tree Competition From Airborne Laser Scanning Improve Estimates of Genetic Variance

2021 ◽  
Vol 11 ◽  
Author(s):  
David Pont ◽  
Heidi S. Dungey ◽  
Mari Suontama ◽  
Grahame T. Stovold
Keyword(s):  
Laser Scanning ◽  
Management Practices ◽  
Spatial Models ◽  
Airborne Laser Scanning ◽  
Tree Level ◽  
Residual Variance ◽  
Spatial Effects ◽  
Individual Tree ◽  
Airborne Laser ◽  
Individual Trees

Phenotyping individual trees to quantify interactions among genotype, environment, and management practices is critical to the development of precision forestry and to maximize the opportunity of improved tree breeds. In this study we utilized airborne laser scanning (ALS) data to detect and characterize individual trees in order to generate tree-level phenotypes and tree-to-tree competition metrics. To examine our ability to account for environmental variation and its relative importance on individual-tree traits, we investigated the use of spatial models using ALS-derived competition metrics and conventional autoregressive spatial techniques. Models utilizing competition covariate terms were found to quantify previously unexplained phenotypic variation compared with standard models, substantially reducing residual variance and improving estimates of heritabilities for a set of operationally relevant traits. Models including terms for spatial autocorrelation and competition performed the best and were labelled ACE (autocorrelation-competition-error) models. The best ACE models provided statistically significant reductions in residuals ranging from −65.48% for tree height (H) to −21.03% for wood stiffness (A), and improvements in narrow sense heritabilities from 38.64% for H to 14.01% for A. Individual tree phenotyping using an ACE approach is therefore recommended for analyses of research trials where traits are susceptible to spatial effects.

Individual tree detection and crown segmentation based on metabolic theory from airborne laser scanning data

2021 ◽  
Vol 15 (03) ◽  
Author(s):  
Honglu Xin ◽  
Yadvinder Malhi ◽  
David A. Coomes ◽  
Yi Lin ◽  
Baoli Liu ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Airborne Laser Scanning ◽  
Metabolic Theory ◽  
Individual Tree ◽  
Tree Detection ◽  
Airborne Laser
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