Predictive Modeling of Black Spruce (Picea mariana (Mill.) B.S.P.) Wood Density Using Stand Structure Variables Derived from Airborne LiDAR Data in Boreal Forests of Ontario-Reference-Cited by-同舟云学术

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Predictive Modeling of Black Spruce (Picea mariana (Mill.) B.S.P.) Wood Density Using Stand Structure Variables Derived from Airborne LiDAR Data in Boreal Forests of Ontario

Published:2016-12-08 Issue:12 Volume:7 Page:311
ISSN:1999-4907
Container-title:Forests
language:en
Short-container-title:Forests

Author:

Pokharel Bharat,Groot Art,Pitt Douglas,Woods Murray,Dech Jeffery

Publisher

MDPI AG

Subject

Forestry

Link

http://www.mdpi.com/1999-4907/7/12/311/pdf

Reference45 articles.

1. Global Forest Resources Assessment 2010: Main Reporthttp://www.fao.org/docrep/013/i1757e/i1757e.pdf

2. Assessment of standing wood and fiber quality using ground and airborne laser scanning: A review

3. Coniferous wood quality in the future: concerns and strategies

4. Wood Formation in Trees

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1. Multifaceted Laser Applications for Wood – A Review from Properties Analysis to Advanced Products Manufacturing;Lasers in Manufacturing and Materials Processing;2023-02-15

2. A Review of Progress and Applications in Wood Quality Modelling;Current Forestry Reports;2022-08-15

3. Modelling wood property variation among Tasmanian Eucalyptus nitens plantations;Forest Ecology and Management;2021-07

4. Estimating Stand Age from Airborne Laser Scanning Data to Improve Models of Black Spruce Wood Density in the Boreal Forest of Ontario;Remote Sensing;2019-08-28

5. Modeling black spruce wood fiber attributes with terrestrial laser scanning;Canadian Journal of Forest Research;2019-06

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