If you are experiencing problems downloading PDF or HTML fulltext, our helpdesk recommend clearing your browser cache and trying again. If you need help in clearing your cache, please click here . Still need help? Email help@ingentaconnect.com

Prediction of Wood Fiber Attributes from LiDAR-Derived Forest Canopy Indicators

$29.50 plus tax (Refund Policy)

Buy Article:


We investigated the potential use of airborne light detection and ranging (LiDAR) data to predict key wood fiber properties from extrinsic indicators in lodgepole pine leading forest stands located in the foothills of central Alberta, Canada. Six wood fiber attributes (wood density, cell perimeter, cell coarseness, mature fiber length, microfibril angle, and modulus of elasticity) were measured at 21 plots, and with use of data reduction techniques, two components of wood properties were derived: wood strength, stiffness, and fiber yield and fiber strength and smoothness. These wood fiber components were then compared with extrinsic indicators of wood characteristic-derived LiDAR-estimated topographic morphology, tree height, and canopy light metrics. The first principal component indicating wood strength and stiffness was significantly correlated to the depth of different canopy zones (or light regimes; r 2 = 0.55, P < 0.05). The second component, related to fiber strength and smoothness, was significantly correlated to the height of the canopy and canopy thickness (r 2 = 0.65, P < 0.05). The results indicate that airborne LiDAR attributes can explain about half of the observed variance in intrinsic wood fiber attributes, which is approximately 5‐10% less than that explained by growth-related field-measured variables such as diameter increment and height. This reduction in explained variance can be balanced by the opportunities for much broader spatial characterizations of wood quantity and quality at the stand and landscape levels.

Keywords: LiDAR; canopy structure; light regime; lodgepole pine; wood fiber

Document Type: Research Article

DOI: http://dx.doi.org/10.5849/forsci.11-074

Publication date: April 1, 2013

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
  • Membership Information
  • ingentaconnect is not responsible for the content or availability of external websites



Share Content

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more