Journal
FORESTRY CHRONICLE
Volume 84, Issue 6, Pages 827-839Publisher
CANADIAN INST FORESTRY
DOI: 10.5558/tfc84827-6
Keywords
light detection and ranging; LiDAR; airborne laser scanning; forest modelling; remote sensing; forest stand variables; Great Lakes - St. Lawrence forest
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Funding
- Tembec Inc.
- Ontario Ministry of Natural Resources
- Canadian Forest Service
- Enhanced Forest Science Productivity Fund
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Models were developed to predict forest stand variables for common species of the Great Lakes - St. Lawrence forest of central Ontario, Canada from light detection and ranging (LiDAR) data. Stands that had undergone various ranges of partial harvesting or initial spacing treatments from multiple geographic sites were considered. A broad forest stratification was adopted and consisted of. (i) natural hardwoods; (ii) natural conifers; and (iii) plantation conifers. Stand top height (R(2) = 0.96, 0.98, and 0.98); average height (R(2) = 0.86, 0.76, and 0.98); basal area (R(2) = 0.80, 0.80, and 0.85); volume (R(2) = 0.89, 0.81, and 0.91); quadratic mean diameter (R(2) = 0.80, 0.68, and 0.83); and density (R(2) = 0.74, 0.71, and 0.73) were predicted from low density (i.e., 0.5 point m(-2)) LiDAR data for these 3 strata, respectively.
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