Modeling Loblolly Pine Dominant Height Using Airborne LiDAR

<p>The dominant height of 73 georeferenced field sample plots were modeled from various canopy height metrics derived by means of a small-footprint laser scanning technology, known as light detection and ranging (or just LiDAR), over young and mature forest stands using regression analysis. LiDAR plot metrics were regressed against field measured dominant height using Best Subsets Regression to reduce the number of models. From those models, regression assumptions were evaluated to determine which model was actually the best. The best model included the 1st and 90th height percentiles as predictors and explained 95% of the variance in average dominant height.</p>

Name thesis:degree_name

M.S.

Level thesis:degree_level

Campus Access Thesis

Discipline thesis:degree_discipline

Geography

Year

2010

Author dc:creator

• Maceyka, Andrew

Contributors dc:contributor

• John R Jensen

• Geography
• Social and Behavioral Sciences
• Dominant Height
• Forestry
• Fusion
• Laser Scanning
• Lidar
• Site Index

Statement dc:rights

• © 2010, Andrew Maceyka

Repository record dc:identifier

https://scholarcommons.sc.edu/etd/1293

OAI identifier oai:identifier

oai:scholarcommons.sc.edu:etd-2294