Theses and Dissertations
Issuing Body
Mississippi State University
Advisor
Frey, Brent R.
Committee Member
Renninger, Heidi J.
Committee Member
Evans, David L.
Date of Degree
5-3-2019
Document Type
Graduate Thesis - Open Access
Major
Forestry
Degree Name
Master of Science
College
College of Forest Resources
Department
Department of Forestry
Abstract
Light Detection and Ranging (LiDAR) is increasingly common in forestry applications, yet relatively little research has evaluated its use in quantifying carbon stocks in afforested bottomland hardwood forests. This study relates forest structural field measurements to metrics derived from low pulse density LiDAR data to assess the use of LiDAR in characterization of planted bottomland hardwood oak stands. Univariate and multivariate linear regressions were performed with field and LiDAR variables to determine relationships. The height-related field dependent variables average height, maximum height, and individual tree volume had the highest adjusted R-squared values of 0.5-0.6 (P<0.0001) for the univariate models and adjusted R-squared values of 0.70-0.79 for the multivariate models. These findings suggest that low-density LiDAR is capable of assessing forest structure and suggests that further research evaluating LiDAR quantification of bottomland hardwood carbon stocks is warranted.
URI
https://hdl.handle.net/11668/21119
Recommended Citation
Anderson, Madelyn Paige, "LiDAR Measurements of Afforested Bottomland Hardwoods in the Lower Mississippi Alluvial Valley" (2019). Theses and Dissertations. 2944.
https://scholarsjunction.msstate.edu/td/2944
Comments
carbon stocks||low-pulse density||forest structure||broad-leaf||floodplain forest||oaks||Quercus