Off-campus Michigan Tech users: To download campus access theses or dissertations, please use the following button to log in with your Michigan Tech ID and password: log in to proxy server
Non-Michigan Tech users: Please talk to your librarian about requesting this thesis or dissertation through interlibrary loan.
Date of Award
2013
Document Type
Master's Thesis
Degree Name
Master of Science in Forest Ecology and Management (MS)
College, School or Department Name
School of Forest Resources and Environmental Science
First Advisor
Robert E Froese
Co-Advisor
Michael J Falkowski
Abstract
We used active remote sensing technology to characterize forest structure in a northern temperate forest on a landscape- and local-level in the Upper Peninsula of Michigan. Specifically, we used a form of active remote sensing called light detection and ranging (e.g., LiDAR) to aid in the depiction of current forest structural stages and total canopy gap area estimation. On a landscape-level, LiDAR data are shown not only to be a useful tool in characterizing forest structure, in both coniferous and deciduous forest cover types, but also as an effective basis for data-driven surrogates for classification of forest structure. On a local-level, LiDAR data are shown to be a benchmark reference point to evaluate field-based canopy gap area estimations, due to the highly accurate nature of such remotely sensed data. The application of LiDAR remote sensed data can help facilitate current and future sustainable forest management.
Recommended Citation
Gebuhr, Timothy J., "Applications of LiDAR remote sensing of forest structure in the Upper Great Lakes region, USA", Master's Thesis, Michigan Technological University, 2013.