Date of Award
2019
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Earth System Science
Committee Chair
Robert Griffin
Committee Member
Emil Cherrington
Committee Member
Thomas Sever
Subject(s)
Optical radar, Forest biomass--Remote sensing, University of Ala.bama in Huntsville
Abstract
Urban tree biomass is essential for the vitality of the surrounding ecosystem. This study utilized field measurements and aerial Light Detection and Ranging (LiDAR) remote sensing to estimate biomass within The University of Alabama in Huntsville (UAH) campus to assess the importance of biomass on a school campus. LiDAR-derived canopy characteristics were calculated and used in a linear regression analysis in conjunction with in situ measured biomass to yield biomass equations for 14 tree species found on the UAH campus. The regression models had a high fit (R2 = 0.73-0.98) for most species. Some species such as the Pinus taeda, Pinus echinata, and Lagerstroemia indica had lower R2 values (0.26-0.43) likely due to overlapping canopies; a limitation in urban biomass studies. This methodology is an avenue for urban planners to estimate biomass without intensive and costly field surveys, especially in Northern Alabama where there is a lack of urban biomass research.
Recommended Citation
Klug, Maggi, "Utilizing LiDAR to quantify aboveground tree biomass within an urban university" (2019). Theses. 292.
https://louis.uah.edu/uah-theses/292