KAEE’s 48th Annual Conference | Forging Paths for Environmental Education: Community, Conversations, and Creativity
Title Sponsor: Morehead State University | Drs. Ernst and Sara Lane Volgenau College of Education
Land Acknowledgement Morehead State University and the surrounding area are located on the traditional lands of the Yuchee, Shawnee, and Eastern Band of Cherokee. Indigenous peoples have lived on the land we now call Kentucky for over 12,000 years. We want to acknowledge the deep history of this land and the people who still live here today. To learn more about this land and the land you call home, visit native-land.ca.
Amur honeysuckle is one of the most disruptive invasive plants in Central Kentucky’s forested ecosystems and in the surrounding region. Its prolific spread and wide-ranging negative impacts on native flora including altered light regimes, resource consumption and allelopathy make it important to systematically monitor and implement management when possible. However, Amur honeysuckle infestations on public and private land are so extensive that most forested habitats are left untreated and even unassessed. Furthermore, assessments usually require experienced land managers and extensive time to accurately develop specifications leading to efficient management.
Because vegetation of different species can exhibit significant spatial diversity within a relatively small area, airborne multi-spectral and LiDAR data can be an important tool for surveying this complex environment. Additionally, drone-based tools can gather data many times faster than ground-based assessments. Therefore, this study was developed to investigate whether drone-based multi-spectral and LiDAR data can be used to assess Amur honeysuckle composition to develop accurate forest improvement specifications. Drone data were compared to field data gathered on 80 forested plots in Central Kentucky representing percent cover of Amur Honeysuckle in five vertical height classes.
Preliminary results indicate a high degree of comparability between the different methods, particularly in the shorter height classes. Drone-based multi-spectral and LiDAR data can accurately and efficiently map the composition of invasive plants in select forested situations leading to increased forest assessments and management. Results from this research will be used to refine this methodology and expand this technology as a forest assessment tool.
