Student North Carolina State University Raleigh, North Carolina, United States
Accurate forest structural parameters are crucial to forest inventory, and modeling of the carbon cycle and wildlife habitat. Lidar is particularly suitable for the measurement of forest structural parameters. This study proposes a low-cost method for obtaining knee attributes, estimating knee volume, and subsequently the aboveground biomass.
Learning Objectives:
This study proposes a low-cost method of generating a 3D point cloud of bald cypress knees. Point cloud imagery is often a series of points that make up the geometric shape of a tree. It is therefore possible to estimate the volume, biomass, and carbon of the bald cypress knees by knowing the knee location, height, and diameter from the generated 3D point clouds. The research will provide the audience with information about the method of gathering data using low-cost remote sensing tools, especially for understory vegetation.
It will also provide an overview of the uniqueness of this study site as well as the species understudy. It will also provide an overview of the method for estimating the volume of these knees directly from the point cloud using an algorithm as well as using the traditional method with an allometric equation.
The accurate estimation of carbon sequestration in wetlands across different landscapes is critical for developing better carbon budgets. It helps in understanding the importance of the knees in this wetland ecosystem. Furthermore, this study will future serve as a framework for future work on the subject and area (especially a wetland ecosystem).
