Title of Submission
Semi-Arid Ecosystem Plant Functional Type and LAI from Small Footprint Waveform Lidar
Degree Program
Geosciences, PhD
Major Advisor Name
Nancy Glenn
Type of Submission
Scholarly Poster
Abstract
Plant functional traits such as vegetation structure, density, and composition are indicators of ecosystem response to climate and human driven disturbances. We used small footprint waveform lidar with an ensemble random forest approach to differentiate the functional traits in a western US semi-arid ecosystem. We introduced a new gap fraction based leaf area index (LAI) estimator using lidar derived parameters. Results showed 60% - 89% accuracies discriminating plant functional types and estimating shrub LAI. These results imply the potential of waveform lidar to quantify plant functional traits in low-stature vegetation which is useful to assess climate impact in semi-arid ecosystems.
Funding Information
NESSF 17-EARTH17F-0209, NASA TE NNX14AD81G