Led by: James Stroud and Jeffrey Cannon;
Graduate Researcher: John Hagood, Amir Hossein Alikhah Mishamandani, Fan Yang
Computational Expert: Baidik Chandera, Dory Peters
The project aims to develop innovative algorithms for processing and analyzing terrestrial LiDAR (Light Detection and Ranging) scans of natural vegetation, with the goal of creating comprehensive, open-source software packages in Python or R. This project will focus on creating novel computational methods to extract, process, and analyze complex vegetation structure data from LiDAR point clouds, enabling more accurate and automated assessment of natural vegetation characteristics. We are especially interested in segmenting and measuring elements of branch and vegetation structure. By developing these algorithms into accessible software packages, the project will provide the scientific community with robust tools for vegetation analysis, supporting applications in ecology, forestry, and environmental monitoring.