Comparing different strategies to pre-process 3D point clouds of trees in diverse forests

Student: Francisco Elias

Faculty Mentor: Lisa Bentley

Biology

College of Science, Technology, and Business

Manual cleaning of tree data using software like LiDAR360 and CloudCompare is essential for accurate analysis of forests and trees through 3D scanners. It is important that this cleaning reflects natural observations. This includes correcting algorithm errors and removing irrelevant or obstructive objects. This project applies various cleaning strategies to the same trees to determine whether these methods significantly impact the accuracy of tree cloud representations.