Silvan: An Immersive Software for Visualization and Mensuration of 3D LiDAR Point Clouds

Abstract

Light Detection and Ranging (LiDAR) point clouds, data representations composed of a collectionof 3D positioned points each with location and intensity data embedded, have numerous applications particularly in the fields of Forestry, Environmental Science, and Remote Sensing. This thesis introduces Silvan, an immersive forestry research software designed for point cloud visualization, segmentation, and mensuration. The main design goals of Silvan are to provide an immersive 3D environment for research in Forestry and Remote Sensing and to provide a mensuration and visualization pipeline for extracting tree metrics including coordinates, tree height, diameter at breast height (DBH), height to live crown, and crown spread. This thesis surveys the current state of research in immersive software for analyzing and visualizing 3D point clouds and focuses on discussing the software implementation details of Silvan and how each feature addresses a limitation of current tree mensuration techniques. This thesis then describes an experimental methodology for gathering and analyzing user feedback and discusses the experimental feedback before finally concluding with discussion of future extensions of Silvan.