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Geospatial Analytics Dissertation Defense: Vishnu Mahesh Vivek Nanda
December 15, 2022 @ 9:00 am - 10:00 am
Defense Presentation Title: Estimating and Modeling Structural Characteristics of Trees Within Aerial LiDAR Data
Co-Advisors: Dr. Perver Baran, faculty fellow and teaching professor, Center for Geospatial Analytics; Dr. Laura Tateosian, faculty fellow and associate teaching professor, Center for Geospatial Analytics
Abstract: The transparency and shape of tree crowns in urban areas play a critical role in applications such as solar energy potential estimation, urban microclimate modeling, and urban landscape planning and architecture. Data-driven approaches model tree crown attributes using point cloud data, but high-density point clouds are cost-prohibitive. To improve modeling capabilities of widely available medium-resolution aerial LiDAR, this dissertation explores techniques for urban tree modeling, including accounting for seasonal variations in crown transparency, using deep learning to select the crown shape of a tree based on its point cloud, and comparing the performance of algorithms for tree crown delineation.