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LDAT: A Web Data Visualization Tool for LiDAR Point Cloud Data Analysis
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Light Detection and Ranging (LiDAR) sensors have been employed in many different ways over time and continue to be utilized today. These sensors produce point clouds which are large and complex data sets that are a collection of position points across a 3D space. The research presented in this thesis focuses on the analysis and visualization of LiDAR point cloud data. The data obtained for this project is from LiDAR sensors located on street lights on Virginia Street to analyze traffic information. A web tool was developed to analyze and visualize this data, ensuing in an interactive and readable representation of the data. In order to ensure the effectiveness of the tool, a user study was conducted to test the functionality and assess possible improvements. This thesis aims to provide a template for creating an effective and a useful data visualization tool in an increasingly data-driven society.