GPU-based Lightweight Parallel Processing Toolset for LiDAR Data for Terrain Analysis
Publication Date
3-22-2019
Document Type
Article
Organizational Units
College of Natural Science and Mathematics, Geography and the Environment, Daniel Felix Ritchie School of Engineering and Computer Science, Computer Science
Keywords
LiDAR, Parallel processing, Graphics processing units
Abstract
LiDAR products are provided at fine spatial resolutions and the data volume can be huge even for a small study region. Therefore, we have developed a parallel computing toolset that is built on Graphics Processing Units (GPUs) computing techniques to speed up the computational processes on LiDAR products. The toolset provides a set of fundamental processing functions for LiDAR point cloud data, serving as a basic toolkit to derive terrain data products. With this toolset, scientists with limited access to high-end computing facilities can still perform efficient analysis of LiDAR products without dealing with the technical complexity of developing and deploying tools for these products. We have integrated data decomposition methods to handle files that exceed the memory capacity of GPU devices. Preliminary results show that GPU-based implementation yields high speedup ratios and can handle files with a maximum size of 8 GB.
Publication Statement
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Recommended Citation
Li, Jing, et al. “GPU-Based Lightweight Parallel Processing Toolset for LiDAR Data for Terrain Analysis.” Environmental Modelling & Software : with Environment Data News, vol. 117, 2019, pp. 55–68. doi: 10.1016/j.envsoft.2019.03.014.