3 April 2012 High-performance visual analytics of terrestrial light detection and ranging data on large display wall
Author Affiliations +
Abstract
A typical LIDAR (light detection and ranging) scan contains hundreds of millions of points. As such, the visualization of LIDAR point clouds poses a significant challenge in data analysis. We propose to visualize and process LIDAR point clouds on a large display wall with an array of monitors. This provides researchers with a high-resolution display environment for looking at and studying large data sets. High-resolution large displays offer both global perspectives and local details of point clouds, which is essential in the process of data exploration. The ability to explore, conceptualize, and correlate spatial and temporal changes of topographical records is required for the development of new analytical models that capture the mechanisms contributing toward cliff erosion. Large displays driven by high-performance parallel visualization cluster allow researchers to fully interact with LIDAR point clouds of slopes in Houshanyue mountain and cliff failures observed in Solana Beach in California. In our study, cases studies of visualization based approaches were conducted using large displays in digital immersive environments. Visual analytics techniques such as delineation, segmentation, and classification of features, change detection, and annotation were used to perform erosion assessment. The results showed that the researchers can observe the temporal change of a failure mass effectively in high-resolution large display environments.
© 2012 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2012/$25.00 © 2012 SPIE
Tung-Ju Hsieh, Yang-Lang Chang, and Bormin Huang "High-performance visual analytics of terrestrial light detection and ranging data on large display wall," Journal of Applied Remote Sensing 6(1), 061502 (3 April 2012). https://doi.org/10.1117/1.JRS.6.061502
Published: 3 April 2012
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KEYWORDS
LIDAR

Visualization

Clouds

Visual analytics

Virtual reality

Data processing

OpenGL

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