Special Section on High-Performance Computing in Applied Remote Sensing: Part 2

High-performance visual analytics of terrestrial light detection and ranging data on large display wall

[+] Author Affiliations
Tung-Ju Hsieh

National Taipei University of Technology, Department of Computer Science and Information Engineering, No. 1, Section 3, Chung-Hsiao E. Road, Taipei 10608, Taiwan

Yang-Lang Chang

National Taipei University of Technology, Department of Electrical Engineering, No. 1, Section 3, Chung-Hsiao E. Road, Taipei 10608, Taiwan

Bormin Huang

University of Wisconsin-Madison, Space Science and Engineering Center, 1225 W. Dayton Street, Madison, Wisconsin 53706

J. Appl. Remote Sens. 6(1), 061502 (Apr 03, 2012). doi:10.1117/1.JRS.6.061502
History: Received November 4, 2011; Revised December 31, 2011; Accepted January 17, 2012
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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.

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© 2012 Society of Photo-Optical Instrumentation Engineers

Citation

Tung-Ju Hsieh ; Yang-Lang Chang and Bormin Huang
"High-performance visual analytics of terrestrial light detection and ranging data on large display wall", J. Appl. Remote Sens. 6(1), 061502 (Apr 03, 2012). ; http://dx.doi.org/10.1117/1.JRS.6.061502


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