Remote Sensing Applications and Decision Support

High-performance parallel approaches for three-dimensional light detection and ranging point clouds gridding

[+] Author Affiliations
Permata Nur Miftahur Rizki, Sangyoon Oh

Ajou University, Department of Computer Engineering, 206 Worldcup-ro, Suwon 16499, Republic of Korea

Heezin Lee

University of California at Berkeley, National Center for Airborne Laser Mapping, Department of Earth and Planetary Science, McCone Hall #497, Berkeley, California 94720, United States

Minsu Lee

Ewha Womans University, Department of Computer Science and Engineering, 52 Ewhayeodae-gil, Seoul 03760, Republic of Korea

J. Appl. Remote Sens. 11(1), 016011 (Jan 24, 2017). doi:10.1117/1.JRS.11.016011
History: Received October 11, 2016; Accepted December 27, 2016
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Abstract.  With the rapid advance of remote sensing technology, the amount of three-dimensional point-cloud data has increased extraordinarily, requiring faster processing in the construction of digital elevation models. There have been several attempts to accelerate the computation using parallel methods; however, little attention has been given to investigating different approaches for selecting the most suited parallel programming model for a given computing environment. We present our findings and insights identified by implementing three popular high-performance parallel approaches (message passing interface, MapReduce, and GPGPU) on time demanding but accurate kriging interpolation. The performances of the approaches are compared by varying the size of the grid and input data. In our empirical experiment, we demonstrate the significant acceleration by all three approaches compared to a C-implemented sequential-processing method. In addition, we also discuss the pros and cons of each method in terms of usability, complexity infrastructure, and platform limitation to give readers a better understanding of utilizing those parallel approaches for gridding purposes.

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© 2017 Society of Photo-Optical Instrumentation Engineers

Citation

Permata Nur Miftahur Rizki ; Heezin Lee ; Minsu Lee and Sangyoon Oh
"High-performance parallel approaches for three-dimensional light detection and ranging point clouds gridding", J. Appl. Remote Sens. 11(1), 016011 (Jan 24, 2017). ; http://dx.doi.org/10.1117/1.JRS.11.016011


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