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Parallel viewshed analysis on a PC cluster system using triple-based irregular partition scheme

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Abstract

Using digital elevation models (DEMs), viewshed analysis algorithms determine the visibility of each point on the terrain at a given location in space. As a data-parallel algorithm, real-time viewshed analysis from grid DEM poses a practical challenge to personal computer (PC) users, particularly when dealing with higher resolution and accuracy of large terrain data. Therefore, this paper presents a universal domain decomposition algorithm based on an equal-area strategy for the parallel viewshed analysis on a PC cluster system. The approach uses a scan-line filling method for data partitioning of the irregular bounding polygon of the terrain. The terrain data are divided into sectors of the same area that are connected by the viewpoint and the region vertices, ignoring the null value (or NODATA) points. Furthermore, each sector is assigned to one processor and is organized in the form of triples composed of location and elevation at one point. An index of triples is built to store all of the locations of terminal vertices row-by-row and thus the random access of any point is achieved by using the offsets in each row. Two commonly applied viewshed algorithms, namely, “reference plane” and “Xdraw” algorithms are employed to verify the performance. In addition, two experiments focus on evaluating the efficiency performance and comparing traditional implementation, respectively. Experimental results demonstrate a significant performance improvement compared with the sequential computing method. The memory usage gradually decreases as the number of processors increases. Based on the equal-area decomposition, partitions in terms of sectors can guarantee a suitable load balance. Additional benefits of the proposed solution also include high storage efficiency and program portability.

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Acknowledgments

This work was supported by the Major Scientific Research Projects of Universities in Jiangsu Province (No. 13KJA170001), the Priority Academic Program Development of Jiangsu Higher Education Institutions (No. 164320H101), the National Natural Science Foundation of China (No. 41401237, No. 41571383), the Jiangsu Province Science Foundation for Youths (No. BK20141053), and the Field Frontier Program of the Institute of Soil Science, Chinese Academy of Sciences (No. ISSASIP1624). The cluster support provided by Dr. Gan-Lin Zhang, Institute of Soil Science, Chinese Academy of Sciences, is gratefully acknowledged.

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Authors and Affiliations

  1. Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing, China

    Xiao-Dong Song, Guo-An Tang, Xue-Jun Liu, Wan-Feng Dou & Fa-Yuan Li

  2. State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China

    Xiao-Dong Song

  3. State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing, China

    Guo-An Tang, Xue-Jun Liu, Wan-Feng Dou & Fa-Yuan Li

  4. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China

    Guo-An Tang, Xue-Jun Liu, Wan-Feng Dou & Fa-Yuan Li

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  1. Xiao-Dong Song
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  2. Guo-An Tang
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  3. Xue-Jun Liu
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Correspondence to Guo-An Tang.

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Communicated by: H. A. Babaie

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Song, XD., Tang, GA., Liu, XJ. et al. Parallel viewshed analysis on a PC cluster system using triple-based irregular partition scheme. Earth Sci Inform 9, 511–523 (2016). https://doi.org/10.1007/s12145-016-0263-5

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  • DOI: https://doi.org/10.1007/s12145-016-0263-5

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