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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  4/2016 - 1
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An Efficient Tile-Pyramids Building Method for Fast Visualization of Massive Geospatial Raster Datasets

GUO, N. See more information about GUO, N. on SCOPUS See more information about GUO, N. on IEEExplore See more information about GUO, N. on Web of Science, XIONG, W. See more information about  XIONG, W. on SCOPUS See more information about  XIONG, W. on SCOPUS See more information about XIONG, W. on Web of Science, WU, Q. See more information about  WU, Q. on SCOPUS See more information about  WU, Q. on SCOPUS See more information about WU, Q. on Web of Science, JING, N. See more information about JING, N. on SCOPUS See more information about JING, N. on SCOPUS See more information about JING, N. on Web of Science
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,473 KB) | Citation | Downloads: 1,145 | Views: 1,882

Author keywords
geographic information systems, indexing, parallel algorithms, spatial resolution, tiles

References keywords
visualization(11), terrain(10), tile(5), rendering(5), information(5), data(5), graphics(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2016-11-30
Volume 16, Issue 4, Year 2016, On page(s): 3 - 8
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.04001
Web of Science Accession Number: 000390675900001
SCOPUS ID: 85007576472

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Building tile-pyramids is an effective way for publishing and accessing the map visualization service of large-scale geospatial data in the web. But it is a time-consuming task in Geographic Information System (GIS) to build tile-pyramids using traditional methods. In this article, an adaptive multilevel tiles generation method is proposed, which first builds grid index for the geospatial raster dataset, and then generates tiles according to different hierarchy level numbers in the tile-pyramid. With the optimized map rendering engine implemented, a parallel tiles pyramid generation method for large-scale geospatial raster dataset is integrated into a high performance GIS platform. Proved by experiments, the new method shows acceptable applicability, stability and scalability besides its high efficiency.

References | Cited By  «-- Click to see who has cited this paper

[1] X. Wang, F Zhang and L Zhang, "Tile-pyramid Construction and Organization Based on Terrain Data," Mapping and Geospatial Information, vol. 35, no. 6, pp. 49-51, Jun. 2012.

[2] Y. Wang, Y. Pu, L. David and X. Song. "Tile Generation of Multi-Source Projection Vector Data Based on TileStache," Geo-information World, vol. 22, no. 1, pp. 77-81, Jan. 2015.

[3] J. Li, B. Gan, L. Meng, W. Zhang and H. Duan, "Fast Section of Sequential Remote Sensing Image Cache in the Cloud Environment," Journal of Information Sciences, Wuhan University, vol. 40, no. 2, pp. 243-248, Feb. 2015.
[CrossRef] [SCOPUS Times Cited 1]

[4] Y. Zhao and N. Wang, "A Quick Tile Caching Generating Method Based on Dynamic Projection and Scan-Line Cropping," Geomatics Science and Technology, vol. 34, no. 41, pp. 34-41, April 2015.

[5] Z. Du and Q. Li. "A New Method of Storage and Visualization for Massive Point Cloud Dataset," In Proc. CIPA Symposium, Kyoto, Japan, Oct. 2009.

[6] N. Kang, Q. Xu, Y. Zhou and C. Lan, "A Graphic Hardware-based Algorithm for Visualization of Massive Terrain Dataset," Journal of System Simulation, vol. 19, no. 17, pp. 61-64, Sept. 2007.

[7] C. Dai, Y. Zhang, X. Deng and Z. Geng, "Fast Rendering of Massive Textured Terrain Data," In proc. ASPRS Annual Conference, Reno, Nevada, May 2006.

[8] R. Pajarola, "Large Scale Terrain Visualization Using the Restricted Quadtree Triangulation," In Proc. IEEE Visualization Conference, IEEE, pp. 19-26, Oct. 1998.
[CrossRef] [Web of Science Times Cited 133]

[9] L. Hwa, M. Duchaineau and K. I. Joy, "Real-time Optimal Adaptation for Planetary Geometry and Texture: 4-8 Tile Hierarchies," IEEE Transactions on Visualization and Computer Graphics, vol. 11, no. 4, pp. 355-368, June 2005,
[CrossRef] [Web of Science Times Cited 31] [SCOPUS Times Cited 39]

[10] R. Westerteiger, A. Gerndt, B. Hamann, "Spherical terrain rendering using the hierarchical HEALPix grid," In Proc. IRTG, Kaiserslautern, Germany, pp. 13-23, Oct. 2011.
[CrossRef] [SCOPUS Times Cited 10]

[11] P. Lindstrom and V. Pascucci, "Terrain simplification simplified: A general framework for view-dependent out-of-core visualization," IEEE Transaction on Visualization and Computer Graphics, vol. 8, no. 3, pp. 239-254, July-Sept. 2002.
[CrossRef] [Web of Science Times Cited 131] [SCOPUS Times Cited 223]

[12] F. Losasso and H. Hoppe, "Geometry clipmaps: terrain rendering using nested regular grids," ACM Transactions on Graphics, vol. 23, no. 3, pp. 766-773, 2004.
[CrossRef] [Web of Science Times Cited 143] [SCOPUS Times Cited 259]

[13] G. He, W. Xiong, L. Chen, "A MPI-based parallel pyramid building algorithm for large-scale remote sensing images," In Proc. Geoinformatics, 2015 23rd International Conference on. IEEE, pp. 1-4, 2015.
[CrossRef] [SCOPUS Times Cited 2]

[14] A. Liu, Q. Du, D. Zhang, Z. Cai and H. Li, "Organization and Indexing Mechanism for Global Tile Map Data Under Embedded Environment," Geomatics and Information Science of Wuhan University, vol. 40, no. 4, April 2015,
[CrossRef] [SCOPUS Times Cited 2]

[15] C. Qin, L. Zhan and A. Zhu, "How to Apply the Geospatial Data Abstraction Library (GDAL) Properly to Parallel Geospatial Raster I/O," Transactions in GIS, vol. 18, no. 6, pp. 950-957, 2014,
[CrossRef] [Web of Science Times Cited 29] [SCOPUS Times Cited 31]

[16] W. Xiong, L. Chen, "HiGIS: An Open Framework for High Performance Geographic Information System," Advances in Electrical and Computer Engineering, vol.15, no. 3, pp. 123-132, 2015.
[CrossRef] [Full Text] [Web of Science Times Cited 4] [SCOPUS Times Cited 5]

[17] R. Barton, "Modern Algorithms for Real-Time Terrain Visualization on Commodity Hardware," In Proc. Geoinformatics FCE CTU, 2010.

[18] M. Duchaineau, M. Wolinsky, D. Sigeti, M. Miller, M. Mineev-Weinstein and C. Aldrich, "ROAMing Terrain: Real-time Optimally Adapting Meshes," In Proc. IEEE Visualization, pp. 81-88, Oct. 1997.
[CrossRef] [Web of Science Times Cited 277]

[19] R. Pajarola, M. Antonijuan and R. Lario, "QuadTIN: Quadtree Based Triangulated Irregular Networks," In Proc. VISÂ’02: Proceedings of the Conference on Visualization, pp.395-402, Nov. 2002.

[20] M. Clasen and H. Hege, "Terrain Rendering Using Spherical Clipmaps," In Proc. Joint Eurographics - IEEE VGTC Symposium on Visualization, pp.91-98. May 2006.

[21] S. Rusinkiewicz and M. Levoy, "QSplat: A Multiresolution Point Rendering System for Large Meshes," In Proc. International Conference on Computer Graphics and Interactive Techniques, pp. 343-352, 2000,

References Weight

Web of Science® Citations for all references: 748 TCR
SCOPUS® Citations for all references: 572 TCR

Web of Science® Average Citations per reference: 34 ACR
SCOPUS® Average Citations per reference: 26 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2021-04-16 11:03 in 121 seconds.

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Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

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