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DEM_Comp Software for Effective Compression of Large DEM Data Sets  

Kang, In-Gu (Dept. of Geoinformatics, University of Seoul Planning & Policy Division, National Geographic Information Institute)
Yun, Hong-Sik (School of Civil & Environmental Engineering, Sungkyunkwan University)
Wei, Gwang-Jae (Dept. of constructional & environmental system engineering, Sungkyunkwan University)
Lee, Dong-Ha (College of Engineering, Sungkyunkwan University)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.28, no.2, 2010 , pp. 265-271 More about this Journal
Abstract
This paper discusses a new software package, DEM_Comp, developed for effectively compressing large digital elevation model (DEM) data sets based on Lempel-Ziv-Welch (LZW) compression and Huffman coding. DEM_Comp was developed using the $C^{++}$ language running on a Windows-series operating system. DEM_Comp was also tested on various test sites with different territorial attributes, and the results were evaluated. Recently, a high-resolution version of the DEM has been obtained using new equipment and the related technologies of LiDAR (LIght Detection And Radar) and SAR (Synthetic Aperture Radar). DEM compression is useful because it helps reduce the disk space or transmission bandwidth. Generally, data compression is divided into two processes: i) analyzing the relationships in the data and ii) deciding on the compression and storage methods. DEM_Comp was developed using a three-step compression algorithm applying a DEM with a regular grid, Lempel-Ziv compression, and Huffman coding. When pre-processing alone was used on high- and low-relief terrain, the efficiency was approximately 83%, but after completing all three steps of the algorithm, this increased to 97%. Compared with general commercial compression software, these results show approximately 14% better performance. DEM_Comp as developed in this research features a more efficient way of distributing, storing, and managing large high-resolution DEMs.
Keywords
DEM compression algorithm; LiDAR; Lempel-Ziv compression; Huffman coding;
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  • Reference
1 Kidner, D. B. and Smith, D. H. (1992), Compression of digital elevation models by Huffman coding, Computers & Geosciences, Vol. 18, No.8, pp. 1013-1034.   DOI   ScienceOn
2 Kidner, D. B. and Smith, D. H. (2003), Advances in data compression of digital elevation models, Computers & Geosciences, Vol. 29, No.8, pp. 985-1002.   DOI   ScienceOn
3 Welch, T. A. (1984), A technique for high-perfonnallce data compression, IEEE Computer, Vol. 17, No.6, pp. 8-19.
4 RARLAB (2010), rar.exe, http://www.rarsoft.com
5 zlib Group (2010), pkzip.exe, http://www.zlib.net
6 Jacob, Z. and Lempel, A. (1977), A universal algoritlun for sequential data compression, IEEE Transactions on Information Theory, Vol. 23, No.3, pp. 337-343.   DOI
7 Franklin, W. R. (1995), Compressing elevation data, In: Advances in Spatial Databases: Proceedings of the Fourth International Symposium on Large Spatial Databases (SSD 95), Portland, ME, August, Lecture Notes in Computer Science, Vol. 951. Springer, Berlin, pp. 385-404.
8 Boehm, B. W. (1967), Tabular representations of multivariate functions with applications to topographic modeling, In: Proceedings, 22nd ACM National Coriference, Washington DC, pp. 403-415.