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International Symposium on Spatial Databases

SSD 1995: Advances in Spatial Databases pp 385–404Cite as

Compressing Elevation Data

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 951))

Abstract

This paper compares several, text and image, lossless and lossy, compression techniques for regular gridded elevation data, such as DEMs. Sp_compress and progcode, the best lossless methods average 2.0 bits per point on USGS DEMs, about half the size of gzipped files, and 6.2 bits per point on ETOPO5 samples. Lossy compression produces even smaller files at moderate error rates. Finally, some technques for compressing TINs will be introduced.

Partial support was provided by NSF grant CCR-9102553.

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Author information

Authors and Affiliations

  1. Electrical, Computer, and Systems Engineering Dept., 6026 JEC, Rensselaer Polytechnic Institute, 12180-3590, Troy, New York

    Wm Randolph Franklin

Authors
  1. Wm Randolph Franklin
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Editor information

Max J. Egenhofer John R. Herring

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© 1995 Springer-Verlag Berlin Heidelberg

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Franklin, W.R. (1995). Compressing Elevation Data. In: Egenhofer, M.J., Herring, J.R. (eds) Advances in Spatial Databases. SSD 1995. Lecture Notes in Computer Science, vol 951. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60159-7_23

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  • DOI: https://doi.org/10.1007/3-540-60159-7_23

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60159-3

  • Online ISBN: 978-3-540-49536-9

  • eBook Packages: Springer Book Archive

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