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Spatial Data Compression Techniques for GML

Authors: Yuzhen Li; Takashi Imaizumi; Shiro Sakata; Hiroo Sekiya; Jihong Guan;

Spatial Data Compression Techniques for GML

Abstract

The Geography Markup Language (GML) has been introduced to standardize the representation of geographical data in Extensible Markup Language (XML), which makes the exchanging and sharing of geographical information easier. As GML becomes the geospatial language of the Web, the compression of GML files becomes a new challenge to the compression research field. That is because, GML documents tend to be much larger in size than other documents containing the same information, which raising concerns about processing and transportation. In this paper, we first introduce the architecture of the explored GML compressor. Then, analyze the main redundancy characteristic of GML. After that, we explain the precision decrease, delta compression and extrapolation techniques for GML spatial data compression. Experimental results show the efficiency of our proposed methods.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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