Research on Generalization Technology of Spatial Line Vector Data

Data simplification is an important factor of the spatial data generalization, which is an effective way to improve rendering speed. This paper firstly introduces the algorithms classification of the spatial line vector data in two-dimensional environment, and then it emphatically summarizes and ana...

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Published inApplied Mechanics and Materials Vol. 687-691; no. Manufacturing Technology, Electronics, Computer and Information Technology Applications; pp. 1153 - 1156
Main Authors Zhang, Xiao Yu, Dou, Shi Qing
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 01.11.2014
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ISBN3038353280
9783038353287
ISSN1660-9336
1662-7482
1662-7482
DOI10.4028/www.scientific.net/AMM.687-691.1153

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Summary:Data simplification is an important factor of the spatial data generalization, which is an effective way to improve rendering speed. This paper firstly introduces the algorithms classification of the spatial line vector data in two-dimensional environment, and then it emphatically summarizes and analyzes the advantages and disadvantages of the algorithms which can be used in the spatial line vector data simplification in the three dimensional environment. The three-dimensional Douglas-Peucker algorithm with a certain overall characteristics has wide application prospect. The simplified algorithms in 3D environment represent the development direction of the future. But at present, the existing data simplification algorithms in 3D environment are not mature enough, they all have certain advantages and disadvantages, this makes their use is limited by a certain extent. The application of these simplified algorithms in 2D and 3D is mostly on multi-resolution expression. Developing from 2D algorithm to the direction of 3D algorithm, it also lists many works and problems that need us to do and study in the future.
Bibliography:Selected, peer reviewed papers from the 2014 International Conference on Manufacturing Technology and Electronics Applications (ICMTEA 2014), November 8-9, 2014, Taiyuan, Shanxi, China
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ISBN:3038353280
9783038353287
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.687-691.1153