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Proceedings Paper

Processing model of multi-scale geospatial data based on genetic algorithms
Author(s): Hongyan Deng; Fang Wu; Qian Zhao; Dongmei Dong
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Paper Abstract

It is one of the most important and far-reaching problems about multi-scale processing and representation of geospatial data in geographic information science. Processing model of multi-scale geospatial data is the key to the problem. After deeply analysing principles of Genetic Algorithms, a processing model of multi-scale geospatial data based on Genetic Algorithms is proposed: 1.determining coding, this model used restricted coding method combined with existing models; 2. making fitness function: the geometric feature of points cluster and the number of points in line are leading guidelines of fitness function; 3. ascertaining local optimization strategy: it takes contrast of points cluster and precision of points in line as the secondary factors, in order to achieve high optimization efficiency. Experiments have demonstrated that the model does well in terms of preserving geometric feature of geospatial data.

Paper Details

Date Published: 7 August 2007
PDF: 8 pages
Proc. SPIE 6754, Geoinformatics 2007: Geospatial Information Technology and Applications, 675417 (7 August 2007); doi: 10.1117/12.764677
Show Author Affiliations
Hongyan Deng, Information Engineering Univ. (China)
Fang Wu, Information Engineering Univ. (China)
Qian Zhao, Information Engineering Univ. (China)
Dongmei Dong, Information Engineering Univ. (China)


Published in SPIE Proceedings Vol. 6754:
Geoinformatics 2007: Geospatial Information Technology and Applications

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