Construction of multi-source geospatial vector data association relation based on topic maps

Jingli Jiang; Siheng Ren

doi:10.1117/12.2604626

5 October 2021 Construction of multi-source geospatial vector data association relation based on topic maps

Jingli Jiang, Siheng Ren

Proceedings Volume 11911, 2nd International Conference on Computer Vision, Image, and Deep Learning; 1191123 (2021) https://doi.org/10.1117/12.2604626
Event: 2nd International Conference on Computer Vision, Image and Deep Learning, 2021, Liuzhou, China

Abstract

Implicit correlations exist between multi-source geospatial data, the association relation can’t be displayed intuitively and retrieved effectively, which leads to the difficulty in data utilization and data sharing. Aimed at this situation, association relation topic maps is constructed using topic map tools Ontopia in this article. Besides, to increase the efficiency of building topic map, the automatic generation algorithm of association relation topic map which based on C# is proposed. The result of experiment shows that the association relation topic map can be constructed correctly by using Ontopia tools and automatic generation algorithm.

Citation Download Citation

Jingli Jiang and Siheng Ren "Construction of multi-source geospatial vector data association relation based on topic maps", Proc. SPIE 11911, 2nd International Conference on Computer Vision, Image, and Deep Learning, 1191123 (5 October 2021); https://doi.org/10.1117/12.2604626

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