New method adaptive to geospatial information acquisition and share based on grid

Yingchun Fu; Xiuxiao Yuan

doi:10.1117/12.657354

4 January 2006 New method adaptive to geospatial information acquisition and share based on grid

Yingchun Fu, Xiuxiao Yuan

Proceedings Volume 5985, International Conference on Space Information Technology; 59851S (2006) https://doi.org/10.1117/12.657354
Event: International Conference on Space information Technology, 2005, Wuhan, China

Abstract

As we all know, it is difficult and time-consuming to acquire and share multi-source geospatial information in grid computing environment, especially for the data of different geo-reference benchmark. Although middleware for data format transformation has been applied by many grid applications and GIS software systems, it remains difficult to on demand realize spatial data assembly jobs among various geo-reference benchmarks because of complex computation of rigorous coordinate transformation model. To address the problem, an efficient hierarchical quadtree structure referred as multi-level grids is designed and coded to express the multi-scale global geo-space. The geospatial objects located in a certain grid of multi-level grids may be expressed as an increment value which is relative to the grid central point and is constant in different geo-reference benchmark. A mediator responsible for geo-reference transformation function with multi-level grids has been developed and aligned with grid service. With help of the mediator, a map or query spatial data sets from individual source of different geo-references can be merged into an uniform composite result. Instead of complex data pre-processing prior to compatible spatial integration, the introduced method is adaptive to be integrated with grid-enable service.

Citation Download Citation

Yingchun Fu and Xiuxiao Yuan "New method adaptive to geospatial information acquisition and share based on grid", Proc. SPIE 5985, International Conference on Space Information Technology, 59851S (4 January 2006); https://doi.org/10.1117/12.657354

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KEYWORDS

Data modeling

Databases

Image processing

Performance modeling

Data conversion

Composites

Computing systems

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