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Proceedings Paper

Implementing computing techniques to accelerate network GIS
Author(s): Chaowei Phil Yang; David Wong; Menas Kafatos; Ruixin Yang
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Paper Abstract

We have witnessed the accumulation of petabyes of geospatial data in the past decades, and, currently, terabytes of data are collected every day. These geospatial data are crucial in supporting decision making and emergency response. It becomes increasingly important to deliver these datasets in a timely fashion to the decision support or emergency response systems. Network GIS provides a vehicle to facilitate this delivering process. But to deliver efficiently such large volume of data and to handle large number of concurrent users, the performance of Network GIS needs to be improved to a level that different types of applications, especially near real time applications, can be satisfied. In this circumstance, we 1) review selected research on improving the performance of Network GIs; 2) provide insides on implementing the techniques; and 3) illustrate how to adopt the techniques in Network GIs. We expect the research and development reported here can be easily adopted by different users to accelerate the performance of various Network GIS software and applications, as well as to support the building of spatial data infrastructure to support the sharing of heterogeneous geospatial information.

Paper Details

Date Published: 28 October 2006
PDF: 17 pages
Proc. SPIE 6418, Geoinformatics 2006: GNSS and Integrated Geospatial Applications, 64181C (28 October 2006); doi: 10.1117/12.712935
Show Author Affiliations
Chaowei Phil Yang, George Mason Univ. (United States)
David Wong, George Mason Univ. (United States)
Menas Kafatos, George Mason Univ. (United States)
Ruixin Yang, George Mason Univ. (United States)


Published in SPIE Proceedings Vol. 6418:
Geoinformatics 2006: GNSS and Integrated Geospatial Applications
Deren Li; Linyuan Xia, Editor(s)

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