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Grid-enabled high-performance quantitative aerosol retrieval from remotely sensed data
- Source :
-
Computers & Geosciences . Feb2011, Vol. 37 Issue 2, p202-206. 5p. - Publication Year :
- 2011
-
Abstract
- Abstract: As the quality and accuracy of remote-sensing instruments improve, the ability to quickly process remotely sensed data is in increasing demand. Quantitative remote-sensing retrieval is a complex computing process because of the terabytes or petabytes of data processed and the tight-coupling remote-sensing algorithms. In this paper, we intend to demonstrate the use of grid computing for quantitative remote-sensing retrieval applications with a workload estimation and task partition algorithm. Using a grid workflow for the quantitative remote-sensing retrieval service is an intuitive way to use the grid service for users without grid expertise. A case study showed that significant improvement in the system performance could be achieved with this implementation. The results of the case study also give a perspective on the potential of applying grid computing practices to remote-sensing problems. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00983004
- Volume :
- 37
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Computers & Geosciences
- Publication Type :
- Academic Journal
- Accession number :
- 57516824
- Full Text :
- https://doi.org/10.1016/j.cageo.2010.07.004