The design and implementation of grid computing platform for aerosol remote sensing (GCP-ARS)

Jiakui Tang; Aijun Zhang

doi:10.1117/12.761328

26 July 2007 The design and implementation of grid computing platform for aerosol remote sensing (GCP-ARS)

Jiakui Tang, Aijun Zhang

Proceedings Volume 6752, Geoinformatics 2007: Remotely Sensed Data and Information; 675245 (2007) https://doi.org/10.1117/12.761328
Event: Geoinformatics 2007, 2007, Nanjing, China

Abstract

The grid refers to an infrastructure that dynamically aggregates computing resources which are geographically distributed or heterogeneous, and leverages on resources for computational intensive applications. The technology has been applied in many disciplines. However, applications in aerosol retrieval from remote sensing data are just started. Aerosol retrieval using satellite images is to abstract the aerosol information such as aerosol optical thickness, size distribution, which are the key parameters for climate modeling, satellite image atmospheric correction, and environment pollution monitoring, etc, the procedure of which is not only data intensive but also computing intensive. In this paper, we mainly discussed the issues upon the design and implementation of grid computing platform for aerosol remote sensing (GCP-ARS), which is a grid middleware we have proposed to bridge the users and grid computing platform for aerosol retrieval. The concluding remarks and future work direction are given finally.

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Jiakui Tang and Aijun Zhang "The design and implementation of grid computing platform for aerosol remote sensing (GCP-ARS)", Proc. SPIE 6752, Geoinformatics 2007: Remotely Sensed Data and Information, 675245 (26 July 2007); https://doi.org/10.1117/12.761328

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