A High Performance Remote Sensing Product Generation System Based on a Service Oriented Architecture for the Next Generation of Geostationary Operational Environmental Satellites

Remote Sensing

Satya Kalluri⁴  James Gundy²  Brian Haman²  Anthony Paullin²  Paul Van Rompay³  David Vititoe²  Allan Weiner²  Lizhe Wang¹ 

[1] id="af1-remotesensing-07-10385">1NOAA, GOES-R Program Office, Code 417, NASA GSFC, Greenbelt, MD 20771, U;Harris Corporation, Melbourne, FL 32904, USA; E-Mails:;Atmospheric and Environmental Research, Lexington, MA 02421, USA; E-Mail:;NOAA, GOES-R Program Office, Code 417, NASA GSFC, Greenbelt, MD 20771, USA

关键词: GOES-R;    Product Generation;    High Performance Computing (HPC);    Service Oriented Architecture (SOA);   

DOI  :  10.3390/rs70810385

来源: mdpi

【 摘 要 】

The Geostationary Operational Environmental Satellite (GOES) series R, S, T, U (GOES-R) will collect remote sensing data at several orders of magnitude compared to legacy missions, 24 × 7, over its 20-year operational lifecycle. A suite of 34 Earth and space weather products must be produced at low latency for timely delivery to forecasters. A ground system (GS) has been developed to meet these challenging requirements, using High Performance Computing (HPC) within a Service Oriented Architecture (SOA). This approach provides a robust, flexible architecture to support the operational GS as it generates remote sensing products by ingesting and combining data from multiple sources. Test results show that the system meets the key latency and availability requirements for all products.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.