Remote Sensing (Aug 2015)

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

  • Satya Kalluri,
  • James Gundy,
  • Brian Haman,
  • Anthony Paullin,
  • Paul Van Rompay,
  • David Vititoe,
  • Allan Weiner

DOI
https://doi.org/10.3390/rs70810385
Journal volume & issue
Vol. 7, no. 8
pp. 10385 – 10399

Abstract

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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.

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