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Imaging Spectroscopy Processing Environment on the Cloud (ImgSPEC)
  • +7
  • E. Natasha Stavros,
  • Philip Townsend,
  • George Chang,
  • Hook Hua,
  • Thomas Huang,
  • Justin Merz,
  • Winston Olson-Duvall,
  • William Phyo,
  • Sujen Shah,
  • David Thompson
E. Natasha Stavros
NASA Jet Propulsion Laboratory

Corresponding Author:[email protected]

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Philip Townsend
University of Wisconsin
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George Chang
Jet Propulsion Laboratory
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Hook Hua
Jet Propulsion Laboratory
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Thomas Huang
Jet Propulsion Laboratory
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Justin Merz
University of California Davis
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Winston Olson-Duvall
Jet Propulsion Laboratory, California Institute of Technology
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William Phyo
NASA Jet Propulsion Laboratory
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Sujen Shah
Jet Propulsion Laboratory
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David Thompson
Jet Propulsion Laboratory, California Institute of Technology
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Abstract

The geospatial Imaging Spectroscopy Processing Environment on the Cloud (ImgSPEC; formerly GeoSPEC) pioneers an on-demand science data processing system (SDPS) producing user-customized Level 1 calibrated radiance to Level 3+ data products in anticipation for the 2017-2027 Earth Decadal Survey prioritized spaceborne global imaging spectrometer to advance the study of Surface Biology and Geology (SBG). SBG data volumes (~20 TB/day) of high dimensionality (>224 bands) would be infeasible to download and the breadth of applications of the data across dozens of disciplines presents a need to evolve the traditional NASA SDPS. ImgSPEC streamlines processing data into key SBG observables that have demonstrated algorithms at local-to-regional scales and may vary locally. As such, a traditional, monolithic SDPS could not fully exploit the information in SBG measurements. To remove this barrier to use, ImgSPEC demonstrates an on-demand SDPS prototype that improves imaging spectroscopy data discovery, access, and utility enabling shared knowledge transfer from advanced imaging spectroscopy users to less experienced users such as decision makers and the general public. We test three use cases: 1) standard data processing workflows, 2) customized variants of standard workflows, and 3) algorithm development of new workflows. We create collaborative algorithm development environments that offer services typically restricted to NASA SDPSs such as data product provenance and bulk processing. We leverage existing NASA-funded information technologies such as the hybrid on-premise/ cloud science data system (HySDS), the Multi-mission Algorithm and Analysis Platform (MAAP), ECOSIS – a crowd-sourced spectral database, and ECOSML – a crowd-sourced model database. We demonstrate ImgSPEC on the Terrestrial Ecosystem use case processing through to foliar traits and fractional cover, thus aligning with driving thrusts for the SBG Science and Applications Communities.