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2021 ESIP Winter Meeting (Jan. 26th-29th, 2021)
https://2021esipwintermeeting.sched.com/

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The meeting was conducted via Qiqochat, using Zoom for presentations and breakout sessions.
Slido was used to capture audience questions and to conduct the two polls.

ESIP Session Links

• Session page on ESIP Sched
• ESIP Session notes page (live) (pdf)

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• Available on the ESIP session notes page

Agenda

• Welcome
  • Ed Armstrong (LP.DAAC, ESO): Introductory presentationSlide Poll
  • Audience poll #1 on ARD:
    
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  • Audience poll #2 on ARD:
    
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• Presentations
  • Ignacio Zuleta (ARD Zone): Virtual constellations, ARD and sensor fusion: the future of earth observation [Missed presentation, Technical Issues]
  • Steven Labahn (USGS, CEOS Land Surface Imaging Virtual Constellation (LSI-VC) Co-Lead): CEOS Analysis Ready Data (ARD)
  • Chris Lynnes (NASA): Analysis Ready Satellite Data in NASA’s EOSDIS
• Questions to the speakers (captured from the Slido tool and the Zoom chat)
  • Steven Labahn (USGS, CEOS Land Surface Imaging Virtual Constellation (LSI-VC) Co-Lead): CEOS Analysis Ready Data (ARD)
  • Does CEOS provide more granularity on what ‘use with ease and confidence’ means for a new user?
  • Reply: Ease of use - guaranteed that product is met with a certain kind of quality and standard. Showed scorecard summary tables - level of assurance around what a data product contains 
  • Are all data transformations (data and code), from original to ARD, saved? What system is used to save this history?
  • ARD is a powerful "holy grail" and CARD4L is so well-defined, is there a danger that people might think ARD is a solved problem
    • Reply: CARD4L is not trying to define all of ARD
  • Why did you decide not to specify the metadata format & data packaging? That seems like a key usability requirement.
  • In STAC, we are currently working on creating CARD4L extensions, and there are two open PRs for SAR and Optical.
  • Can you say a few more words about COAST?
  • Chris Lynnes (NASA): Analysis Ready Satellite Data in NASA’s EOSDIS
  • pixels expand near the pole simply because of the projection used. the FOVs are function of off-nadir angle only
  • One of the challenges is that the "processing level" definitions appear to be different between land and atmosphere... where in land Level-2 is gridded/ground referenced whereas that's Level-3 in the atmosphere domain
  • How might the ESIP endorsed Analytics definition be updated with ARD concepts? https://datascience.codata.org/articles/10.5334/dsj-2017-006/
  • Confounding factors?
  • In terms of "easy to used spatial characteristics", have you considered using a standardized hierarchical spatial indexing system like H3? see H3geo.org.
  • How did you create AIRS L2G time-aggregated data before you run PANDAS on it? Did you store everything in memory or save it in an intermediate format?
• Breakout into 4 rooms