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Remote Sensing Working Group:
Summary of Goals, Progress, and Future Activities
Amy Braverman
Jet Propulsion Laboratory, California Institute of Technology
May 14, 2018
1
Outline
From where did we start? A (very) short review of the Opening Workshop
talks last fall.
Goals of the Remote Sensing Working Group
Subgroups
Mid-year workshop
Future activities
Technical talks by sub-group leads
2
Last fall
Noel’s talk: broad overview of the role of statistical principles in remote
sensing
Dan’s talk: NASA’s remote sensing data processing and distribution
infrastructure
Matthias’ talk: framework for spatial statistics suitable for massive and
distributed data
3
Goals
How do we connect these concepts in a way that is specific enough to
suggest tangible research to pursue?
Big constraint: can’t move (all) data
Points to a need to flexibly trade-off inferential quality against cost
(computational and transportation, etc.)
4
Remote Sensing Working Group subgroups
Spatial Retrievals
Spatial “X" (Lead: Jon Hobbs and Matthias Katzfuss)
Spatial “Y" (Lead: Zhengyan Zhu)
Optimization (Lead: Jessica Matthews)
Emulators (Lead: Emily Kang)
Theory of Data Systems (ToDS; lead: Amy Braverman)
5
Mid-program workshop
Remote Sensing, Uncertainty Quantification, and a Theory of Data Systems:
At Caltech, February 12 – 14, 2018
Co-sponsored by JPL and Caltech
About 50 attendees (about 20 from SAMSI, 2 international/other, 1 NASA
(ESTO), 2 NOAA, rest from JPL and Caltech)
Goal: how to bring modern spatial statistical methodology to bear on
massive distributed remote sensing data sets? Requires a quantitative
framework for balancing uncertainty against costs.
6
Future activities
All subgroups intend to continue meeting past the end of the program.
(Sub-group leads will discuss technical objectives.)
OCO-2 and OCO-3 missions to provide support for some continuing
research related to Spatial “X".
NASA ESTO has commissioned a study ($100K award): Spatial Data
Analysis Systems of Opportunity to follow-up on the workshop at Caltech.
Maggie Johnson coming to JPL for her second post-doc year. (Many
thanks to Bill Tolone (UNCC), George Djorgovski (Caltech), and Dan
Crichton (JPL).
7
Technical talks
Jon Hobbs (Spatial “X")
Zhengyuan Zhu (Spatial “Y")
Jessica Matthews (Optimization)
Emily Kang (Emulators)
Maggie Johnson (ToDS)
8
Many thanks to all members of the Remote Sensing Working Group for a
stimulating and productive program!
Special thanks to Jon Hobbs for providing an interface to the OCO-2 mission.
©2018 California Institute of Technology. Government sponsorship
acknowledged.
9

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CLIM: Transition Workshop - Introduction to Remote Sensing Working Group - Amy Braverman, May 14, 2018

  • 1. Remote Sensing Working Group: Summary of Goals, Progress, and Future Activities Amy Braverman Jet Propulsion Laboratory, California Institute of Technology May 14, 2018 1
  • 2. Outline From where did we start? A (very) short review of the Opening Workshop talks last fall. Goals of the Remote Sensing Working Group Subgroups Mid-year workshop Future activities Technical talks by sub-group leads 2
  • 3. Last fall Noel’s talk: broad overview of the role of statistical principles in remote sensing Dan’s talk: NASA’s remote sensing data processing and distribution infrastructure Matthias’ talk: framework for spatial statistics suitable for massive and distributed data 3
  • 4. Goals How do we connect these concepts in a way that is specific enough to suggest tangible research to pursue? Big constraint: can’t move (all) data Points to a need to flexibly trade-off inferential quality against cost (computational and transportation, etc.) 4
  • 5. Remote Sensing Working Group subgroups Spatial Retrievals Spatial “X" (Lead: Jon Hobbs and Matthias Katzfuss) Spatial “Y" (Lead: Zhengyan Zhu) Optimization (Lead: Jessica Matthews) Emulators (Lead: Emily Kang) Theory of Data Systems (ToDS; lead: Amy Braverman) 5
  • 6. Mid-program workshop Remote Sensing, Uncertainty Quantification, and a Theory of Data Systems: At Caltech, February 12 – 14, 2018 Co-sponsored by JPL and Caltech About 50 attendees (about 20 from SAMSI, 2 international/other, 1 NASA (ESTO), 2 NOAA, rest from JPL and Caltech) Goal: how to bring modern spatial statistical methodology to bear on massive distributed remote sensing data sets? Requires a quantitative framework for balancing uncertainty against costs. 6
  • 7. Future activities All subgroups intend to continue meeting past the end of the program. (Sub-group leads will discuss technical objectives.) OCO-2 and OCO-3 missions to provide support for some continuing research related to Spatial “X". NASA ESTO has commissioned a study ($100K award): Spatial Data Analysis Systems of Opportunity to follow-up on the workshop at Caltech. Maggie Johnson coming to JPL for her second post-doc year. (Many thanks to Bill Tolone (UNCC), George Djorgovski (Caltech), and Dan Crichton (JPL). 7
  • 8. Technical talks Jon Hobbs (Spatial “X") Zhengyuan Zhu (Spatial “Y") Jessica Matthews (Optimization) Emily Kang (Emulators) Maggie Johnson (ToDS) 8
  • 9. Many thanks to all members of the Remote Sensing Working Group for a stimulating and productive program! Special thanks to Jon Hobbs for providing an interface to the OCO-2 mission. ©2018 California Institute of Technology. Government sponsorship acknowledged. 9