[SGVLUG] Meeting on Thu Oct 10th: Big Data 24 Hour Near Real Time Processing and Computation for the JPL Airborne Snow Observatory
Lan Dang
l.dang at ymail.com
Tue Oct 1 13:32:04 PDT 2013
Hi all,
The SGVLUG meets Thursday next week. Big thanks to James for recruiting our presenter for October. This is a reprise of a presentation given at JPL. I missed it due to a meeting conflict, so I'm happy to have another opportunity to see it.
The beginning of the school year is a good time to attract new people. I will give brownies or cookies (literally) to the person(s) who makes and post flyers around Caltech. It might be worth posting at Pasadena City College as well.
SGVLUG meeting, Thu 10/10/2013 7-9pm
WEBSITE: http://sgvlug.org
TOPIC: BIG DATA! 24 Hour Near Real Time Processing and Computation for the JPL Airborne Snow Observatory
PRESENTER: Chris Mattmann
LOCATION: Caltech - Downs 107. The Downs building is across from the tennis courts on California at Arden.
ABSTRACT:
JPL’s Airborne Snow Observatory is an integrated imaging spectrometer and scanning LIDAR for measuring mountain snow albedo, snow depth/snow water equivalent, and ice height (once exposed), led by PI Dr. Tom Painter. The team recently wrapped our “Snow On” campaign where over a course of 3 months, we flew the Tuolumne River Basin, Sierra Nevada, California above the O’Shaughnessy Dam of the Hetch Hetchy reservoir; focusing initial on the Tuolumne, and then moving to weekly flights over the Uncompahgre Basin, Colorado.
To meet the needs of its customers including Water Resource managers who are keenly interested in Snow melt, the ASO team had to develop and end to end 24 hour latency capability for processing spectrometer and LIDAR data from Level 0 to Level 4 (“ish”) products. Fondly referring to these processing campaigns as “rodeos” the team rapidly constructed an open source data processing system at minimal cost and risk that not only met our processing demands, but taught the entire team many lessons about remote sensing of snow and dust properties, algorithm integration, the relationship between computer scientists, and snow hydrologist; flight and engineering teams, geographers, and most importantly lessons about camaraderie that will engender highly innovative and rapid data systems development, and quality science products for years to come.
Chris Mattmann is the Compute Lead for the ASO project and he will humbly tell the story of the Compute processing capability on behalf of the larger team, highlighting contributions of its key members along the way
Bio: http://www.amazon.com/Chris-Mattmann/e/B006V44GIG
Thanks to Junaid for reserving Downs 107.
Lan
(who has now resorted to food bribery to delegate work)
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