• DocumentCode
    144428
  • Title

    24 Hour near real time processing and computation for the JPL Airborne Snow Observatory

  • Author

    Mattmann, Chris A. ; Painter, Thomas ; Ramirez, Paul M. ; Goodale, Cameron ; Hart, Andrew F. ; Zimdars, Paul ; Boustani, Maziyar ; Khudikyan, Shakeh ; Verma, Rishi ; Caprez, Felix Seidel ; Deems, Jeff ; Trangsrud, Amy ; Boardman, Joseph

  • Author_Institution
    Jet Propulsion Lab., California Inst. of Technol., Pasadena, CA, USA
  • fYear
    2014
  • fDate
    13-18 July 2014
  • Firstpage
    5222
  • Lastpage
    5225
  • 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). This paper describes the first year of the project\´s "Snow On" campaign where over a course of 3 months, ASO 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 moved 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 products. This paper describes the Big data processing architecture and data system for ASO.
  • Keywords
    Big Data; geophysics computing; hydrological techniques; ice; real-time systems; remote sensing by laser beam; reservoirs; rivers; snow; Big Data processing architecture; California; Colorado; Hetch Hetchy reservoir; JPL Airborne Snow Observatory; Sierra Nevada; Tuolumne River Basin; Uncompahgre Basin; data system; ice height; imaging spectrometer; mountain snow albedo measurement; scanning LIDAR; snow depth-snow water equivalent; Data processing; Laser radar; Linux; Mobile communication; Snow; Software; ASO; Big Data; JPL; OODT;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
  • Conference_Location
    Quebec City, QC
  • Type

    conf

  • DOI
    10.1109/IGARSS.2014.6947676
  • Filename
    6947676