Advertisement

SALSA: A Software System for Data Management and Analytics in Field Spectrometry

  • Baljeet Malhotra
  • John A. Gamon
  • Stéphane Bressan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7338)

Abstract

Field spectrometry is emerging as an important tool in the study of the dynamics of the biosphere and atmosphere. Large amounts of data are now collected from spectrometers mounted on towers, robotic trams and other platforms. These data are crucial for verifying not only the optical data captured by satellites and airborne systems but also to validate the flux measurements that track ecosystem-atmosphere gas exchanges, the “breathing of the planet” critical to regulating our atmosphere and climate. There is a need for readily available systems for the management, processing and analysis of field spectrometry data. In this paper we present SALSA, a software system for the management, processing and analysis of field spectrometry data that also provides a platform for linking optical data to flux measurements. SALSA is demonstrated using real data collected from multiple research sites.

Keywords

Optical Data Radiance Measurement Logical Separation Irradiance Measurement Airborne System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Baldocchi, D., et al.: Fluxnet: A new tool to study the temporal and spatial variability of ecosystem- scale carbon dioxide, water vapor, and energy flux densities. Bulletin of the American Meteorological Society 82(1), 2415–2434 (2001)CrossRefGoogle Scholar
  2. 2.
    Gamon, J.A., et al.: A mobile tram system for systematic sampling of ecosystem optical properties. Remote Sensing of Environment 103(3), 246–254 (2006)CrossRefGoogle Scholar
  3. 3.
    Harma, P., et al.: Detection of water quality using simulated satellite data and semi-empirical algorithms in Finland. The Science of The Total Environment 268(1–3), 107–121 (2001)Google Scholar
  4. 4.
    Hilker, T., et al.: Tracking plant physiological properties from multi- angular tower-based remote sensing. Oecologia 165(4), 865–876 (2011)CrossRefGoogle Scholar
  5. 5.
    Marshall, E.: Fitting plant earth into a user-friendly database. Science 261(13), 846–848 (1993)CrossRefGoogle Scholar
  6. 6.
  7. 7.
    Rouse, J.W., et al.: Monitoring vegetation systems in the great plains with ERTS. In: 3rd ERTS Symposium, NASA, vol. 1, pp. 309–317 (1973)Google Scholar
  8. 8.
    Running, S., et al.: A continuous satellite-derived measure of global terrestrial primary production. Bioscience 54, 547–560 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Baljeet Malhotra
    • 1
  • John A. Gamon
    • 2
  • Stéphane Bressan
    • 3
  1. 1.SAP ResearchSingapore
  2. 2.University of AlbertaCanada
  3. 3.National University of SingaporeSingapore

Personalised recommendations