Modern computational techniques for environmental data; application to the global ozone layer
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part III
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As part of a historic remediation project, approximately 61 km2 of salt evaporation ponds in the southern portion of San Francisco Bay, CA (USA) are scheduled for restoration to natural tidal marsh habitat over the next several decades. We have investigated the correlation of remotely sensed infrared spectral information with in situ field measurements and sampling, and evaluated the usefulness of a remote sensing approach to monitor salinity and population distributions of microbial communities in the hypersaline ponds. The Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) instrument operated by the Jet Propulsion Laboratory has created a ten-year archive of spectral information concerning these ponds. We utilized spectral signatures of microbial populations that are sensitive to salinity, and trained a supervised classification algorithm to identify physical parameters from an AVIRIS scene based upon microbe spectra gathered in the field using a portable visible to near-infrared (VNIR) spectrometer. Our results indicate that automated analyses of hyperspectral observations are capable of detecting variations in microbial populations and discriminating corresponding salinity levels.