HYPERSPECTRAL REMOTE SENSING OF BENTHOS (GOES-R)

The benthic environments along coastal margins are changing at an alarming rate. Seagrasses are particularly vulnerable to anthropogenic degradation of coastal environments resulting from eutrophication, dredging, and watershed modifications that reduce water clarity and stimulate blooms of nuisance algae. We propose to evaluate and develop algorithms for using remotely sensed ocean color to estimate benthic productivity in optically shallow water. Our approaches will utilize the high spectral and spatial resolution afforded by the GOES-R HES-CW to derive quantitative measures of seagrass biomass (e.g., Leaf area index, rates of primary production, oxygen flux, and carbonate dissolution) that can be incorporated in global biogeochemical models.

 

  • Conduct sensitivity analysis identifying U.S. coastal regions (e.g., Chesapeake Bay, Monterey Bay) with optically shallow water ecosystems that can be resolved by the GOES-R HES-CW. Potential benthic constituents for analysis include seagrasses, kelp, and benthic algal mats.
  • Develop and validate algorithms for estimating benthic productivity from seagrass and sediment across the large optically shallow carbonate sediment basins (Florida Bay, Bahamas, etc.
  • Conduct field investigations to validate approach using hyperspectral airborne imagery

See Bostrom and Dierssen (2013) for details on this research.

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