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R/E-24J
Discrimination of Phytoplankton Taxa in the Optically Complex Waters of Chesapeake Bay
Principal Investigator:
Greg SilsbeStart/End Year:
2020 - 2021Institution:
Horn Point Laboratory, University of Maryland Center for Environmental ScienceCo-Principal Investigator:
Anna WindleTopic(s):
Strategic focus area:
Healthy coastal ecosystemsDescription:
A spectral library of remote sensing reflectance for major phytoplankton taxonomic groups in the Chesapeake Bay will be developed using measured and modeled inherent optical properties as inputs into radiative transfer equations (HydroLight TM). The spectral library will be used to develop a phytoplankton discrimination algorithm in order to distinguish major phytoplankton taxa and sediment types in Chesapeake Bay waters. Hyperspectral remote sensing reflectance spectra collected from an unoccupied aircraft system (UAS) or the upcoming hyperspectral satellite mission, PACE, can be used as inputs to the algorithm to effectively quantify and map phytoplankton taxonomic-specific biomass. This proposed research has the potential to significantly improve decision making regarding water quality in the Chesapeake Bay.
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Featured Fellow
Anna Windle uses satellites and drones to study water quality in Chesapeake Bay. In her spare time, Anna enjoys swimming, biking, and running to train for triathlons.
Featured Research Project
Discrimination of Phytoplankton Taxa in the Optically Complex Waters of Chesapeake Bay
A spectral library of remote sensing reflectance for major phytoplankton taxonomic groups in the Chesapeake Bay will be developed using measured and modeled inherent optical properties as inputs into radiative transfer equations (HydroLight TM). The spectral library will be used to develop a phytoplankton discrimination algorithm in order to distinguish major phytoplankton taxa and sediment types in Chesapeake Bay waters.
