Optical Identification of Phytoplankton Groups in the Chesapeake Bay: Toward Application of a Hyperspectral Algorithm to Aid Resource Managers

S. Morgaine McKibben; Stephanie Schollaert Uz

doi:10.1364/HISE.2021.HTu2C.3

OSA Optical Sensors and Sensing Congress 2021 (AIS, FTS, HISE, SENSORS, ES)
OSA Technical Digest (Optica Publishing Group, 2021),
paper HTu2C.3
•https://doi.org/10.1364/HISE.2021.HTu2C.3

Optical Identification of Phytoplankton Groups in the Chesapeake Bay: Toward Application of a Hyperspectral Algorithm to Aid Resource Managers

S. Morgaine McKibben and Stephanie Schollaert Uz

Hyperspectral Imaging and Sounding of the Environment 2021

Washington, DC United States
19–23 July 2021
ISBN: 978-1-943580-90-3

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Aquatic Remote Sensing I (HTu2C)

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S. M. McKibben and S. S. Uz, "Optical Identification of Phytoplankton Groups in the Chesapeake Bay: Toward Application of a Hyperspectral Algorithm to Aid Resource Managers," in OSA Optical Sensors and Sensing Congress 2021 (AIS, FTS, HISE, SENSORS, ES), S. Buckley, F. Vanier, S. Shi, K. Walker, I. Coddington, S. Paine, K. Lok Chan, W. Moses, S. Qian, P. Pellegrino, F. Vollmer, G. , J. Jágerská, R. Menzies, L. Emmenegger, and J. Westberg, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper HTu2C.3.

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Abstract

Multi- to hyperspectral evolution of satellite ocean color sensors is advancing space- based coastal ocean science and applications. An approach for optically partitioning phytoplankton (microalgae) communities into component groups is being developed for the Chesapeake Bay.

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