Citation:

Knight, J F., R S. Lunetta, H. W. Paerl, J J. Streicher, B. L. Peierls, T. Gallo, J G. Lyon, AND T H. Mace. REMOTE MEASUREMENT OF PHYTOPLANKTON PIGMENTS IN THE PAMLICO SOUND, NC USING HYPERSPECTRAL IMAGERY. Presented at International Geosciences and Remote Sensing Symposium (IGARSS) 2004, Anchorage, AK, September 20-24, 2004.

Impact/Purpose:

Our research objectives are to: (a) develop new methods using satellite remote sensor data for the rapid characterization of LC condition and change at regional to national scales; (b) evaluate the utility of the new NASA-EOS MODIS (Moderate Resolution Imaging Spectrometer) leaf area index (LAI) measurements for regional scale application with landscape process models (e.g., biogenic emissions and atmospheric deposition); (c) provide remote sensor derived measurement data to advance the development of the next generation of distributed landscape process-based models to provide a predictive modeling capability for important ecosystem processes (e.g., nutrients, sedimentation, pathogens, etc.); and (d) integrate in situ monitoring measurement networks with UAV and satellite based remote sensor data to provide a continuous environmental monitoring capability.

Description:

Monitoring of phytoplankton concentrations in estuarine environments is important for managing both recreational and commercial fishery resources. Impacts on estuarine areas from phytoplankton blooms include neurotoxic shellfish poisoning; fish, bird, and vegetation kills; and potentially negative effects on human health. Measurement of the distributions and concentrations of phytoplankton species has heretofore been accomplished through the use of in situ water sampling and traditional analytical techniques. Phytoplanakton taxanomic groups are identified by the relative concentrations of diagnostic marine pigments present in water samples as measured by High Performance Liquid Chromatography (HPLC). To date, estimation of marine pigments in Case II estuaries derived from remotely sensed images has been limited to determination of chlorophyll concentrations. The remote measurement of diagnostic pigment concentrations needed to provide estimates of the relative abundances of specific phytoplankton taxanomic groups has not previously been demonstrated in marine environments. This presentation describes a method in which hyperspectral image data processed with derivative analysis and regression modeling was used to determine the concentrations of certain diagnostic marine pigments - including peridinin, which is unique to the harmful dinoflagellate organisms.

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