Degree Granting Department
Kendall L. Carder, Ph.D.
Gabriel A. Vargo, Ph.D
Edward Van Vleet, Ph.D.
Backscatter, Light absorption, Phytoplankton, Remote sensing
Estimating with precision coastal marine properties such as primary production, particulate and dissolved carbon, and red tide concentrations is a challenging but important part of marine research. It benefits not only the local communities, but also provides an important input to various global biogeochemical modeling efforts. Due to the complexity of coastal environments resulting from temporal variability of tidal and riverine influences, it is useful to develop and deploy an automated sensor network that provides real-time feedback. It can be used to validate remote sensing models to retrieve in-water constituents, and provide calibration and validation for atmospheric correction of satellite sensors. For turbid waters, satellite observations in the infrared part of the spectrum can not be used to estimate atmospheric aerosol concentration because the water is not “black” as is found for clearer waters. This research contribution introduces a modeling effort for a turbid coastal harbor area using a semi-analytical hyperspectral remote sensing algorithm for Case 2 waters to process data from the Autonomous Marine Optical System (AMOS). Retrieved results are then compared with field sample measurements showing satisfactory closure between measurements and theory. A time series of AMOS data over a one-month time span is examined, revealing significant variations in biological activity. A sensitivity analysis of the model is performed to expose the limitations and possible improvements to AMOS measurements in the future.
Scholar Commons Citation
Du, Chunzi, "Autonomous Optical Measurements in Bayboro Harbor (Saint Petersburg, Florida)" (2005). Graduate Theses and Dissertations.