Paper No. 7
Presentation Time: 10:30 AM


WHITEHEAD, Shannon Lynne, Geology & Environmental Geoscience, College of Charleston, 66 George Street, Charleston, SC 29401 and ALI, Khalid A., Geology and Environmental Geosciences, College of Charleston, 202 Calhoun Street, Charleston, SC 29424,

Coastal zones are complex and dynamic ecological systems that represent the most productive areas of the marine environment. They have important functions including primary food supply, recreation, biodiversity and transportation. These important functions and their scenic properties have resulted in the high population density building stress on these environments. The southeast coastal region is one of the fastest growing regions in the United States and the increasing utilization of open water bodies has led to the deterioration of water quality and aquatic ecology, placing the future of these resources at risk. In coastal zones, a key index that can be used to assess the stress on the environment is the water quality. Millions of people visit the beaches of South Carolina (SC) every year. The occurrence of hypoxia, or low dissolved oxygen, is increasing in the coastal waters of SC and represents a significant threat to the health and economy of the state. Remote sensing has become very promising in providing temporal and spatial information regarding biogeodynamics most efficiently. In optically complex environments, such as in Long Bay South Carolina, the water contains multiple biogeochemical constituents or color producing agents (CPAs) such as, phytoplankton, total suspend matter (TSM), and colored dissolved organic carbon. Identifying and analyzing in-water constituents in these waters are crucial for understanding and assessing many biogeochemical processes. This study focuses on using remote sensing as a tool to estimate CPAs such as phytoplankton concentrations, using chlorophyll a as a proxy, and the concentrations of TSM in the Long Bay waters of SC. In this work, we evaluated the performance of 10 bio-optical chlorophyll a models applied to hyperspectral data based on regression and residual analysis. Among the suite of the chlorophyll a models, algorithms utilizing the 700/670 band ratio gave the best results with R2 as high as 0.73 and RMSE = 0.20ug/l. Regression analysis between individual bands and TSM indicated that the 550 nm was most sensitive spectral region. This study demonstrates that the various CPAs in the coastal water of SC can be quantified remotely, and crucial for detecting and monitoring potential large scale development of algal blooms in response to the increasing ecological stress.