Document Type

Thesis

Degree

Master of Science (MS)

Major/Program

Environmental Studies

First Advisor's Name

Assefa M. Melesse

First Advisor's Committee Title

Committee chair

Second Advisor's Name

Leonard J. Scinto

Second Advisor's Committee Title

Committee Member

Third Advisor's Name

Jennifer S. Rehage

Third Advisor's Committee Title

Committee Member

Keywords

Chlorophyll-a, Chesapeake Bay, Ocean Color Algorithm, Coastal Water, Algal Bloom, MODIS

Date of Defense

6-20-2018

Abstract

This study analyses the spatial and temporal variability of chlorophyll-a in Chesapeake Bay; assesses the performance of Ocean Color 3M (OC3M) algorithm; and develops a novel algorithm to estimate chlorophyll-a for coastal shallow water. The OC3M algorithm yields an accurate estimate of chlorophyll-a concentration for deep ocean water (RMSE=0.016), but it failed to perform well in the coastal water system (RMSE=23.17) of Chesapeake Bay. A novel algorithm was developed which utilizes green and red bands of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The novel algorithm derived the chlorophyll-a concentration more accurately in Chesapeake Bay (RMSE=4.20) than the OC3M algorithm. The study indicated that the algorithm that uses red bands could improve the satellite estimation of chlorophyll-a in the coastal water system by reducing the noise associated with bottom reflectance and colored dissolved organic matter (CDOM)

Identifier

FIDC006903

Available for download on Tuesday, January 22, 2019

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