Date of Award

Spring 2005

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Civil Engineering - (Ph.D.)

Department

Civil and Environmental Engineering

First Advisor

Sima Bagheri

Second Advisor

Hsin Neng Hsieh

Third Advisor

Lisa Axe

Fourth Advisor

Taha F. Marhaba

Fifth Advisor

Eliza Zoi-Heleni Michalopoulou

Abstract

Three important optical properties used for monitoring coastal water quality are the concentrations of chlorophyll (CHL), color dissolved organic matter (CDOM) and total suspended materials (TSM). Ocean color remote sensing, a technique to collect color data by detection of upward radiance from a distance (Bukata et al.,1995), provides a synoptic view for determining these concentrations from upwelling radiances. In the open ocean (Case-I), it is not difficult to derive empirical algorithms relating the received radiances to surface concentrations of water quality parameters. In coastal waters (Case-Il), there are serious unresolved problems in extracting chlorophyll concentration because of high concentration of suspended particles (Gordon and Morel, 1983).

There are three basic approaches to estimate optical water quality parameters from remotely sensed spectral data based on the definitions given by Morel & Gordon (1980): (1) an empirical method, in which statistical relationships between the upward radiance at the sea surface and the quantity of interest are taken into account; (2) a semiempirical method, in which the spectral characteristics of the parameters of interest are known and some modeling of the physics is introduced; and (3) an analytical method, in which radiative transfer models are used to extract the inherent optical properties (lOPs) and a suite of analysis methods can be used to optimally retrieve the water constituents from the remotely sensed upwelling radiance or irradiance reflectance signal.

The focus of this research is the modification and application of analytical and statistical algorithms to characterize the physically based surface spectral reflectance for the waters of the Hudson/Raritan Estuary and to retrieve the water constituent concentrations from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and LIght Detection And Ranging (LIDAR) signals. The approaches used here are based on the unique capabilities of AVIRIS and LIDAR data which can potentially provide a better understanding of how sunlight interacts with estuarine/inland water, especially when complemented with in situ measurements for analysis of water quality parameters and eutrophication processes.

The results of analysis in forms of thematic maps are then input into geographic information system (GIS) of the study site for use by water resource managers and planners for better monitoring and management of water quality condition.

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