J. of Spatial Hydrology The Selection of Narrow Wavebands for Optimizing Water Quality Monitoring on the Great Miami River, Ohio using Hyperspectral Remote Sensor Data

Remote sensing data were successfully used to estimate spatial and temporal variation of optical water quality parameters such as chlorophyll a, turbidity and Total Suspended Solids (TSS) of the Great Miami River, Ohio. During the summer of 1999, spectral data were collected with a hand-held spectroradiometer, a laboratory spectrometer and airborne hyperspectral sensors. Approximately 80 km of the Great Miami River were imaged during a flyover with a Compact Airborne Spectrographic Imager (CASI) sensor. Approximately 10 km were imaged during a second flyover to repeat coverage of the urban and industrial influences around the city of Dayton, Ohio. Instream measurements of water quality data such as turbidity levels, chlorophyll a concentrations, and Secchi-disk depth were acquired on the same days as the flyovers. Relationships between optical water quality parameters and one or two broad wavebands were determined. An attempt was made to utilize portions of the electromagnetic spectrum, which minimize the effects of atmospheric anomalies, in turn normalizing the spectrally additive constants in all wavebands. Because this assumption was not met for turbidity, a first derivative approach was used. The derivative reflectance is an alternative and theoretically more robus