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HYPERSPECTRAL CHANNEL SELECTION FOR WATER QUALITY MONITORING ON THE GREAT MIAMI RIVER, OHIO
Citation:
Shafique, N A., B C. Autrey, F A. Fulk, AND S M. Cormier. HYPERSPECTRAL CHANNEL SELECTION FOR WATER QUALITY MONITORING ON THE GREAT MIAMI RIVER, OHIO. Presented at Society of Environmental Toxicology and Chemistry, Baltimore, MD, November 11-15, 2001.
Impact/Purpose:
The purpose of this research project is to provide methods, tools and guidance to Regions, States and Tribes to support the TMDL program. This research will investigate new measurement methods and models to link stressors to biological responses and will use existing data and knowledge to develop strategies to determine the causes of biological impairment in rivers and streams. Research will be performed across multiple spatial scales, site, subwatershed, watershed, basin, ecoregion and regional/state.
Description:
During the summer of 1999, spectral data were collected with a hand-held spectroradiometer, a laboratory spectrometer and airborne hyperspectral sensors from the Great Miami River (GMR), Ohio. Approximately 80 km of the GMR were imaged during a flyover with a Compact Airborne Spectrographic Imager sensor. Approximately 10 km were imaged during a second flyover to repeat coverage of the urban influences around the city of Dayton, Ohio. Instream measurements of water quality data such as chlorophyll a concentrations, turbidity levels 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. Generally, atmospheric characters had negligible effects on the wavebands used or could be considered as spectrally additive constants in all wavebands. Because this assumption was not met for turbidity, the alternative and theoretically more robust derivative of reflectance was used. A high correlation was observed between these narrow wavebands (spectral channels) and water quality parameters. Based on this correlation, semi-quantitative models were developed to produce maps of the relative distributions of chlorophyll a and turbidity from the hyperspectral images of the river.