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ANALYZING WATER QUALITY WITH IMAGES ACQUIRED FROM AIRBORNE SENSORS
Citation:
Autrey, B C. ANALYZING WATER QUALITY WITH IMAGES ACQUIRED FROM AIRBORNE SENSORS. Presented at Science Forum 2003, Washington, DC, May 5-7, 2003.
Impact/Purpose:
The goal of this research is to develop methods and indicators that are useful for evaluating the condition of aquatic communities, for assessing the restoration of aquatic communities in response to mitigation and best management practices, and for determining the exposure of aquatic communities to different classes of stressors (i.e., pesticides, sedimentation, habitat alteration).
Description:
Monitoring different parameters of water quality can be a time consuming and expensive activity. However, the use of airborne light-sensitive (optical) instruments may enhance the abilities of resource managers to monitor water quality in rivers in a timely and cost-effective manner. The degree to which these optical instruments are useful will depend on their ability to detect water quality parameters in different water bodies. In 1999, an optical sensor was flown over the relatively shallow Great Miami River (GMR), Ohio, collecting an image consisting of many very narrow wavelengths of light (hyperspectral data). At the same time, water quality parameters were measured, water samples were collected and a spectrometer (another optical instrument) was used to collect data directly from the river. By using the relationships between the data collected directly from the river and the optical data collected from the airplane, mathematical relationships (called spectral indices) were developed which could be used to estimate the concentration of chlorophyll a, turbidity and the concentration of phosphorus in the river. In 2001, a similar study was conducted in which another hyperspectral imaging sensor was flown over a portion of the relatively deep Ohio River while other data were collected directly from the river. These data were analyzed and tested against the spectral indices developed during the 1999 study. The GMR's spectral index for chlorophyll a was usable in the Ohio River. However, the spectral indices developed from the GMR data for turbidity and phosphorous were not usable for the Ohio River data and, therefore, were refined in order to accurately estimate these parameters.
This study demonstrates the potentially widespread applicability of the chlorophyll a spectral index while revealing the limited applicability of the turbidity and phosphorous spectral indices. Although differences between the dynamics of the two rivers may have made these spectral indices incompatible, with further refinement they may yet prove to be broadly applicable tools in the detection and measurement of potential water quality problems. The full development of this tool will be the use of these indices in estimating water quality parameters with data acquired by satellite, and can help make water quality monitoring much more efficient for resource managers.