Mapping Surface Water Quality in Flaming Gorge Reservoir using Hyperoin Spaceborne Hyperspectral Imagery
Can hyperspectral imagery obtained from spaceborne sensors produce maps of surface water quality that are superior to those derived from spaceborne multispectral sensors such as Landsat TM (Thematic Mapper)?
Need and Benefit
The proposed research is meant to determine if hyperspectral imagery (imagery composed of many narrow spectral bands) from the Hyperion spaceborne sensor aboard the EO-1 satellite can improve upon water quality maps generated by spaceborne multispectral sensors such as Landsat TM. Multispectral remote sensing of water quality is a proven tool that allows for the extrapolation of point-sampled water quality data across an entire lake surface. However, the broad spectral ranges of multispectral sensors typically mask subtle spectral variations that can be used to determine concentrations of chlorophyll-a (a key indicator of reservoir biological productivity) in the presence of varying amounts of mineral suspended sediment. Hyperspectral sensors may have the spectral sensitivity to make these discriminations.
Airborne hyperspectral imagery has been shown to improve water quality prediction accuracies over those from multispectral imagery; but until now, hyperspectral imagery was extremely expensive and only available from airborne platforms. The spaceborne Hyperion sensor has reduced signal to noise characteristics relative to airborne sensors, and design compromises complicate radiometric calibration of the imagery. However, it is far less expensive to acquire and has consistent sun-target-sensor geometry across the image, which should make for simplified processing for water quality mapping. Hyperion imagery, or imagery acquired by future hyperspectral sensors, could be an inexpensive data source for the monitoring of surface water quality in Reclamation reservoirs.
Water quality has an obvious impact on water supply, in that water quality standards must be met before water can be delivered for beneficial use. This proposal falls under the Water Delivery focus area of the Science and Technology (S&T) Program, in the Water Quality (WD4) subarea Develop and improve tools, models, and methods for managing water quality issues that impact operations and deliveries.
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