Remote sensing is used in a large number of ervironmental investigations, including water quality assessments. Most of the data acquired for water quality are from satellite platforms, which contain sensors that provide images using wide bandwidths. The use of narrow, correctly positioned, spectral bands in current airborne sensing devices as well as in a new generation of sensors planned for satellites simplifies formulation of water quality algorithms. If simple, accurate, reproduci ble, and sensitive algorithms applicable to a wide range of coastal and inland waters can be developed, then using remote sensing will become not only easier and more reliable, but also more affordable and rapid due to the reduction of data volume, increased integration times, and facilitated image analysis.The "operationalization" of remote sensing for monitoring water quality conditions will become closer to reality. In the present investigation, algorithms representing spectral energy from single bandwidths, ratios of bandwidths, and line heights found to be highly correlated with chlorophyll a, turbidity, and suspended solids for inland waters, are being tested in two coastal ecosystems, the Indian River Lagoon and Tampa Bay. It looks promising that even in the absence of precise optical characteristics for an environment, it may be possible to simulate that environment from previous ground truthing and derive fixedwing transportable coefficients.Commercial Applications:The demonstration of a low cost and rapid imaging and image analysis system using algorithms that require minimal or no calibration, and with high predictive capabilities for chlorophyll a and suspended sediment concentrations in surface water, will lead to a significant increase in the demand for water quality information collected by remote sensing.
