Bio-optical algorithms for remote estimation of chlorophyll-a concentration (Chl) in case-1 waters exploit the upwelling radiation in the blue and green spectral regions. In turbid productive waters other constituents, that vary independently of Chl, absorb and scatter light in these spectral regions. As a consequence, the accurate estimation of Chl in turbid productive waters has so far not be...

This paper describes fuzzy spectral-spatial clustering of multivariate image data to perform a segmention into a desired number of clusters, and orthogonal subspace projection (OSP) to reduce the influence of undesired spectra. The clustering is used to identify clouds in SeaWiFS data. The influence of the clouds is successfully reduced by means of OSP causing the ocean signal to become much mo...

When aerosols from the Hawaii volcano plume are present then the water leaving radiance derived from the SeaWifs satellite using the SeaDas algorithm is too large. It is shown that this problem may be due to the use of an incorrect aerosol model. Furthermore, it is shown that using longer wavelengths may be needed to solve the atmospheric correction problem under Hawaii volcanic aerosols.

The primary focus of this proposed research is for the atmospheric correction algorithm evaluation and development and satellite sensor calibration and characterization. It is well known that the atmospheric correction, which removes more than 90% of sensor-measured signals contributed from atmosphere in the visible, is the key procedure in the ocean color remote sensing (Gordon and Wang, 1994)...

Although modern ocean color sensors, such as MODIS and SeaWiFS, are often considered global missions, in reality it takes many days, even months, to sample the ocean surface enough to provide complete global coverage. The irregular temporal sampling of ocean color sensors can produce biases in monthly and annual mean chlorophyll estimates. We quantified the biases due to sampling using data ass...