Optical remote sensing of marine constituents in coastal waters: an optimization approach

摘要

Optical remote sensing of ocean colour is a well-established technique. But most algorithms developed higherto have been based on the assumption that only the phytoplankton concentration and related algae degradation products affect the optical properties of the ocean. Such algorithms are often based on assumptions that become questionable in coastal areas in which strong scattering by inorganic marine particles may occur. Then the assumption of a near-infrared dark pixel in the satellite image, will no longer be valid, and the band-ratio technique used for computing the algae concentration will become inaccurate as well. To overcome these limitations we have developed an inverse-modeling algorithm for retrieval of marine constituents in coastal waters. Here the determination of ocean colour is based on a three-component optical model of ocean water consisting of chlorophyll-a, suspended matter, and yellow substance. A simulated-annealing optimization scheme is employed to minimize the difference between measured satellite data and corresponding simulated data obtained by use of a coupled atmosphere-ocean radiative transfer code. Our results show that retrieval of marine constituents in coastal water is possible. Experimental validation of the algorithm remains to be carried out.