This study shows match-up analysis of chlorophyll-a concentration in coastal area in Upper Gulf of Thailand. An applicability of atmospheric correction are investigated in turbid area. When a suspended matter concentration is over 7 g/m3 in a mouth of Bangpakong river, atmospheric correction was failed, then chlorophyll-a concentration could not be estimated. Three algorithms which are MODIS (Moderate Resolution Imaging Spectroradiometer) standard, neural network for GLI (Global Imager) and regional empirical algorithm are compared using match-up data set. The regional algorithm has better correlation than other algorithms and its RMSE was minimum in three algorithms. MODIS standard algorithm has good performance in higher than 1mg/m3, however, CHL was overestimated in lower concentration.
A system for analyzing remotely-sensed satellite images using knowledge bases driven by multi-stage inference engines has been developed. Sea-surface temperature analysis is thought to have great potential for effectively identifying the positions and shapes of oceanic conditions such as ocean fronts, eddies, currents, and so on. Knowledge and experience accumulated through conventional oceanic observation by ships and other methods are indispensable when extracting such oceanic conditions from remotely-sensed data, and the extraction process requires the efforts of human experts. This paper discusses some useful strategies for dealing with the problems of automatic extraction of oceanic conditions, including a mechanism for selecting individual algorithms and automatically constructing a sequence of image processing commands, a scheme for verifying consistency between knowledge rules, and a scheme for the intensive accumulation of knowledge information. In addition, this paper presents some experimental applications to remotely-sensed ocean image data which have been performed highly efficiently. The resulting extracted ocean fronts and currents have been successfully verified using oceanographic surveys.
Optical and phytoplankton pigment data collected from around 80 stations in the south-west Atlantic sector of Antarctic Ocean between the Drake Passage and Antarctic Peninsula during three Antarctic Expeditions of Japan Fisheries Agency in Austral summer were analyzed for bio-optical characterization. Three optical water types were identified based on the spatial variability of phytoplankton pigment in the euphotic zone and corresponding profile of physical parameters along with total beam attenuation coefficient, c<SUB>t</SUB>(m<SUP>-1</SUP>) and diffuse attenuation coefficient, K<SUB>d</SUB>(m<SUP>-1</SUP>). The derived pigment specific particulate beam attenuation coefficient and diffuse attenuation coefficients were effectively used to identify optical stations under dominant influence of non-chlorophyll substances. The pigment specific coefficients were compared with the coefficients reported from typical case I waters and polar waters as well. Significant variations from temperate model and agrement with polar region model are discussed. Chlorophyll remote sensing model was examined with two sets of reflectance, R((lambda) ) and sub-surface upwelling radiance, L<SUB>u</SUB>((lambda) ) ratios. The typical case I water remote sensing algorithm and the algorithm derived from present analysis were implemented on the CZCS image, and satellite derived chlorophyll values were compared with in situ estimates available in the same area from the Polish BIOMASS-FIBEX expedition. The results point to the need of more critical study on the bio-optical aspects before implementation of local algorithms for this region on ocean color image.