Visualization of Ocean Colour and Temperature from multi-spectral imagery captured by the Japanese ADEOS satellite

Abstract

The Ocean Colour and Temperature Scanner on board of the Japanese Advanced Earth Observing Satellite has been designed to provide frequent global measurements of marine chlorophyll levels and ocean temperature and created a means for visualizing the biological activity in the upper ocean. Over the time of its operation, the sensor captured the coverage of global oceans suitable for studies of the marine primary production and monitoring of fishery sites and environmental changes. Current radiative transfer techniques modelling marine chlorophyll levels based on optical reflectances captured by satellite sensors have to account for atmospheric path radiances superimposed onto the water-leaving radiance and a diversity of water suspended particles. Detailed modelling of geophysical processes and empirically constrained algorithms sometimes produce misclassifications. This paper presents chlorophyll concentration for several sites around the Pacific Ocean. Where the skill of the conventional chlorophyll algorithm is uncertain, the results given by an unsupervised neural network classification scheme are also provided. The hierarchical neural network introduced in the text extracts water pixels from images and reclassifies them to separate case 1 and case 2 waters and water radiances with the significant influence of the atmospheric attenuation.