Abstract

Ocean color remote sensing has brought a new era in ocean management. A reasonable number of satellites are dedicated at present for providing ocean color data to boost up ocean management. The major satellites include MODIS, OCM-2, VIRS, OLCI, etc. Major applications of those sensors are identifying potential fishing ground and harmful algal bloom, tracking cyclone, determining oil slick, monitoring mangrove ecosystem and trends. Ocean color remote sensing offers many advantages over conventional procedures for example synoptic coverage, repeated observations, and area averaging. The absence of nearshore, particularly the area below 200 m depth of the Bay of Bengal, data is a major limitation of those sensors. The necessity of regional and bio-optical algorithms, atmospheric corrections, in-situ data validations, artificial neural networks, and the accuracy of those sensors is still a challenge for oceanographers. This study aims to address the preferable ocean color remote sensors and their importance of oceanic management in the Bay of Bengal.