Automated Oceanographic Feature Detection from High Resolution Satellite Images

A. Chaudhuri, A. Gangopadhyay, R. Balasubramanian, and S. Ray (USA)


Scientific Visualization, Remote Sensing, Eddy Detection, Upwelling, Physical Oceanography.


This research focuses on analysis and processing of high resolution Sea Surface Temperature (SST) and Chlorophyll_a (Ocean Color) observations from satellite data. Our objective is to detect and locate mesoscale oceanographic features, such as eddies, upwelling, jets, filaments and narrow frontal regions. Our approach is to identify these features by utilizing their dominant patterns and variability to characterize their spatial segmentation properties. Mesoscale phenomena, such as eddies, currents, fronts and upwelling regions in the Monterey Bay and in the Gulf of Mexico are studied here. An automatic ocean feature identification procedure is presented. Schemas like eddy structuring element construction and banded thresholding methodology are discussed. This approach is demonstrated on satellite derived images of SST and Ocean Color.

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