Coastal sea surface current observation with GOCI imagery

Xiulin Lou; Aiqin Shi; Huaguo Zhang

doi:10.1117/12.2030969

26 October 2013 Coastal sea surface current observation with GOCI imagery

Xiulin Lou, Aiqin Shi, Huaguo Zhang

Proceedings Volume 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 89212D (2013) https://doi.org/10.1117/12.2030969
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China

Abstract

Measurements of sea surface currents are important in understanding the dynamic of ocean processes especially in coastal waters, and satellite remote sensing has been used to derive sea surface advective velocities with visible or infrared imagery. Yet satellite remote sensing suffered from lack of high temporal imagery in dynamic coastal waters and from frequent cloud cover. In this study, using measurements from the Geo-stationary Ocean Color Imager (GOCI), we observed the sea surface currents in the East China Sea on 29 May 2011 by applying the Maximum Cross-Correlation (MCC) technique. The hourly ocean color images on 29 May 2011 (8 images per day from 8:30 am to 15:30 pm) showed water pattern movement and evolution through the course of a day, and 7 sequence sea surface velocity fields were derived. The results show that there were significant diurnal changes of the sea surface currents in the coastal waters. The average current velocity was 30~40 cm/s during the measurements, with maximum velocity of 50~60 cm/s observed between 9:30 and 10:30 am. The short-term changes of the surface velocities are mainly a result of the horizontal dilution due to tides. The case study here demonstrates the unique value of a geostationary satellite ocean color sensor in revealing short-term dynamics in coastal waters.

Citation Download Citation

Xiulin Lou, Aiqin Shi, and Huaguo Zhang "Coastal sea surface current observation with GOCI imagery", Proc. SPIE 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 89212D (26 October 2013); https://doi.org/10.1117/12.2030969

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