Computing Coastal Ocean Surface Currents from MODIS and VIIRS Satellite Imagery

• Main Authors: Jianfei Liu, William J. Emery, Xiongbin Wu, Miao Li, Chuan Li, Lan Zhang
• Format: Article
• Language: English
• Published: MDPI AG 2017-10-01
• Series: Remote Sensing
• Subjects: maximum cross-correlation (MCC); coastal currents; Moderate-Resolution Imaging Spectroradiometer (MODIS); Visible Infrared Imaging Radiometer Suite (VIIRS); ocean color(OC); thermal infrared (IR)
• Online Access: https://www.mdpi.com/2072-4292/9/10/1083

We explore the potential of computing coastal ocean surface currents from Moderate-Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) satellite imagery using the maximum cross-correlation (MCC) method. To improve on past versions of this method, we evaluate combining MODIS and VIIRS thermal infrared (IR) and ocean color (OC) imagery to map the coastal surface currents and discuss the benefits of this combination of sensors and optical channels. By combining these two sensors, the total number of vectors increases by 58.3 % . In addition, we also make use of the different surface patterns of IR and OC imagery to improve the tracking performance of the MCC method. By merging the MCC velocity fields inferred from IR and OC products, the spatial coverage of each individual MCC field is increased by 65.8 % relative to the vectors derived from OC images. The root mean square (RMS) error of the merged currents is 18 cm · s − 1 compared with coincident HF radar surface currents. A 5-year long time serious of merged MCC computed currents was used to investigate the current structure of the California Current (CC). Weekly, seasonal, and 5-year mean flows provide a unique space-time picture of the oceanographic variability of the CC.