Computing Coastal Ocean Surface Currents from MODIS and VIIRS Satellite Imagery

被引:9
|
作者
Liu, Jianfei [1 ]
Emery, William J. [2 ]
Wu, Xiongbin [1 ]
Li, Miao [1 ]
Li, Chuan [1 ]
Zhang, Lan [1 ]
机构
[1] Wuhan Univ, Sch Elect Informat, Radio Oceanog Lab, Wuhan 430072, Hubei, Peoples R China
[2] Univ Colorado, Dept Aerosp Engn Sci, Colorado Ctr Astrodynam Res, Boulder, CO 80309 USA
基金
中国国家自然科学基金;
关键词
maximum cross-correlation (MCC); coastal currents; Moderate-Resolution Imaging Spectroradiometer (MODIS); Visible Infrared Imaging Radiometer Suite (VIIRS); ocean color(OC); thermal infrared (IR); CALIFORNIA CURRENT SYSTEM; VELOCITIES; RADAR;
D O I
10.3390/rs9101083
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页数:19
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