26 October 2013 Fusion of SAR and MODIS images for oceanic internal waves tracking in the South China Sea
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Proceedings Volume 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 89210L (2013) https://doi.org/10.1117/12.2035676
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China
Abstract
South China Sea (SCS) is one of the most active areas for internal waves (IW) occurrences in the world. These waves generated at the Luzon Strait, propagate westward into the SCS, and dissipate on the continental shelf after persisting for more than 4 days. IW phase speed is an important parameter to study the evolution of IWs and the ocean interior characteristics. In this paper, we analyzed one pair of SAR/MODIS images containing same IW signatures in the SCS spanning from 19N to 23N and from 115E to 118E. The SAR and MODIS images were taken at 02:07:52 and 02:50:00 UTC on 22 April 2007, respectively. First, the SAR and MODIS images are calibrated and geo-referenced. By overlaying images in a GIS system, we are able to track the same wave-crest displacement between the time intervals of the image pair, and thus, derive the phase speeds of IWs at different locations. We show that the phase speeds of individual wave packets can be estimated accurately using this pair of MODIS/ASAR images separated in time by 42 minutes and 8 seconds. Furthermore, we find that there is an inseparable relationship between IW phase speed and water depth. The IW phase speeds are in proportion to the water depths along their pathways. In conclusion, we present a new multiple-sensor image fusion technique in a GIS environment to extract IW geolocation information and derive their propagation phase speeds.
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Bingqing Liu, Bingqing Liu, Hong Yang, Hong Yang, Xianwen Ding, Xianwen Ding, Zhongxiang Zhao, Zhongxiang Zhao, Xiaofeng Li, Xiaofeng Li, } "Fusion of SAR and MODIS images for oceanic internal waves tracking in the South China Sea", Proc. SPIE 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 89210L (26 October 2013); doi: 10.1117/12.2035676; https://doi.org/10.1117/12.2035676
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