Dr. Zhihong Wang Profile

Dr. Zhihong Wang

at Second Institute of Oceanography SOA

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Publications (2)

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Proceedings Article | 14 October 2019 Paper

Threshold stability of different algorithms for green tide detection base on geostationary ocean color imager

Xiaoguang Huang, Difeng Wang, Fang Gong, Xianqiang He, Yan Bai, Zhihong Wang, Qiankun Zhu

Proceedings Volume 11150, 1115018 (2019) https://doi.org/10.1117/12.2532542

KEYWORDS: Earth observing sensors, Landsat, Satellites, Detection and tracking algorithms, Satellite imaging, Imaging systems

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Since 2008, macroalgal blooms of Ulva Prolifera (also called green tide) have occurred every summer in the Yellow Sea (YS), which has caused environmental and economic problems. In recent years, a variety of detection algorithms for green tide have been proposed. However, the extraction thresholds of each algorithm are uncertain because of atmospheric conditions, the distribution of green tides, etc. In this paper, Geostationary Ocean Color Imager (GOCI) data and Landsat- 8 data were used to explore the threshold stability of some common detection algorithms for green tide, including the AFAI, DVI, EVI, IGAG, and NDVI. Four scenes of GOCI satellite data from 2016 to 2018 were selected for the experiments. The first step was to extract the green tide areas in one region to determine the threshold for each algorithm. In this step, the extraction results of the Landsat-8 data, which has a resolution of 30 m, was seen as the true value of the green tide coverage. Then, we determined the threshold value for each algorithm by visual inspection. The thresholds determined in the first step were used to extract the green tide area in the other three regions, and the extraction results were compared by visual contrast. A comparison of the extraction precision for each algorithm in the other three regions indicated that the threshold stability of the AFAI algorithm was the best among these data in the YS region.

Proceedings Article | 10 October 2018 Presentation + Paper

Abnormal upwelling off the southeast of Vietnam in summer 2016

Zhihong Wang, Xiaoyan Chen, Yan Bai, Xianqiang He, Xiaoping Zhang

Proceedings Volume 10784, 107840Q (2018) https://doi.org/10.1117/12.2324042

KEYWORDS: Climatology, Satellites, Data modeling, Climate change, Oceanography, MODIS

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The upwelling appears generally off the southeast of Vietnam coast in summer. Previous studies have shown that under the influence of El Niño events, the upwelling would be weakened, charactering with high sea surface temperature (SST) and low Chlorophyll-a concentration (Chl-a). However, a different pattern of upwelling appeared in summer 2016, a decaying period of a strong El Niño event. There was a high SST and low Chl-a in June and July, which were similar with that of 1998 and 2010, another two El Niño years. However, we found a strong upwelling together with a moderate phytoplankton bloom off the southeast of Vietnam in August 2016. The analysis of the wind data and SST data indicated that the southwesterly summer monsoon played an important role on this particular case. The abrupt intensification of the southwest wind in late July of 2016 resulted in the SST cooling with nearly one-week delay, which meant that the great significance of the Madden-Julian Oscillation (MJO) occurred. The continuous intensification of the southwest wind enhanced the upwelling associated with Ekman pumping and offshore Ekman transport. As a result, the high-nutrient water of the subsurface was brought into the upper layer, which induced the high Chl-a, and cold-water mass spreading northeastward offshore.

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