13 October 2017 Retrieval of total suspended particulate matter in highly turbid Hangzhou Bay waters based on geostationary ocean color imager
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Hangzhou Bay waters are often characterized by extremely high total suspended particulate matter (TSM) concentration due to terrestrial inputs, bottom sediment resuspension and human activities. The spatial-temporal variability of TSM directly contributes to the transport of carbon, nutrients, pollutants, and other materials. Therefore, it is essential to maintain and monitor sedimentary environment in coastal waters. Traditional field sampling methods limit observation capability for insufficient spatial-temporal resolution. Thus, it is difficult to synoptically monitor high diurnal dynamics of TSM. However, the in-orbit operation of the world’s first geostationary satellite ocean color sensor, GOCI, thoroughly changes this situation with hourly observations of covered area. Taking advantage of GOCI high spatial-temporal resolution, we generated TSM maps from GOCI Level-1B data after atmospheric correction based on six TSM empirical algorithms. Validation of GOCI-retrieved normalized water-leaving radiances and TSM concentration was presented in comparison with matched-up in-situ measurements. The mean absolute percentage differences of those six TSM regional algorithms were 24.52%, 163.93%, 195.50%, 70.50%, 121.02%, 82.72%, respectively. In addition, the discrepancy reasons were presented, taking more factors such as diversified satellite data, various study area, and different research season into consideration. It is effective and indispensable to monitor and catch the diurnal dynamics of TSM in Hangzhou Bay coastal waters, with hourly GOCI observations data and appropriate inversion algorithm.
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Jia Liu, Jia Liu, Jiahang Liu, Jiahang Liu, Xianqiang He, Xianqiang He, Tieqiao Chen, Tieqiao Chen, Feng Zhu, Feng Zhu, Yihao Wang, Yihao Wang, Zengzhou Hao, Zengzhou Hao, Peng Chen, Peng Chen, } "Retrieval of total suspended particulate matter in highly turbid Hangzhou Bay waters based on geostationary ocean color imager", Proc. SPIE 10422, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2017, 1042217 (13 October 2017); doi: 10.1117/12.2278047; https://doi.org/10.1117/12.2278047


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