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Remote estimation of total suspended matter concentration in the Hangzhou Bay based on OLCI and its water color product applicability analysis
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Yuan Li1, 2, Yulong Guo3, *, Chunmei Cheng4, Yibo Zhang2, Yaoduo Hu2, Zhong Xia2, Shun Bi5
Haiyang Xuebao | 2019, 41(9) : 156 - 169
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Haiyang Xuebao | 2019, 41(9): 156-169
Marine Information Science
Remote estimation of total suspended matter concentration in the Hangzhou Bay based on OLCI and its water color product applicability analysis
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Yuan Li1, 2, Yulong Guo3, *, Chunmei Cheng4, Yibo Zhang2, Yaoduo Hu2, Zhong Xia2, Shun Bi5
Affiliations
  • 1 School of Tourism and Urban & Rural Planning, Zhejiang Gongshang University, Hangzhou 310018, China
  • 2 State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
  • 3 College of Resources and Environmental Sciences, Henan Agricultural University, Zhengzhou 450002, China
  • 4 College of Geomatics and Municipal Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China
  • 5 School of Geography Science, Nanjing Normal University, Nanjing 210023, China
Published: 2019-09-25 doi: 10.3969/j.issn.0253-4193.2019.09.015
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As a main carrier of nutrients and pollutants, total suspended matter (TSM) has a significant influence on water environment, especially on estuary water environment. The Ocean and Land Colour Instrument (OLCI) was onboard ESA Sentinel-3A satellite and launched in February 16, 2016, with fine spatial, temporal and spectral resolution. To find the best atmospheric correction method and TSM retrieval model for the application of OLCI in Hangzhou Bay (HZB), six atmospheric correction methods and eight TSM retrieval models were test based on in situ water color data collected from HZB on July 2017. In addition, the OLCI Level 2 product (e.g. TSM and inherent optical properties (IOP) data) was compared with in situ data to evaluate the accuracy and applicability of OLCI Level 2 product. The results show that the method of atmospheric correction based on ultraviolet wavelength (UVAC) and the TSM retrieval model based on band ratio have best performance. Specifically, the mean absolute percentage error (MAPE) of atmospheric correction in four match-up sites is 34.21%, 13.11%, 5.92% and 20.28%, respectively. In addition, the averaged MAPE of atmospheric correction in band Oa2 to Oa12 and Oa16 to Oa18 is 15.23%, and in band Oa4 to Oa10 is less than 8%. The band ratio (Oa16/Oa5) model has the best performance, with a MAPE of 16.49% and root mean square error (RMSE) of 50.92 mg/L in calibration stage, and a MAPE of 19.08% and RMSE of 19.29 mg/L in validation stage. However, the TSM and IOP product derived from C2RCC (case 2 regional coast colour) algorithm and the TSM product derived from OLCI Level 2 product has no linear relationship with in situ data. These results indicate that the above Level 2 product is unsuitable for HZB TSM and IOP remote estimation. Finally, the UVAC method and band ratio model are applied to OLCI imagery that is collected on July 23, 2017. Spatially, TSM shows a relative low value in the center of HZB and relative high value in the south and east part of HZB.

Hangzhou Bay  /  OLCI data  /  total suspended matter  /  applicability analysis  /  atmospheric correction
Yuan Li, Yulong Guo, Chunmei Cheng, Yibo Zhang, Yaoduo Hu, Zhong Xia, Shun Bi. Remote estimation of total suspended matter concentration in the Hangzhou Bay based on OLCI and its water color product applicability analysis[J]. Haiyang Xuebao, 2019 , 41 (9) : 156 -169 . DOI: 10.3969/j.issn.0253-4193.2019.09.015
Year 2019 volume 41 Issue 9
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doi: 10.3969/j.issn.0253-4193.2019.09.015
  • Receive Date:2018-08-15
  • Online Date:2026-04-03
  • Published:2019-09-25
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  • Received:2018-08-15
  • Revised:2018-11-01
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Affiliations
    1 School of Tourism and Urban & Rural Planning, Zhejiang Gongshang University, Hangzhou 310018, China
    2 State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
    3 College of Resources and Environmental Sciences, Henan Agricultural University, Zhengzhou 450002, China
    4 College of Geomatics and Municipal Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China
    5 School of Geography Science, Nanjing Normal University, Nanjing 210023, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
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占总种数比例
Percentage of
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种数
Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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