Satellite Remote Sensing of Total Suspended Matter Concentration in Hangzhou Bay and Its Adjacent Waters
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摘要: 近海及海湾总悬浮物是重要的水质参数之一，而杭州湾及其邻近海域是典型的海湾与近岸海域，与人类关系密切。卫星遥感广泛应用于海水总悬浮物浓度的探测与分析。利用现场实测数据，建立了中国HY-1C/D卫星水色水温扫描仪（Chinese Ocean Color and Temperature Scanner, COCTS）及其他当前在轨的典型水色遥感器在杭州湾及邻近海域的总悬浮物卫星遥感反演方法模型，模型平均相对误差不高于19%。反演并融合获得了HY-1C/D等多源卫星2015－2022年杭州湾及邻近海域的总悬浮物浓度卫星遥感及其融合数据。融合数据经实测数据对比验证，两者之间线性相关系数为0.72，平均相对偏差为26%。卫星遥感结果表明，2015－2022年间杭州湾及其邻近海域总悬浮物浓度年际变化不大，其线性变化不超过其年平均浓度值的0.5%。研究结果表明利用包括HY-1C/D卫星COCTS等的海洋水色遥感载荷，可有效遥感反演得到杭州湾及其邻近海域的总悬浮物浓度并分析其时空变化特征。Abstract: The Total Suspended Matter (TSM) in the coastal water area and sea bays is one of the important water quality parameters, and Hangzhou Bay and its adjacent waters are typical gulfs and offshore waters with close relationships with humans. Satellite remote sensing is widely used for monitoring and analyzing the concentration of total suspended matter in seawater. Satellite remote sensing retrieval models of TSM concentration for Chinese Ocean Color and Temperature Scanner (COCTS) on the HY-1C and HY-1D satellites and other typical ocean color remote sensors currently in orbit in Hangzhou Bay and its adjacent waters were developed using in-situ measured data. The average relative errors of the models are not greater than 19%. TSM concentration in Hangzhou Bay and adjacent waters from 2015 to 2022 was retrieved and merged from multi-source satellite data including HY-1C/D. The merged products in this study have been validated against in-situ measured data with the linear correlation coefficient of 0.72 and an average relative error of 26%. The results indicate that the inter-annual variation of the TSM concentration in Hangzhou Bay and its adjacent waters is not significant in the period from January 2015 to December 2022, and its linear variation does not exceed 0.5% of its annual average concentration value. The results of the study indicate that the TSM concentration and its temporal and spatially variation characteristics in Hangzhou Bay and its adjacent waters can be effectively retrieved from space broad ocean color remote sensing payloads including COCTS on the HY-1C/D satellites.
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Key words:
- Hangzhou Bay /
- Total suspended matter concentration /
- HY-1C/D satellites /
- Remote sensing
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图 1 研究区及其HY-1C卫星海岸带成像仪遥感影像（2019年11月11日）
Figure 1. Study area and remotes sensing image acquired by Coastal Zone Imager (CZI) on the HY-1C satellite (11 November 2019)
图 2 遥感反演建模所用实测点位置分布
Figure 2. Locations of in-situ measurements used forremote sensing retrieval modeling
图 3 研究区内实测站点实测遥感反射比光谱曲线
Figure 3. Spectral curves of remote sensing reflectance at measured stations in the study area
图 4 HY-1C/D卫星COCTS杭州湾及其邻近海域TSM浓度遥感反演模型效果评价散点图
Figure 4. Scatter plot for evaluating of the TSM concentration remote sensing retrieval model of COCTS on the HY-1C satellite in Hangzhou Bay and its adjacent waters
图 5 GOCI，VIIRS（SNPP和JPSS-1卫星）和MODIS卫星载荷杭州湾及其邻近海域TSM浓度遥感反演模型效果评价散点图
Figure 5. Scatter plot for evaluating the TSM concentration remote sensing retrieval models for satellite sensor of GOCI, VIIRS on the SNPP, VIIRS on the JPSS-1, and MODIS in Hangzhou Bay and its adjacent waters
图 6 杭州湾及其邻近海域TSM浓度卫星遥感反演结果（观测日期：2021年1月13日）
Figure 6. Remote sensing retrieval results of TSM concentration from satellites covering the Hangzhou bay and its adjacent sea area (acquired on 13 January 2021)
图 7 2021年1月13日杭州湾及其邻近海域TSM浓度多源卫星遥感融合结果
Figure 7. Merged TSM concentration from multi-source satellite remote sensing results in Hangzhou Bay and its adjacent waters on 13 January 2021
图 8 杭州湾及邻近海域TSM浓度精度评估匹配点位置分布
Figure 8. Locations of matching points for TSM concentration accuracy evaluation in Hangzhou Bay and its adjacent waters
图 9 TSM浓度融合结果精度检验对比散点图
Figure 9. Scatter plot for accuracy evaluation of the merged TSM concentration
图 10 杭州湾及其邻近海域遥感TSM浓度变化趋势（平均年变化率）分布（黑色区域有效遥感观测数据不足80%）
Figure 10. Distribution map of TSM concentration change trend (average annual change rate) in Hangzhou Bay and its adjacent waters (The black area in the figure represents the percentage of effective remote sensing data is less than 80%)
图 11 TSM浓度卫星遥感数据2020年平均分布及分析站位位置分布
Figure 11. Average distribution map of TSM concentration remote sensing data in 2020 and the location distribution of analysis sites
图 12 分析站位A～E位置处TSM浓度时序曲线
Figure 12. Time series curve of TSM concentration at analysis site A to site E
表 1 卫星数据源信息
Table 1. Satellite data source information used in this study
序号 传感器/卫星 幅宽/ km 空间分辨率/m 时间分辨率/d–1 在轨时间范围（年月） 1 COCTS/HY-1C，HY-1D 3000 1100 2 2018.09－（HY-1C）
2020.06－（HY-1D）2 GOCI/COMS 2500 250 8 2010.06－ 3 VIIRS/SNPP，JPSS-1 3000 750 2 2011.10－（SNPP）
2017.11－（JPSS-1）4 MODIS/Terra，Aqua 2330 1000 2 1999.12－（Terra）
2002.05－（Aqua）
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表 2 杭州湾及其邻近海域TSM浓度遥感反演模型各传感器波段选择信息
Table 2. Bands selection information of various sensors for the retrieval models of TSM concentration in Hangzhou Bay and its adjacent waters
传感器 $ \lambda _{\rm{B}} $/nm $ \lambda _{\rm{G}} $/nm $ \lambda _{\rm{R}} $/nm COCTS 490 565 670 MODIS 488 551 667 VIIRS/SNPP 486 551 671 VIIRS/JPSS-1 489 556 667 GOCI 490 560 665
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表 3 杭州湾及其邻近海域TSM浓度遥感反演模型公式系数及其建模效果评价结果信息
Table 3. The formula coefficients and modeling evaluation indicators of TSM concentration remote sensing retrieval models in Hangzhou Bay and its adjacent waters
传感器 b0 b1 b2 相关系数${R^2}$ 平均相对误差/（%） COCTS 0.42080 22.79800 –0.33329 0.962 16.90 MODIS 0.60253 24.40700 –0.55732 0.965 18.80 VIIRS/SNPP 0.55215 24.25332 –0.50701 0.965 18.10 VIIRS/JPSS-1 0.49413 23.46630 –0.43409 0.964 17.20 GOCI 0.49282 24.08773 –0.43924 0.966 16.20
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表 4 TSM浓度变化分析站点位置信息
Table 4. Location information of the sites for TSM concentration variation analysis
站位 A B C D E 位置 30.50°N, 121.55°E 31.10°N, 122.25°E 32.00°N, 124.50°E 30.50°N, 123.75°E 29.00°N, 124.10°E
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