| 半分析模型在近岸及河口水体透明度反演应用研究 |
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| 引用本文： | 刘显傅,孟雪娇,汪小勇,毕大勇,陈蕾,娄全胜.半分析模型在近岸及河口水体透明度反演应用研究[J].海洋学报(英文版),2020,39(8):103-112. |
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| 作者姓名： | 刘显傅 孟雪娇 汪小勇 毕大勇 陈蕾 娄全胜 |
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| 作者单位： | 南海规划与环境研究院, 国家海洋局, 广州, 510300;汕尾海洋环境监测中心站, 国家海洋局, 汕尾, 516600;国家海洋技术中心, 国家海洋局, 天津, 300112;南海环境监测中心, 国家海洋局, 广州, 510300 |
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| 基金项目： | The National Natural Science Foundation of China under contract No. 61527810; the Marine Science and Technology Fund from Director of South China Sea Branch, State Oceanic Administration of China under contract No. 180101; the Key Laboratory Open Project Fund of Technology and Application for Safeguarding of Marine Rights and Interests, State Oceanic Administration of China under contract No. 1720. |
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| 摘 要： | Secchi depth(SD, m) is a direct and intuitive measure of water's transparency, which is also an indicator of water quality. In 2015, a semi-analytical model was developed to derive SD from remote sensing reflectance, thus able to provide maps of water's transparency in satellite images. Here an in-situ dataset(338 stations) is used to evaluate its potential ability to monitor water quality in the coastal and estuarine waters, with measurements covering the Zhujiang(Pearl) River Estuary, the Yellow Sea and the East China Sea where measured SD values span a range of 0.2–21.0 m. As a preliminary validation result, according to the whole dataset, the unbiased percent difference(UPD) between estimated and measured SD is 23.3%(N=338, R~2=0.89), with about 60% of stations in the dataset having relative difference(RD)≤20%, over 80% of stations having RD≤40%. Furthermore, by excluding the field data which with relatively larger uncertainties, the semi-analytical model yielded the UPD of 17.7%(N=132,R~2=0.92) with SD range of 0.2–11.0 m. In addition, the semi-analytical model was applied to Landsat-8 images in the Zhujiang River Estuary, and retrieved high-quality mapping and reliable spatial-temporal patterns of water clarity. Taking into account the uncertainties associated with both field measurements and satellite data processing, and that there were no tuning of the semi-analytical model for these regions, these findings indicate highly robust retrieval of SD from spectral techniques for such turbid coastal and estuarine waters. The results suggest it is now possible to routinely monitor coastal water transparency or visibility at high-spatial resolutions from measurements, like Landsat-8 and Sentinel-2 and newly launched Gaofen-5.
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| 关 键 词： | 透明度 水质 近岸与河口水体 半分析模型 遥感 Landsat-8 |
| 收稿时间： | 2019/9/30 0:00:00 |
Using a semi-analytical model to retrieve Secchi depth in coastal and estuarine waters |
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| Liu Xianfu,Meng Xuejiao,Wang Xiaoyong,Bi Dayong,Chen Lei,Lou Quansheng.Using a semi-analytical model to retrieve Secchi depth in coastal and estuarine waters[J].Acta Oceanologica Sinica,2020,39(8):103-112. |
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| Authors: | Liu Xianfu Meng Xuejiao Wang Xiaoyong Bi Dayong Chen Lei Lou Quansheng |
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| Institution: | 1.South China Sea Institute of Planning and Environmental Research, State Oceanic Administration, Guangzhou 510300, China2.Shanwei Marine Environmental Monitoring Center Station, State Oceanic Administration, Shanwei 516600, China3.National Ocean Technology Center, State Oceanic Administration, Tianjin 300112, China4.Environmental Monitoring Center of South China Sea, State Oceanic Administration, Guangzhou 510300, China |
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| Abstract: | Secchi depth (SD, m) is a direct and intuitive measure of water’s transparency, which is also an indicator of water quality. In 2015, a semi-analytical model was developed to derive SD from remote sensing reflectance, thus able to provide maps of water’s transparency in satellite images. Here an in-situ dataset (338 stations) is used to evaluate its potential ability to monitor water quality in the coastal and estuarine waters, with measurements covering the Zhujiang (Pearl) River Estuary, the Yellow Sea and the East China Sea where measured SD values span a range of 0.2–21.0 m. As a preliminary validation result, according to the whole dataset, the unbiased percent difference (UPD) between estimated and measured SD is 23.3% (N=338, R2=0.89), with about 60% of stations in the dataset having relative difference (RD)≤20%, over 80% of stations having RD≤40%. Furthermore, by excluding the field data which with relatively larger uncertainties, the semi-analytical model yielded the UPD of 17.7% (N=132, R2=0.92) with SD range of 0.2–11.0 m. In addition, the semi-analytical model was applied to Landsat-8 images in the Zhujiang River Estuary, and retrieved high-quality mapping and reliable spatial-temporal patterns of water clarity. Taking into account the uncertainties associated with both field measurements and satellite data processing, and that there were no tuning of the semi-analytical model for these regions, these findings indicate highly robust retrieval of SD from spectral techniques for such turbid coastal and estuarine waters. The results suggest it is now possible to routinely monitor coastal water transparency or visibility at high-spatial resolutions from measurements, like Landsat-8 and Sentinel-2 and newly launched Gaofen-5. |
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| Keywords: | Secchi depth water quality coastal and estuarine waters semi-analytical model remote sensing Landsat-8 |
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