Inversion Method of Chlorophyll Concentration Based on
Relative Reflection Depths
AN Ying1, 2, 4, DING Jing3, LIN Chao2, LIU Zhi-liang1, 4*
1. Research Center for Marine Science, Hebei Normal University of Science & Technology, Qinhuangdao 066004, China
2. State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
3. National Satellite Ocean Application Service, Beijing 100081, China
4. Hebei Key Laboratory of Ocean Dynamics，Resources and Environments, Qinhuangdao 066004, China
Abstract：Chlorophyll concentration in ocean waters is the main parameter for describing marine primary productivity, estimating phytoplankton abundance and variation, assessing environmental quality and forecasting ecological disasters. The general inversion model of chlorophyll products used by satellite remote sensing at home and abroad is the OCx (x=2~6) algorithms based on the intensity ratio of remote sensing reflection spectra in different bands. When applied to case-1 glasses of waters, the mean relative error on a global scale is about 35%. However, for case-2 waters with complex inherent optical properties and large regional differences, OCx algorithms have large errors or even fail. The previous research results show that the relative spectral height is beneficial to extracting the feature information and improving the signal-to-noise ratio of ocean color. However, the inversion model based on relative height still has problems, such as single band selection and a narrow application range. In China coastal, the construction method and application effect of the relative height model need to be further studied and verified. Based on in-situ measured chlorophyll concentration data and apparent optical parameters in Qinhuangdao coastal waters, after normalizing hyperspectral data and selecting characteristic bands, the inversion model has been constructed based on relative reflection depths of characteristic bands in this paper. The related coefficient between the inversion and the measured values is 0.883 58, and the mean relative error is 28.33%. Compared with the OCx algorithms, the average relative errors are reduced by more than 27%～50%. The model is verified, and the mean relative error is 31.17%. On this basis, correlation analysis was carried out on the multi-spectral data of HY-1C China Ocean Color & Temperature Scanner and the measured chlorophyll concentration, and the inversion model was established based on the relative reflection depths at 443 and 520 nm. The mean relative error of the model was reduced by 53.44% compared with that of the L2B product at the same time. The results show that the inversion model based on relative reflection depths can make full use of the information of chlorophyll characteristic bands, reduce the sensitivity to noise, and improve the signal-to-noise ratio of ocean color constituents, thus greatly improving the inversion accuracy and robustness of the model. This research has important scientific significance and substantial application value for constructing hyperspectral and multi-spectral inversion models of ocean color elements, measurement of water optical parameters, popularization and application of satellite products, estimation of primary productivity, ecological environment monitoring, hydrodynamic process research and other fields.
安 颖，丁 静，蔺 超，刘志亮. 相对反射深度的秦皇岛海域叶绿素浓度反演[J]. 光谱学与光谱分析, 2022, 42(04): 1083-1091.
AN Ying, DING Jing, LIN Chao, LIU Zhi-liang. Inversion Method of Chlorophyll Concentration Based on
Relative Reflection Depths. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(04): 1083-1091.
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