Abstract
The envelope removal method has the advantage of suppressing the background spectrum and expanding the weak absorption characteristic information. However, for second-class water bodies with a relatively complex water quality, there are few studies on the inversion of chlorophyll a (Chl-a) concentration in water bodies that consider the spectral absorption characteristics. In addition, the current research on the inversion of the Chl-a concentration was carried out under the condition of sample concentration equilibrium. For areas with a highly variable Chl-a concentration, it is still challenging to establish a highly applicable and accurate Chl-a concentration inversion model. Taking Dongting Lake in China as an example, this study used high-concentration samples and spectral absorption characteristics to invert the Chl-a concentration. The decap method was used to preprocess the high-concentration samples with large deviations, and the envelope removal method was used to extract the spectral absorption characteristic parameters of the water body. On the basis of the correlation analysis between the water Chl-a concentration and the spectral absorption characteristics, the water Chl-a concentration was inverted. The results showed the following: (1) The bands that were significantly related to the Chl-a concentration and had a large correlation coefficient were mainly located in the three absorption valleys (400–580, 580–650, and 650–710 nm) of the envelope removal curve. Moreover, the correlation between the Chl-a concentration and the absorption characteristic parameters at 650–710 nm was better than that at 400–580 nm and 580–650 nm. (2) Compared with the conventional inversion model, the uncapped inversion model had a higher RP2 and a lower RMSEP, and was closer to the predicted value of the 1:1 line. Moreover, the performance of the uncapped inversion model was better than that of the conventional inversion model, indicating that the uncapped method is an effective preprocessing method for high-concentration samples with large deviations. (3) The predictive capabilities of the ER_New model were significantly better than those of the R_New model. This shows that the envelope removal method can significantly amplify the absorption characteristics of the original spectrum, which can significantly improve the performance of the prediction model. (4) From the inversion models for the absorption characteristic parameters, the prediction models of A650–710 nm_New and D650–710 nm_New exhibited the best performance. The three combined models (A650–710 nm&D650–710 nm_New, A650–710 nm&NI_New, A650–710 nm&DI_New) also demonstrated good predictive capabilities. This demonstrates the feasibility of using the spectral absorption feature to retrieve the chlorophyll concentration.
Funder
The Open Fund of the Key Laboratory of Non-ferrous Metal Mineralization Prediction and Geological Environment Monitoring (Central South University) of the Ministry of Education
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development
Cited by
2 articles.
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