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| Retrieval of Water Quality Parameters of Urban River Network Using Hyperspectral Date Based on Inherent Optical Parameters |
| LIN Jian-yuan1, ZHANG Chang-xing2*, YOU Hong-jian3 |
1. School of Engineering Science，University of Chinese Academy of Sciences，Beijing 100049, China
2. Key Laboratory of Spatial Active Opto-Eletronic Technique, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
3. Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China |
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Abstract The water radiative transfer mechanism is the theoretical basis of water spectral characteristic analysis. The inherent optical parameters of water due to the composition of the water is independent of the surface light field of water. The semi-empirical algorithm based on statistics can be used to retrieve water quality parameters in some specified areas. However, that is lacking in physical meaning. It was of great significance for the study of the spectral characteristics of turbid water in inland cities to study the model to retrieve the water quality parameters of urban river network based on inherent optical parameters using hyperspectral data. The study was based on the analysis algorithm of bio-optical model. Taking the consideration of the characteristics of inland type II water of urban river network such as complexity of optical characteristics, strong heterogeneity of spatial distribution, small water and large fluidity. The paper came up with an improved QAA algorithm suitable for water of inland urban river network to obtain the inherent optical parameters of water. The improvements included the following two aspects: adjustment of the backscattering estimation model and optimization of the reference band. By calculating inherent optical parameters, such as the coefficient of total absorption of the reference band, the coefficient of backscattering particles, etc., coefficient of phytoplankton absorption was obtained and coefficient of pure water absorption was eliminated in this paper. A linear regression analysis was carried out on the optimal ratio of coefficient of phytoplankton absorption and concentration of chlorophyll-a to build a model to retrieve water quality of chlorophyll-a concentration. A linear regression analysis was also carried out to eliminate the optimal band ratio of coefficient of pure water absorption and concentration of suspended solids. And a model to retrieve suspended solids concentration for water quality was built. Aiming at type II water bodies of inland river network and taking the typical river network of Jiaxing City as the research area, regional aeronautical hyperspectral data, ground quasi-synchronous measurement data of water sampling data and spectral data above the water surface were collected; the QAA algorithm and IIMIW algorithm were used to retrieve the inherent optical parameters of the measured water spectral data. With the two algorithms compared and the characteristics of urban river network was taken into consideration, the improved QAA algorithm was put forward. The retrieval of the inherent optical parameters of the water in the study area was achieved by using improved QAA algorithm. Based on the inherent optical parameters of water obtained by the inversion, quantitative inversion model of chlorophyll-a concentration and suspended solids concentration were established. The determining coefficients R2 of the inversion model were 0.64 and 0.71, respectively. The retrieved results were validated and analyzed using the actual measured sample data of four ground samples acquired at the same time in the area by the aircrafts which obtained aviation hyperspectral data. Comparing the retrieved values of water quality parameters of concentration with the measured values, the average relative errors of retrieved values for chlorophyll-a and suspended solids were 9.2% and 9.4% respectively. The table of distribution of chlorophyll-a and suspended solids obtained from the retrieval was also consistent with the characteristics and actual conditions of the urban river network. That provided methods and model references for urban river network water quality monitoring.
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Received: 2018-10-24
Accepted: 2019-02-18
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Corresponding Authors:
ZHANG Chang-xing
E-mail: zzhangcx@163.com
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