The accurate extraction of an aquaculture area is significant in aquaculture management, post disaster evaluation, and aquatic environment protection. However, little attention has been paid to the aquaculture area extraction in coastal water with high turbidity. In this study, based on the spectral and geospatial features of aquaculture cages in complex coastal water with varying turbidity, we proposed a new aquaculture area extraction method using a Gaofen-2(GF-2) satellite image with 0.8m spatial resolution. The water was classified into clear, medium, and high turbidity categories according to the suspended sediment concentration (SSC) derived from the inversion of the GF-2 image. Different rules of extraction were developed with respect to those three categories of water body: (1) The Normalized Difference Water Index(NDWI) threshold was set for the clear water, (2) a ratio index (R=Green/NIR) was established for the medium turbid water body, and (3) for the turbid water body, feature analysis with a specified classification rule was established. The experimental results demonstrated that our proposed method worked well, with the high accuracies of 87.3300% for the overall accuracy, even for the high turbidity water. The Kappa coefficient was 0.7375, which was much better than the Kappa coefficient values of the three conventional classification methods represented in this paper. This study provides effective information support and auxiliary decision analysis for management departments to scientifically plan and environmentally manage coastal aquaculture areas.

The sea area around Dajin Island in the Pearl River Estuary is the second-largest habitat in China for the Indo-Pacific humpback dolphin (Sousa Chinensis). However, the rapid economic development of this area brings potential threats to the aquatic ecology around Dajin Island. Real-time monitoring and evaluation of the ecological health of the sea area are urgent. In this study, band ratio and single-band inversion algorithms were performed to obtain Chlorophyll-a (Chl-a) and Suspended Sediment Concentration (SSC), relying on both Compact Airborne Spectrographic Imager (CASI) and Moderate resolution Imaging Spectrometer (MODIS) images. The CASI/Chl-a with high spatial resolution was adopted to assess the eutrophication status, while the dissolved organic carbon (DOC) concentration and chromophoric dissolved organic matter (CDOM) optical properties were used to derive the material composition and sources. The results suggest that the study area is under a low to medium eutrophication state with evenly distributed low Chl-a concentration. However, higher Chl-a is observed in the outer estuary with MODIS/Chl-a. The relatively high DOC concentration, especially in the north, where aquaculture is practiced, and near the estuary’s main axis, i.e., east Dajin Island, indicates that the eutrophication state might be underestimated using satellite chlorophyll alone. CDOM optical properties indicated that terrestrial materials are the DOC’s primary material sources, but the DOC derived from fishery aquaculture cannot be ignored. The low Chl-a concentration is likely due to the turbulent hydrodynamic regime caused by jet flow and reciprocating flow in this marine area. Comprehensive observation, including the assessment of different technological platforms, is suggested for the aquatic environment.

The sea area of Dajin Island in the Pearl River Estuary is the habitat of the Chinese White Dolphin. The CASI(Compact Airborne Spectrographic Imager) hyperspectral data was used to observe the three constituents of ocean color (chlorophyll-a, suspended sediment concentration and chromophoric dissolved organic matter), which play an important role in reflecting water quality, indicating sea environment and water eutrophication, and the inversion model of three constituents of ocean color is constructed. In addition, the in situ measured water color constituent data is used to evaluate the accuracy of the inversion results. The results show that: 1) the band ratio model (Chla=0.9601×(Rrs(622.486)/Rrs(851.341))+0.0739) based on CASI data can well retrieve the chlorophyll-a (Chl-a) concentration in the studied sea area, the content is 0.1-4.4 μ g / L, and the relative average error is 14.77%.2) The single-band index model (SSC=0.4829×exp(19.619×Rrs(622.486)))based on CASI data can better invert the concentration of suspended sediment concentration (SSC), the concentration is 0.48-12.15 mg/L, and the relative average error is 11.16%.3) The band ratio model(CDOM=1.0222e^ (-2.144×(Rrs(B36)/Rrs(B3))) based on CASI data can better invert the concentration of chromophoric dissolved organic matter (CDOM) in the studied sea area, with a relative average error of 12.80%. This shows that CASI airborne remote sensing has a very important role in developing refined observations for specific areas, and can more quickly and effectively monitor the ecological environment and evaluate pollution in the cloudy coverage study area