Remote sensing technology is widely used to obtain information on floating green tides, and thresholding methods based on indices such as the normalized difference vegetation index (NDVI) and the floating algae index (FAI) play an important role in such studies. However, as the methods are influenced by many factors, the threshold values vary greatly; in particular, the error of data extraction clearly increases in situations of high-turbidity water (HTW) (NDVI > 0). In this study, high spatial resolution, multispectral images from the Sentinel-2 MSI mission were used as the data source. It was found that the International Commission on Illumination (CIE) hue angle calculated using remotely sensed equivalent multispectral reflectance data and the RGB method is extremely effective in distinguishing floating green tides from areas of HTW. Statistical analysis of Sentinel-2 MSI images showed that the threshold value of the hue angle that can effectively eliminate the effect of HTW is 218.94°. A test demonstration of the method for identifying the floating green tide in HTW in a Sentinel-2 MSI image was carried out using the identified threshold values of NDVI > 0 and CIE hue angle < 218.94°. The demonstration showed that the method effectively eliminates misidentification caused by HTW pixels (NDVI > 0), resulting in better consistency of the identification of the floating green tide and its distribution in the true color image. The method enables rapid and accurate extraction of information on floating green tide in HTW, and offers a new solution for the monitoring and tracking of green tides in coastal areas.

The CIE hue angle has significant potential in marine ecology and environment monitoring using remote sensing methods. It is calculated from the remote sensing reflectance (R_rs) of all visible bands, which serves as a comprehensive indicator of seawater radiance information and represents one of the key quantitative parameters for assessing seawater color. In this study, a remote sensing retrieval model of total suspended matter concentration (TSM) was developed using the in situ measured data acquired in the coastal waters of Qinhuangdao from 2013 to 2021. This model, based on the CIE hue angle, achieved performance metrics of R² = 0.68, MAPE=24.47%, and RMSE=2.72 mg/L, demonstrating better accuracy than traditional empirical models that utilize fewer bands. Based on this model, the monthly and interannual TSM in the coastal waters of Qinhuangdao from 2003 to 2023 were retrieved. Influenced by natural factors, such as the monsoons, the TSM in the coastal waters of Qinhuangdao generally exhibited a trend of first decreasing and then increasing from January to December. Except for certain anomalous years (2007, 2008, 2017, etc.), the overall variation process of TSM from 2003 to 2023 showed an initial increase followed by a decrease, closely related to the pollution reduction management requirements implemented by the Chinese government in different periods. The findings of this paper demonstrate that the coastal waters of Qinhuangdao have become clearer, and the ecological environment has been effectively improved as a result of the Chinese government’s vigorous promotion of ecological civilization construction, adhering to the development concept that ‘lucid waters and lush mountains are invaluable assets’, and by introducing the action plan for the comprehensive treatment of pollution in the Bohai Sea.

Unmanned Aerial Vehicles (UAVs) have become powerful tools for high-resolution, quantitative remote sensing in ecological and environmental studies. In this study, we present a novel approach to accurately mapping and estimating the biomass of Suaeda salsa using UAV-based visible-light imagery combined with hue angle inversion modeling. By integrating diffuse reflectance standard plates into the flight protocol, we converted RGB pixel values into reflectance and derived hue angle metrics with enhanced radiometric accuracy. A hue angle cutoff threshold of 249.01° was identified as the optimal cutoff to distinguish Suaeda salsa from the surrounding land cover types with high confidence. To estimate biomass, we developed an exponential inversion model based on hue angle data calibrated through extensive field measurements. The resulting model—Biomass = 3.57639 × 10⁻¹⁵ × e^0.12201×α—achieved exceptional performance (R² = 0.99696; MAPE = 3.616%; RMSE = 0.02183 kg/m²), indicating strong predictive accuracy and robustness. This study highlights a cost-effective, non-destructive, and scalable method for the real-time monitoring of coastal vegetation, offering a significant advancement in remote sensing applications for wetland ecosystem management.

Nuclear energy plays a crucial role in global carbon reduction. However, thermal discharges from nuclear power plants can potentially impact marine ecosystems. This study investigates the long-term thermal impact of the Haiyang Nuclear Power Plant on the adjacent marine environment using a decade-long Landsat thermal infrared dataset. Spatial and temporal patterns of thermal discharge were analyzed, focusing on the temperature difference between intake and outlet water, the warming trend in the thermal mixing zone, and the spatial distribution of the thermal plume. Our results indicate the following: (1) Seasonal Variation in Thermal Discharge: The temperature difference between intake and outlet water exhibited significant seasonal variability, with higher values in winter and lower values in summer. The spatial distribution of the thermal plume was influenced by tidal currents, leading to a cyclical pattern. (2) Long-Term Warming Trend: Prolonged thermal discharge resulted in a notable warming trend in the thermal mixing zone, with an average annual increase of 0.3 °C. This warming effect was most pronounced in winter and least in summer. (3) Spatial Distribution of Thermal Plume: The spatial extent and intensity of the thermal plume varied seasonally. Summer exhibited a larger influence range but with lower temperature rises, while winter showed a smaller influence range but with higher temperature rises. In winter, the 4 °C temperature rise area exceeded the designated environmental functional zone boundary in some instances. These findings provide valuable insights into the thermal impact of nuclear power plants and highlight the importance of considering seasonal variations and long-term monitoring to ensure environmental sustainability.