The coastal current presents complex changes in spatiotemporal scale due to various dynamic processes and shoreline islands. High frequency surface wave radar has become an effective method to solve these problems because of its wide coverage area and high temporal resolution. Several years ocean current data was collected in Zhoushan sea area, the dynamic processes of the ocean in tide cycle, extreme events, intermonth and interannual time scales in this area were interpreted by using tidal current harmonic analysis, low pass filtering and correlation analysis. The results depicted that the Zhoushan sea area is a regular semi-diurnal tide area, and the current movement is mainly in the form of rotating current. The distribution of current velocity in investigation area illustrated a decreasing trend from northeast to southwest. Interannual variation of residual current in the Zhoushan sea area is not significant, however the obvious intermonth variation characteristic of the residual current was detected. In winter, the flow is southward, and its larger near shore than outside sea. On the contrary, the flow velocity is stronger and the spatial distribution is more uniform in summer. The correlation between wind and residual current was analyzed, during strong winds, the correlation coefficient between wind speed and residual current velocity ranged from 0.48 to 0.90, and the correlation coefficient between wind direction and residual current direction ranged from 0.55 to 0.68. When extreme events occur, the correlation coefficients of velocity and direction are 0.92 and 0.91, respectively. By way of conclusion, the analysis of high frequency surface wave radar data can well reflect the temporal and spatial characteristics of ocean currents in Zhoushan sea area, which provide a basis for marine disaster monitoring, pollutants and algal bloom transport research.

Rip current is a kind of high speed offshore current which occurs frequently in coastal. Based on Castelle’s rip current classification model, Google Earth images of 14 beaches in Guangdong Province were interpreted and classified, and the application of rip current classification model in remote sensing images was discussed. The results show that in high risk months, the composition of rip currents is relatively simple, the mixed rips are few, and the bathymetrically-controlled rip currents play a dominant role, and the number of rip currents remains at a high level. In the middle risk months, the proportion of hydrodynamically-controlled rip currents and mixed rips increases, while the proportion of bathymetrically-controlled rip currents still has a certain proportion. There is little or no rip currents in low-risk months. The structure of rip current is closely related to the state of beach. For the beach in the bay, the length of the bay affects the number of rip currents, and the concave degree of the bay affects the composition ratio of different types of rip currents. Considering the limitations of experimental conditions, this law needs to be further studied and verified in combination with the actual terrain and landform. The classification results obtained according to the interpretation criteria presented in this paper are in good agreement with the risk evaluation model proposed by previous authors, which further demonstrates the effectiveness of the interpretation criteria and provides some reference value for the future research and classification of rip currents.

Affected by fluvial sediment discharge, wind waves and tides, etc., suspended sediment in estuaries and adjacent waters has significant temporal and spatial changes. Based on the GOCI remote sensing images at hourly resolution, this paper uses the optimal remote sensing inversion algorithm, combined with spatial analysis and statistical methods to deeply study the temporal and spatial dynamic characteristics and driving mechanism of suspended sediment in the Yellow River Estuary and adjacent waters. The results show that the impact of fluvial sediment discharge on the concentration of suspended sediment is concentrated in the nearshore area of the estuary. The impact of high fluvial sediment discharge on the distribution of suspended sediment concentration can reach about 20 km offshore and spread to the Gudong nearshore area. Strong winds can cause intensive resuspension of sediment near the old river mouth of Qingshuigou, forming a high-concentration suspended sediment area. The flood and ebb tides have a significant impact on the hourly-scale suspended sediment concentration, and affect the dispersal of suspended sediment from north to south. The variation and dispersal range of the suspended sediment concentration in the spring tide are larger than that of the neap tide due to different tidal flow velocities. There is an obvious negative correlation between water depth and suspended sediment concentration. According to the difference of driving factors, the suspended sediment concentration present exponential, power function, and linear relationships with the increase of water depth.

As China’s first operational ocean color sensor, the coastal zone imager (CZI) carried by Haiyang-1C (HY-1C) satellite is playing an increasingly significant role in offshore ocean environmental monitoring. After the launch of HY-1D satellite, the combination of CZI sensors can provide two observations in three days for coastal zone through dual-satellite system. CZI sensors have demonstrated prominent application advantages for monitoring marine floating algae, oil spill and so on. Since the high spatial resolution optical data contains abundant information about the marine environment, it also brings some distraction to the identification and extraction of specific ocean targets. In this work, a novel CZI algorithm was developed based on cooperation of scaled algae index (SAI) and virtual baseline floating macroalgae height (VB-FAH) to extract floating green tide information in the Yellow Sea from HY-1C satellite CZI measurements. VB-FAH method can be used to enhance the difference between floating algae and sea water, especially for satellite’s sensors with no short-wave infrared bands. After that, the algorithm efficiently rejects the complex interference information in the ocean high spatial resolution optical data by SAI sliding window. The algorithm has high accuracy and time efficiency in the extraction of floating green tide from CZI measurements. Moreover, the study carried out an uncertainty analysis for the area of algae-containing pixels between HY-1C satellite CZI data with 50 m spatial resolution and GF-1 satellite WFV1 data with 16 m spatial resolution. The result indicates that the uncertainty in the inversion results of CZI data mainly comes from the over estimation of small patches of floating algae. The study also pointed out that the uncertainty of optical data for floating algae monitoring is not only from the difference of spatial resolution between two sensors, but also related to the spatial variability of the morphological size of floating algae. Exploring the morphological spatial variability of floating algae will help improve the accuracy of optical data inversion results and clarify the uncertainty.

The marine ecological disasters occurred frequently in recent years. A large number of floating algae gather in the sea surface and inshore water, which brings serious harm to the economic activities and ecological health of coastal cities. In this study, HY-1C, GF-1 and HJ-1A/1B satellite remote sensing images were used to extract information and divide the growth stages of Sargassum in the South Yellow Sea from April to June in 2016 to 2020, combined with the MODIS sea surface temperature data, photosynthetically active radiation data and sea surface wind data to explore the effects of environmental factors on the temporal and spatial distribution of Sargassum. The results show that: (1) In terms of time, the Sargassum mainly appeared from April to June every year. Sargassum had the largest range of influence in 2017 and smaller in other years. In terms of space, the Sargassum was first detected in the far sea northeast of the Changjiang River Estuary and disappeared in the sea near 35°−36°N. (2) In terms of growth rate, the growth phase of Sargassum could be divided into three stages: “development-outbreak-extinction”. (3) At different growth stages, sea surface temperature and photosynthetically active radiation had different degrees of influence on Sargassum. The larger area of Sargassum in 2017 was mainly influenced by higher sea surface temperature and photosynthetically active radiation. The southeast monsoon promoted the drift of Sargassum from the southeast to the northwest and north. This shows that the spatiotemporal characteristics of Sargassum are affected by a variety of environmental factors.

As one of the most important water quality parameters, chlorophyll a is an important indicator to evaluate the degree of eutrophication of water bodies and also the main factors of primary productivity state of the oceans. The coastal zone imager (CZI) onboard the Chinese Haiyang-1C (HY-1C) satellite has an advantage observation in high temporal and spatial resolution. In this study, a chlorophyll a concentration retrieval model for CZI onboard the HY-1C satellite is developed from the in-situ measurements in the East China Sea and the South China Sea. The chlorophyll a concentration is retrieved by the model in the measured waters and compared with MODIS chlorophyll a concentration. The chlorophyll a concentration also retrieved in the Zhujiang River Estuary, Changjiang River Estuary and Bohai Bay. The correlation coefficient between the predicted value of the model and the in-situ chlorophyll a concentration is 0.774 3, the average relative error is 24.58%. The accuracy of the model is verified with the in-situ measurements with the correlation coefficient of 0.993 9 and the average relative error of 18.49%. The distribution of chlorophyll a concentration retrieved from CZI is nearly the same as that of MODIS. The chlorophyll a concentration decreases gradually from northwest to southeast and the peak value locates on the west bank of the Zhujiang River Estuary. The inversion of chlorophyll a concentration in Changjiang River Estuary and Bohai Bay accords with the actual situation. The work in this study indicates that HY-1C satellite coastal zone imager data are useful for the monitoring of coastal ocean color in China.

A support vector machine (SVM) sea ice classification method of Haiyang-1C (HY-1C) satellite coastal zone imager (CZI) images based on the optimal feature set is proposed in this paper. The spectral features and the texture features of CZI images are extracted, and then distance separability criterion is used for feature selection to obtain the optimal feature set. The sea ice classification experiment and analysis of the three CZI images of Liaodong Bay are carried out based on SVM classification method with the optimal feature set as the input of the classifier. The results show that the sea ice classification accuracy obtained by the proposed method is better than that of only using the spectral features or the texture features. The sea ice classification accuracy of December 19, 2020, January 10, 2021 and January 16, 2021 are 93.67%, 91.75% and 84.89%, respectively, all above 80%. The sea ice area of Liaodong Bay is estimated according to the sea ice classification map. It is found that the sea ice area of Liaodong Bay in the three images increased successively, and the maximum area is about 11 998.98 km².

Chinese Ocean Color Temperature Scanner (COCTS) of Haiyang 1C/D (HY-1C/D) satellite is mainly used to detect ocean water color, water temperature and other elements. These elements can only be achieved by processing satellite data, and geometric positioning is the core of preprocessing, which directly affects quality of these elements. COCTS has the characteristics of 114° field of view and quaternary whisk broom point by point. A set of complete geometric positioning method has been developed based on COCTS characteristics. The satellite position and velocity corresponding to the sampling time are obtained by using the interpolation method in the satellite ephemeris extracted from 0 level data, and then the transformation matrix from orbital coordinate system (ORB) to earth-centered rotating coordinate system (ECR) will be achieved. Based on the quaternary whisk broom point by point, the ORB viewing vector of every sampling point in a sweep can be calculated by rotating center viewing vector around X and Y axis in corresponding angles. The relationship model of viewing vector and the earth intersection point can be established to carry out geolocation of remote sensing images obtained from band data. This article uses interpolation to replace the traditional complex method that requires 6 orbital elements to calculate the satellite position, and directly calculates ORB to ECR transformation matrix rather than the traditional two-step transformation method. After multiple sets of data calculation and qualitative and quantitative verification, the HY-1C/D COCTS geometric positioning results are consistent. As a result of the sampling pixel scale effect, the error increases gradually from Nadir to the edge of two sides and from the equator to two poles, all within the error of 2 pixels. This method meets certain positioning accuracy requirements and can be employed for geometric positioning of COCTS.

The research of tidal changes is vital to ocean engineering, the protection of flooding as well as the utilization of ocean resources in coastal areas. Previous studies are mainly based on long-term hourly tide gauges whose number and location are highly limited. Previous study indicated that the long-term trends of tidal amplitudes are abnormally large in the central deep basin of the South China Sea (SCS) based on 25-year satellite altimeter data, which is not realistic and the resultant of the interference of ocean mesoscale variability on tidal harmonic analysis. In this paper, we use 27-year T/P-Jason satellite altimeter data processed by X-TRACK software to study the long-term tidal trends in the SCS. The satellite altimeter data processed by X-TRACK obviously improves the accuracy and completeness of satellite data in the SCS. Meanwhile, the weighted least square method is used to eliminate the effect of tidal aliasing caused by long period sampling. We find that in most areas of the SCS, the amplitudes of four major tidal constituents have significant long-term trends. The significant positive and negative long-term trends of amplitudes and phases are mainly distributed in the coastal areas such as the western Luzon Strait, the Strait of Malacca and Taiwan Strait, where the water depth and shoreline change dramatically. The largest positive long-term trend of amplitudes can reach 2.75 mm/a and the largest negative long-term trend of amplitudes can reach −2.16 mm/a. The long-term trends of tidal amplitudes in the SCS should be related to river flow and human interference.

Based on the long-term observation obtained from two sets of submarine mooring system deployed at Niulang Seamount in the western Pacific, the vertical distribution of the deep currents and the temporal variation characteristics were analyzed in the paper. The results show that: (1) The annual mean ocean currents and the variations were the largest in the upper layer, the second in the middle and deep layers, and the smallest in the middle-deep layers. (2) The subtropical countercurrent was at the depth shallower than 150 m, and the northward current was at depth deeper than 150 m and at the middle layers; the near bottom current was weak southward at the summit of the seamount, but southwestward at the bottom of the seamount. (3) Both at the summit and bottom of the seamount, the currents showed a seasonal oscillation with the most energetic oscillation at a period of about 100 d throughout the water column; at depth above 2 000 m, currents showed a synchronous oscillation in the throughout the water column, with the oscillation amplitude decreasing with depth; current oscillation at deep layers (below 2 000 m) were in opposite phase with that at the upper layers, and the oscillation amplitude was the strongest at 4 000 m.