遥感图像中尺度海洋锋及涡旋提取方法研究进展

Research progress of methods for the extraction of mesoscale ocean fronts and eddies based on remote sensing data

目的中尺度海洋锋及涡旋均是重要的中尺度海洋环境特征。中尺度海洋锋及涡旋的提取及其时空分布、变化的研究对海洋生态系统的研究、渔业资源评估、渔情预报及军事等都有重要意义。遥感技术能在同一时间获取大面积海洋要素观测数据,遥感数据具有优良的连续性、同步性,因此遥感数据被广泛应用于中尺度海洋锋及涡旋提取的研究中。方法对基于遥感数据进行中尺度海洋锋提取的梯度法、Canny算法、小波分析法和基于引力模型的方法,以及涡旋的提取的Okubo-Weiss法(OW法)、Winding-Angle法(WA法)、基于海面高度的无阈值等值线法和Hybird Detection(HD法)进行总结和分析,并提出对中尺度海洋锋面及涡旋提取方法的见解及新思路。结果利用2014年2月南海北部海表温度(SST)数据,分别采用梯度法中的Gradient法、Sobel算法以及Canny算法对南海北部温度锋进行提取并得到该区域温度锋分布图。结果表明在多种锋面提取方法中,Canny算法具有较高的效率且其提取结果的连续性和精度更好。中尺度涡的提取方法中,WA法的提取结果具有更好的准确性。早期的中尺度涡提取方法忽略了多中心结构涡旋存在的情况,而后来的HD法能较好地识别多中心结构涡旋。结论阈值选取是中尺度海洋锋及涡旋提取的难点和提取结果好坏的关键。然而海洋要素图像弱边缘的特点使得传统边缘检测方法不一定适用于中尺度锋提取。文章通过对不同锋面及涡旋提取方法的总结与分析,为海洋锋面及涡旋提取的研究提供了参考依据。

Objective Mesoscale ocean fronts and eddies are important mesoscale marine environment characteristics. The ocean front is the interface of water masses with different properties. In the area where an ocean front exists, corresponding hydrological factors （e. g. , temperature, chlorophyll concentration, and salinity） present a high horizontal gradient. Sea- water convergence and vertical motion are enhanced in fields where fronts appear; this enhancement leads to the enrichment of nutrients and provides a rich diet to plankton, fish, and so on. Therefore, the sea area where fronts appear can serve as a good fishing ground （e. g. , Zhoushan and Minnan fishing grounds in China）. Mesoseale eddy plays an important role in ocean circulation and is an important undertaker of energy transport and ocean material transfer in oceans. Furthermore, ed- dies can influence the distribution of hydrological factors, such as temperature and salinity, and is thus one of the important factors of marine hydrological variation. Eddies associated with local lifting flow, such as the upwelling associated with cold eddies, carry nutrients to euphotic zones from the bottom of the ocean, greatly improve the primary productivity of the ocean, and influence the distribution of the fishing ground. Thus, they affect the development of the marine economy. Re- mote sensing data demonstrate excellent continuity and synchronization and can effectively reflect the spatial distribution characteristics of marine hydrological elements and the sea surface height. Therefore, remote sensing data, such as sea sur- face temperature, sea surface height, and sea level anomaly, have been widely used in the extraction of mesoscale ocean fronts and eddies. Research on the extraction of mesoscale ocean fronts and eddies based on remote sensing data is thus sig- nificant to marine ecosystem research, fishery stock assessment, and fishing condition forecasting. We aim to provide a ref- erence and ideas for the extraction of mesoscale ocean fronts and eddies by summarizing and analyzing the methods of extracting mesoscale ocean fronts and eddies. Method This study summarizes and analyzes the methods of front extraction, such as gradient method, canny algorithm, wavelet analysis method, and algorithms based on the law of universal gravity, as well as the methods of eddy extraction, such as OW, WA, SSH-based and HD methods. Insights and new ideas are then provided. To show the difference among various front extraction methods intuitively, fronts are extracted from same area by using gradient, Sobel, and canny algorithms. The extraction results are presented in a figure. When gradient and Sobel algorithms are used to extract fronts, the thresholds used to distinguish the background and front pixels are obtained by the iterative method. Afterward, the Zhang-Suen method is applied to implement binary image thinning. The center line of the front is then obtained. When the canny algorithm is utilized to extract fronts, 0. 25 is selected as the low threshold and 0. 9 as the high threshold. Result With sea surface temperature （SST） data on the northern South China Sea （SCS） in Februar- y 2014, gradient, Sobel, and canny algorithms are used to extract the temperature front in northern SCS. A figure is subse- quently drawn for the temperature front distribution of this area. Results show that among the various front extraction meth- ods, the gradient method is simple but influenced greatly by noise. The canny algorithm presents a great advantage in front positioning accuracy, continuity, and computational efficiency. Wavelet analysis can be used in multi-scale analysis, but the computation is complex. The algorithm based on the law of universal gravity considers the influence of the value and po- sition of the center and neighborhood pixels, so it has better anti-noise ability and accuracy than the gradient method. Among the various eddy extraction methods, the OW method can identify the eddy core region well, but the extraction result is greatly influenced by the selection of the W value threshold. The WA method presents excellent accuracy but requires extensive calculation to obtain the streamline. The SSH-based method is simple but can only extract the eddy boundary and not the core area of the eddy. Early eddy extraction methods ignore the condition that muhi-core eddy structures may appear in oceans, and these methods are unable to identify multi-core eddy structures. The HD method combines the advantages of the OW and SSH-based methods. It can extract the boundary and core area of an eddy simuhaneously and can identify multi-core eddy structures. Conclusion According to the summary and analysis of various front and eddy extraction meth- ods, threshold selection for front and eddy extraction is difficult but is important to the quality of the extraction result. Many researchers have examined the threshold selection method. In addition, edge detection methods, such as gradient method and the canny algorithm, that are used widely in front extraction are designed for extracting sharp edges （ e. g. , solid edge ）. However, sea water is fluid and characterized by a weak edge. In other words, the edge of water masses with differ- ent properties is not obvious and more difficult to identify than a solid edge. Therefore, traditional edge detection methods are unsuitable for mesoscale front extraction due to the weak edge characteristic of marine environment element images. Given that the ocean front is the interface of different water masses, the region growing algorithm, which is used widely in image segmentation, can be utilized to segment the marine environmental element image of the study area into several independent parts that represent different water masses. Then, the boundaries we wish to extract （i. e. , the front） are searched.