中文摘要：

自动化鉴定并且 mesoscale 海洋旋涡追踪最近在物理海洋学成为了一个研究热点。几个方法被开发了并且适用在华南海(SCS ) 调查海洋旋涡的一般运动、几何的特征。然而，很少的研究试图检验内部进化处理的旋涡。在这研究，我们报导了一个混合方法基于他们的内部结构在 SCS 跟踪旋涡繁殖，它被旋涡中心，脚印边阶，和合成边阶描绘。埃迪鉴定和追踪的结果被一个官方补给底的空间与时间的模型代表。消失，再现，裂口，和合并的立刻的国家，动态进化过程，和事件的信息在一个 GIS 数据库被存储。结果被在北 SCS 对十个 Dongsha 气旋的旋涡(数据通信设备) 和三个长寿逆旋风的旋涡(王牌) 比较验证，它在以前的文学被报导。我们的学习证实了这些旋涡的发展。而且，我们在我们的数据库从 2005 ～ 2012 在这些区域发现了更像数据通信设备、像王牌的旋涡。消失，重现，切开，并且合并活动的空间分发分析证明在 SCS 的旋涡趋于到簇到吕宋岛岛的西北，吕宋岛海峡的西南，并且在越南的边缘的海附近。在这些区域的自台湾东面的菲律宾海流向日本的暖流侵入和复杂的海地板地形学是导致这些空间簇的可能的因素。

英文摘要：

Automated identification and tracking of mesoscale ocean eddies has recently become one research hotspot in physical oceanography. Several methods have been developed and applied to survey the general kinetic and geometric characteristics of the ocean eddies in the South China Sea（SCS）. However, very few studies attempt to examine eddies＇ internal evolution processes. In this study, we reported a hybrid method to trace eddies＇ propagation in the SCS based on their internal structures, which are characterized by eddy centers, footprint borders, and composite borders. Eddy identification and tracking results were represented by a GIS-based spatiotemporal model. Information on instant states, dynamic evolution processes, and events of disappearance, reappearance, split, and mergence is stored in a GIS database. Results were validated by comparing against the ten Dongsha Cyclonic Eddies（DCEs） and the three long-lived anticyclonic eddies（ACEs） in the northern SCS, which were reported in previous literature. Our study confirmed the development of these eddies. Furthermore, we found more DCE-like and ACE-like eddies in these areas from 2005 to 2012 in our database. Spatial distribution analysis of disappearing, reappearing, splitting, and merging activities shows that eddies in the SCS tend to cluster to the northwest of Luzon Island, southwest of Luzon Strait, and around the marginal sea of Vietnam. Kuroshio intrusions and the complex sea floor topography in these areas are the possible factors that lead to these spatial clusters.